PEER-REVIEW ARTICLE PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7278 Sustainable Cotton Farming Trends: Leveraging Natural Resource Survey Insights for U.S. Cotton Production Jeyran Bayramova,a Steven Pires,a,b Ed Barnes,a Gaylon Morgan,a Ryan Kurtz,a and Jesse Daystar a *Corresponding author: JDaystar@cottoninc.com DOI: 10.15376/biores.19.4.7279-7319 GRAPHICAL ABSTRACT PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7279 Sustainable Cotton Farming Trends: Leveraging Natural Resource Survey Insights for U.S. Cotton Production Jeyran Bayramova,a Steven Pires,a,b Ed Barnes,a Gaylon Morgan,a Ryan Kurtz,a and Jesse Daystar a Cotton cultivation in the United States is relevant globally, with the nation ranking among the top producers and exporters. This study examines conservation practice adoption trends and technological advancements in U.S. cotton production, focusing on sustainability and productivity. Efforts to improve cotton farming practices have reduced its environmental impacts, including decreased soil loss, water usage, and greenhouse gas emissions. Precision agriculture technologies have been instrumental in enhancing efficiency and reducing input costs, albeit with varying degrees of success. To gain deeper insights into cotton grower challenges and needs, a Natural Resource Survey was conducted in 2023 with 753 respondents. As a follow-up to the 2008 and 2015 surveys, the insights from this survey provide valuable data on grower practices and priorities, highlighting the increasing influence of climate change on cotton production. The findings underscore the importance of conservation agriculture and ongoing research to address grower concerns while improving production efficiency. Particularly noteworthy are the outcomes indicating an increase in cover crop adoption and a decrease in tillage practices, reflecting the industry’s commitment to sustainability. This study contributes to understanding the dynamics shaping the U.S. cotton industry and offers insights into the challenges and opportunities for continual improvement in U.S. cotton cultivation. DOI: 10.15376/biores.19.4.7279-7319 Keywords: Cotton; Survey; Sustainable agriculture; Precision technologies; Cover crops; Pest management and pesticides; Water use; Conservation practices; Biodiversity Contact information: a: Cotton Incorporated, 6399 Weston Pkwy, Cary, NC 27513; b: North Carolina State University, Department of Forest Biomaterials, 2820 Faucette Dr., Raleigh, NC 27607, USA; *Corresponding author: JDaystar@cottoninc.com INTRODUCTION Sustainability Trends in Cotton Production Cotton represents a significant global commodity, characterized by active trade in both its raw and processed forms. The United States is the third among global cotton producers and holds a dominant role in international exports, supplying over 35% of the world’s raw cotton (Cotton Sector at a Glance 2022). Cotton cultivation in the U.S. is centered in the 17 southern-tiered states known as the “Cotton Belt,” with Texas leading as the largest producer, accounting for approximately 40% of the nation’s cotton output in recent years. Cotton is predominantly cultivated for its lint, which serves as fiber, while its seeds are a valuable byproduct utilized in various ways, including cottonseed oil and animal feed. Notably, the inclusion of whole cottonseed in the diet of lactating dairy cows PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7280 has been shown to consistently reduce methane (CH4) emissions, which are among the most potent greenhouse gas emissions contributing to climate change (Grainger et al. 2010). Other parts of cotton plants, such as cotton stalks, have potential uses as renewable sources of cellulose (Prakash et al. 2024). Among fiber types, cotton is perceived by consumers (LifestyleMonitor, 2023) as more environmentally friendly; however, all fiber production has an environmental impact. Continuous improvement is a key tenant of U.S. cotton production. Over the past four decades, U.S. cotton growers have decreased soil loss by 45%, improved irrigation water use efficiency by 58%, and reduced greenhouse gas emissions by 25%, all while improving land use efficiency by 30% (Field to Market 2021). These achievements are primarily the result of improvements in irrigation management and precision technologies, cotton variety development, and Integrated Pest Management (IPM) strategies. Notably, the U.S. has seen a reduction of over 50% in insecticide applications in the past 30 years (Mississippi State University 2022), thanks to boll weevil eradication efforts, biotechnology, new cotton varieties, and IPM. Recognizing the advantages of digitalization in U.S. agriculture, current initiatives are directed towards enhancing farming efficiency, decreasing inputs, boosting yields, and ultimately sustaining the livelihoods of cotton farmers while also addressing environmental concerns. Precision technologies are increasingly spotlighted, with Autosteer/GPS applications integrated into the management of 40% of all U.S. farm and ranchland acreage for on-farm production by 2019, and adoption rates nearing 65% for cotton-planted acreage (McFadden et al. 2023). These technologies have resulted in a reduction of both overall inputs and costs for fertilizers, pesticides, and fuels among adopters, although the extent of reductions has been modest and varies depending on the type of technology utilized. Through the adoption of sustainable agriculture practices, such as cover crops and no-till, cotton growers help to restore soil health, mitigate climate change, and continually improve the industry. Thus, for the last decade, planted cover crop acreage increased by nearly 50%, while cotton farmers using reduced/no-till practices reached 45% (Wallander et al. 2021; ICAC 2022). Including cotton yields, the adoption of regenerative practices by U.S. farmers has resulted in an annual increase of over 8.8 million tons of carbon stored in cultivated cropland soils (USDA 2022). Informed consumers and industry stakeholders can contribute by opting for sustainable apparel choices and supporting initiatives like the Regenerative Cotton Fund and Climate Smart Cotton Program, both of which prioritize soil health, continual improvement, and the adoption of other conservation practices. Understanding the economic, social, and sustainability aspects of cotton production is essential in addressing its profitability and environmental concerns. Developed by Cotton Incorporated, the global cotton life cycle assessment (LCA), first introduced in 2010 and last updated in 2016, provides comprehensive data on cotton fiber production, textile manufacturing, and consumer use impacts. A key discovery from this LCA revealed that textile manufacturing and consumer usage were dominant categories across the entire cotton supply chain due to their substantial energy consumption—such as fiber processing during manufacturing and laundering in consumer use. Although the agricultural phase generally exhibited lower impacts in most categories, blue water consumption was highest for cotton cultivation (Cotton Incorporated 2016). Considering agriculture’s unique opportunity to mitigate climate change impacts, more research is needed to better understand how the adoption of conservation practices and precision agriculture technologies is enhancing crop productivity and increasing the PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7281 resiliency of agricultural landscapes globally. In general, conservation practices, such as cover cropping and reduced/no tillage, can lower the environmental impacts of cotton production and improve soil health (Soil Health Institute 2023). There remains a limited understanding of how beneficial these practices are across regions with different topography, climatic conditions, and water availability. The latter, water availability, has posed challenges to all agricultural sectors, including cotton production, potentially affecting yields due to changes in precipitation patterns, increased weather extremes, and shifts in pest pressure. As examples, Hurricane Harvey resulted in a $100 million loss to Texas cotton in 2017 (Fannin 2017), while drought conditions caused a record 46% crop loss in the U.S. when considering all-cotton production in 2022 (Meyer et al. 2023). To address water supply challenges, further research is needed to understand and cope with excessive and limited water for cultivating cotton into the future. This includes exploring adaptations such as stress-resistant crop varieties, sustainable agricultural practices such as cover crop and no-tillage, modifying IPM and nutrient management recommendations, improving irrigation methods, etc. Climate change may also lead to water scarcity in some regions, forcing a shift in acreage to non-irrigated production due to limited water availability and declining profitability. However, amidst these challenges, there are also emerging opportunities. For instance, rising temperatures have enabled regions such as Kansas to expand cotton cultivation notably compared to a decade prior, with statewide cotton acreage witnessing a twelvefold increase between 2015 and 2020 (Kansas AGGROWTH 2021, 2019). Along with climate change and extreme weather events, biodiversity loss is another challenge and was highlighted as a top three risks in the World Economic Forum’s 2022 Global Risks Report (Foro Económico Mundial et al. 2022). Cotton growers recognize the importance of biodiversity, which is why the lands becoming unsuitable for cotton cultivation are often repurposed into habitats for various wildlife species, including birds like quail, as well as pollinators (CottonToday). These initiatives not only contribute to wildlife conservation but also enhance the efficiency of neighboring cotton fields. However, there is still a deficiency in understanding the factors correlated between cotton cultivation and preserving biodiversity. Access to updated agricultural data and insights into grower concerns and their research needs are critical for guiding research and development efforts aimed at supporting grower profitability while mitigating environmental footprints. In this context, insights from the Natural Resource Survey results hold particular significance. Natural Resource Survey In the summer of 2023, Cotton Incorporated launched a Natural Resource Survey (NRS) targeting U.S. cotton producers, seeking to evaluate the environmental footprint of cotton, contribute to the U.S. LCA project, and gain a better understanding of grower practices and challenges. These survey results were collected digitally, and invitations were sent to growers via emails and postcards. A third-party market research company assisted in the digital survey administration. A copy of the survey questionnaire is provided in Appendix 1. The survey data produced aimed to: 1. Assess changes in grower practices and priorities between 2008 and 2023. 2. Identify grower challenges. 3. Provide U.S. cotton production data for the U.S. life cycle assessment. 4. Gather growers’ insights regarding practices and agricultural technologies that PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7282 positively impact resource efficiency and productivity. 5. Maintain an accurate understanding of growers’ research needs. EXPERIMENTAL The Natural Resource Survey covered a wide range of topics with 62 core questions, including demographics, grower practices and concerns, and field-level data in the 2021 or 2022 crop years. Similar surveys were conducted in 2008 and 2015, enabling comparisons where production data in those surveys also were representative of conditions from the previous crop year. However, questions related to grower attitudes are reflective of the year the survey was conducted. For simplicity, in presenting the results, the year the survey was conducted, namely 2023, is used in this report. Consistent with prior methodologies, the 2023 survey reached growers across 17 cotton-growing states. The results were summarized by assigning data from all these states to four regions – Far West (CA, AZ, NM), Southwest (TX, OK, KS), Midsouth (MO, AR, LA, MS, TN), and Southeast (AL, FL, GA, SC, NC, VA) to provide a representative response about each area's production as illustrated in Fig. 1. The data have been analyzed using different tools, including Microsoft Excel and Power BI. Fig. 1. Cotton growing states in four regions The survey focused on filling the knowledge gap about how farming practices are connected and their broader impacts at a national level across all U.S. cotton-growing regions. Additionally, the survey aimed to offer direction for future research efforts. The examination of independent variables, such as cultivation methods and technology adoption, facilitated the establishment of correlations with dependent variables including field productivity (yield), resource efficiency (nitrogen and water use), and grower concerns (Fig. 2). However, it is important to approach these connections with caution, since each grower faces unique variables and circumstances that can influence how their PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7283 fields perform. It should be noted that the growers in each survey are not the same producers, and such trends between years may not reflect changes in reality. Rather, it may be a different sample group. However, the results do provide some insights into shifts in the industry that are useful to the goals of this study. Fig. 2. Cotton growing production-system simplified model with independent variables labeled in green (more grower control) and blue (less grower control) and the corresponding dependent variables represented in the yellow labels. Survey Method The survey was conducted during May, June, and July of 2023. Cotton Incorporated facilitated outreach by sending eleven thousand postcards to farmers who had produced cotton in 2021. These postcards were dispatched three times between the end of May and the end of July 2023. Additionally, a total of 4,300 emails were sent to request survey participation during this period. The survey encompassed all U.S. cotton-growing regions, yielding 753 responses, as illustrated in Fig. 3. Texas provided the most responses, at 37% of the total, followed by Georgia, the second-largest cotton-producing state, at 13%. In general, the percentage of responses per state corresponded to state-level cotton production volumes. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7284 Fig. 3. Cumulative number of responses by date and state Fig. 4. Percent of respondents by region in the 2015 and 2023 surveys For comparison, in the previous 2015 survey data, there were a total of 925 respondents, with the majority of responses originating from the Southeast region (45%). The Southwest region then accounted for 30% of responses, while in 2023, it constituted the majority with 43% of responses. Conversely, the Far West region witnessed a slight decrease from 4% in 2015 to 3% in 2023. In general, cotton output in the Far West has been consistently decreasing due to declining water resources and competition from higher value crops, such as almonds and processing tomatoes in California (Geisseler and Horwath 2016). The percentage of responses by regions through 2015 and 2023 is shown in Fig. 4. Key factors, such as weather conditions and production costs, can significantly influence cotton farming trends and may contribute to the observed differences in eligibility and interest in participating in the survey. According to USDA-NASS data, in PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7285 2022, 16% of planted acres in the Far West went unharvested due to water shortages, while the Southwest experienced a severe drought resulting in the loss of 52% of planted acres (Fig. 5). Additionally, cotton acreage remained at a record low from 2021 to 2023 due to a prolonged drought reducing water allocations in the region (USDA Quick Stats 2024). Consequently, it’s important to note that data from the Far West may not accurately reflect typical production conditions, given the prevailing challenges posed by the long-term drought. Although irrigation scheduling technologies have contributed to improved water productivity in cotton farming, their adoption by farmers remains limited, indicating significant room for improvement (Barnes et al. 2020). Matching irrigation schedules with the crop’s water use is important, especially during the flowering stage when cotton is most sensitive to water shortages. Optimizing the timing of irrigation termination (IT) for each geographical area is also essential, as early IT can save water but may not maximize yields, while late IT can lead to increased pest damage and reduced yield quality (Koudahe et al., 2021). Continued advancements in sensor and water delivery technologies, enhanced crop simulation models, and the development of drought-tolerant cotton varieties are just a few examples of strategies to address challenges posed by reduced water allocations and droughts (Barnes et al. 2020). Additionally, as irrigation water supplies become depleted, it will be important to consider rotation with high residue crops or cover crops to increase infiltration and soil water holding capacity when possible. Fig. 5. Crop loss data by regions in 2022 (USDA Quick Stats 2022) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7286 Fig. 6. A 30-year average rainfall from 1991 to 2020 in cotton-producing states (rainfall data from Prism Climate Group) To underscore the environmental differences among cotton-growing regions, Fig. 6 depicts precipitation patterns, which show adequate precipitation to grow a cotton crop in the Southeast and Mid-South, while a dramatic precipitation gradient occurs within the Southwest region. In the West region, cotton cannot be grown without irrigation due to the very low annual precipitation. Figure 7 illustrates the diverse soil types across the U.S. and farming practices are significantly influenced by the predominant soil type characteristics across and within each region: Ultisols in the Southeast, Alfisols in the Midsouth, Mollisols in the Southwest, and Aridisols in the Far West. Fig. 7. Dominant soil orders for the U.S. (USDA Natural Resources Conservation Service, 1998) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7287 Respondent Demographics and Data Representativeness The 2023 survey revealed that nearly half of respondents were 51 or older in age and had over 20 years of experience in cotton farming (Fig. 8). Overall demographic makeup of respondents was similar to the 2015 survey with the exception of increased participation of the younger generation (18 to 30) in the Far West increasing from 3% to 20% in 2023. The group of farmers growing cotton during the last 5 years constituted 16% compared to an average of 7 to 8% of the same group observed in other regions (Fig.8). However, it should be noted that the Far West also had the lowest cotton acres and response rate of all regions surveyed, with only 3% of the total responses. In general, responses from the cotton-growing states were reflective of the distribution of cotton-growing acreage, with Texas and Georgia having the highest number of respondents. According to USDA-NASS data, cotton-planted acreage across all 17 states totaled 10.2 million acres in 2023, whereas the surveyed acreage amounted to approximately 0.94 million acres (Fig. 9). The surveyed cotton acreage accounted for 9.2% of the total U.S. cotton cultivated acres. In comparison, the previous 2015 survey reported 818,804 cotton acres, which represented 10% of the cotton planted in the US in 2015. Fig. 8. Distribution of respondents categorized by age and years of growing experience (Refer to Q59 and Q60 in Appendix 1) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7288 Fig. 9. Percent of U.S. cotton acres planted in each state in the 2023 growing season ( orange) and the percentage of cotton acres by state from survey participants (blue) RESULTS AND DISCUSSION Cotton Grower Concerns Within the Natural Resource Survey, respondents were prompted to assess 29 randomly presented concerns or challenges linked to cotton production, scoring each as a Major, Moderate, or Not an Issue on their farm. Noteworthy concerns included cotton production input costs, weed resistance to herbicides, weed control, and cottonseed value, which have consistently ranked as the top four major concerns since the previous survey, comprising 78%, 65%, 55%, and 50% of responses, respectively (Fig. 10). PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7289 Fig. 10. A summary ranking of the top 10 cotton growers’ concerns In contrast, the spread of plant disease and weeds declined from the 5th to the 11th ranking in the latest survey. New concerns introduced in the 2023 survey, such as nematodes, now rank 9th, with a higher percentage of responses from the southeast and midsouth regions. Cotton grower’s concerns about water conservation are evidenced in overall water productivity increases through the adoption of better irrigation delivery systems (Barnes et al. 2020), and adequate water supply remains in their top 10 concerns, rising from 10th place in 2015 to 7th in 2023. Additionally, concerns were raised regarding the lack of new crop protection products and insect resistance to insecticides and Bt cotton, resulting in a 4-point difference. Table 1 displays a shift in concern rankings, with increased concern towards the increasing occurrence of extreme weather events, rising from 13th to 5th place. This shift underscores the escalating impact of climate change effects on these concerns. For grower concerns by region, see ST 1 in Appendix 2. Grower Communication Methods In order to consistently provide producers with updated information to enhance their production efficiency, it is critical to understand the sources from which they acquire information about new technology and practices. Thus, the 2023 survey respondents evaluated 17 information sources based on their reliance, ranging from none to slight, moderate, or great dependence. The survey findings emphasize that cotton producers heavily rely on face-to-face interactions, consultants, and extension agents for information on new technologies (Fig. 11-A). However, there has been a decline in magazine interest since 2008, while apps are more widely utilized. Additionally, social media platforms, particularly YouTube and Facebook, are among the most used social media platforms viewed by producers, as illustrated in Fig. 11-B. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7290 Table 1. A Summary Ranking of Cotton Growers’ Concerns through 2015 and 2023 with Light Blue Highlighting Total Ranking <5, and Dark Blue >5 (Refer to Q26 in Appendix 1) Cotton Production Concerns Major Issue Rank total Δ 2023 2015 2023 2015 Cotton production input costs 78% 81% 1 1 0 Weed resistance to herbicides 65% 69% 2 2 0 Weed control 55% 64% 3 3 0 Cottonseed value 50% 51% 4 4 0 Increased frequency of drought and extreme weather events (climate change) 50% 30% 5 13 8 Seedling vigor and stand establishment 46% 42% 6 6 0 Adequate water supply 42% 37% 7 10 3 Cotton’s tolerance to heat and drought 40% 39% 8 8 0 Consumer attitudes about agriculture’s impact on the environment 38% 40% 9 7 -2 Lack of new crop protection products (insecticides, herbicides, etc.) 34% 29% 10 14 4 Spread of plant diseases and weeds 30% 42% 11 5 -6 Insect resistance to insecticides and Bt cotton 30% 28% 12 16 4 Efficient use of fertilizer 28% 37% 13 9 -4 Herbicides drift 27% 28% 14 15 1 Disease concerns related to nematodes, target spots, viruses, etc. 24% N/A 15 New Variety selection 24% 34% 16 11 -5 Plant bug control 23% 32% 17 12 -5 Soil erosion 19% 19% 18 21 3 Harvest aid materials and application timing 19% 24% 19 19 0 Stinkbug control 19% 23% 19 20 1 Monitoring cotton’s plant growth 17% 25% 21 18 -3 Soil sampling and analysis for fertilization 17% 27% 22 17 -5 Soil compaction 16% 17% 23 22 -1 Insecticides drift 11% 28% 24 15 -9 Water salinity of irrigation wells 11% 7% 25 26 1 Effects of agriculture on wildlife 10% 10% 26 24 -2 Soil salinity 9% 8% 27 25 -2 Water quality protection from agricultural runoff 8% 12% 28 23 -5 Dust from harvesting, farming, gins 4% 4% 29 27 -2 PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7291 Selected Farm Characteristics The 2023 survey explored land and management practices as well as their associated characteristics through a series of multiple questions. Respondents were asked to provide information related to their land and management practices within a selected representative cotton field. One of the questions was about the field size, as this parameter may impact the feasibility of adopting certain practices for producers. In the 2021/2022 growing season, the average size of the representative cotton field varied across regions, with the Southwest reporting the largest size at 187 acres, while the Far West reported the smallest at 73 acres. The average representative field size by region across all surveyed years has been compared and analyzed, see Fig. 12. In the 2023 survey data, larger average field sizes were reported for the Southwest and Midsouth regions compared to the previous two surveys, while sizes remained consistent for the Far West and Southeast regions. In the Far West, the design of irrigation systems often limits field size to ensure efficient water distribution, necessitating restricted field lengths. On the other hand, in the Southeast, field size limitations often stem from topographical features, such as established tree lines. (A) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7292 (B) Fig. 11. Preferred information sources: moderate to high ranking (Refer to Q61 in Appendix 1). (A) Non-digital source of information by respondents through 2008, 2015 and 2023 survey years. (B) Digital source of information by respondents through 2008, 2015, and 2023 survey years Fig. 12. Average field size by region for 2008, 2015, and 2023 survey data (Refer to Q28 in Appendix 1) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7293 Land Use In addition to reporting the acreage of selected cotton fields, the 2023 survey respondents were asked to share details about their entire land holdings. In total, the farmers managed 1,963,111 crop acres (+17% from 2015), with 48% (-1% from 2015) planted to cotton. This allocation translates to 9.2% (-1% from 2015) of the total cotton planted in the United States in 2023. Fig. 13. Acres of irrigated and non-irrigated cotton, non-cotton crops, and natural land from the 2023 survey. (Refer to Q1 in Appendix 1) Notably, only 39% (-6% from 2015) of the surveyed cotton acres received irrigation, which closely aligns with the 36% of irrigated acres reported by the USDA 2018 Farm and Ranch Irrigation Survey (USDA Quick Stats 2022). In comparison to the 2015 survey data, where 49% of the crop acres were planted to cotton, and 45% of the cotton acres were irrigated, the current survey reflects a downward shift. In the 2023 survey, the Far West region had 99% of irrigated cotton fields (and high yields), whereas the Southwest, Southeast, and Midsouth regions reported 36%, 27%, and 56%, respectively. Expanding beyond cropland, respondents also reported a combined 245,550 acres of natural land within their farming enterprises, constituting around 13% of total land ownership. This percentage aligns with the proportion of natural land reported in the 2015 survey data. Figure 13 illustrates all acres by 2023 survey respondents and Fig. 14 shows the percentage of non-irrigated and irrigated cotton acres through the survey years. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7294 Fig. 14. Irrigated and non-irrigated cotton through years and regions Around 40% (775,835 acres) were reported as land for crops other than cotton. Table 2 displays the additional crops cultivated by respondents and the percentage of respondents growing them, showcasing slight variations from the 2008 and 2015 results. The fluctuations in the utilization of other crops over the years can be attributed to the fluctuating commodity prices observed during 2020 to 2021. Consequently, wheat experienced a decrease, whereas peanuts and pasture saw marked increases (USDA NASS 2021). Nevertheless, the primary alternative cash crops in the U.S. during the 2021 growing season included corn, soybean, and wheat, with corn dominating across most regions. Notably, in the Midsouth, soybean took a significant lead, comprising 84% of the crops. The Far West region had a diverse set of crops that include various vegetables and orchards suited to its unique climate (Table 3). PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7295 Table 2. The Percentage of Respondents Who Indicated They Commercially Produced the Crops Listed Crop % Grown 2008 % Grown 2015 % Grown 2023 Corn 48% 46% 46% Wheat 47% 40% 31% Soybeans 37% 39% 32% Sorghum 25% 19% 21% Natural Vegetation 22% 17% 18% Pasture 21% 16% 26% Hay 19% 15% 26% Peanuts 18% 27% 26% Alfalfa 7% 4% 5% Vegetables 6% 5% 5% Orchards 6% 3% 3% Rice 4% 3% 3% Vines 1% 1% <1% None of the above 0% 3% 12% Table 3. Alternative Cash Crops by Respondents by Regions (Refer to Q3 in Appendix 1) Commercial crop/Livestock Region Southeast Midsouth Southwest Far West U.S. Corn 54.6% 73.6% 29.0% 44.0% 46.5% Soybeans 40.4% 83.7% 6.5% 0.0% 31.9% Wheat 21.8% 11.6% 44.4% 44.0% 30.5% Cattle 29.1% 18.6% 34.9% 24.0% 29.6% Peanuts 65.5% 7.0% 2.8% 0.0% 26.3% Hay 24.4% 17.1% 31.2% 24.0% 26.0% Pasture 25.1% 13.2% 31.2% 24.0% 25.6% Sorghum 5.8% 3.1% 41.1% 12.0% 20.7% Natural Vegetation 26.6% 13.2% 12.0% 12.0% 17.5% None of the above 6.6% 8.5% 17.6% 20.0% 12.1% Other 4.7% 2.3% 9.0% 12.0% 6.4% Vegetables 7.6% 1.6% 1.9% 28.0% 4.8% Alfalfa 0.4% 0.0% 6.5% 52.0% 4.6% Rice 0.4% 14.0% 1.5% 4.0% 3.3% Orchards 4.4% 0.0% 1.2% 36.0% 3.3% Poultry 6.2% 0.0% 0.6% 0.0% 2.5% Dairy 0.4% 0.8% 1.2% 4.0% 0.9% Swine 1.5% 0.0% 0.3% 4.0% 0.8% Vines 0.0% 0.0% 0.6% 4.0% 0.4% Crop Rotation and Cover Crops The 2023 survey sought to understand how farmers utilized land during the offseason, recognizing its potential for various crops, which can enhance revenue and benefit the land. Data from the survey indicates an increase in cover crop utilization among cotton farmers, with 48% of respondents planting cover crops, compared to 20% in the 2015 survey. Respondents reported an increase from 9% to 14% in 2015 to 2023 in native PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7296 vegetation practice, respectively. Noteworthy is the positive trajectory witnessed in the Far West region, with 0% of native vegetation usage in 2015 to 7% in 2023 (Fig. 16). The evolving trends in cover crop adoption across time and regions emphasize the increasing preference for cover crops such as wheat (64%), cereal rye (30%), and mixed crops (13%) — a blend of diverse plant species promoting soil vitality and biodiversity. By 2023 survey respondents, cotton was planted annually (23%), every other year (22%), 2 of 3 years (25%), and 1 of 3 years (12%). Fig. 15. Cover crop and residue management practices by 2015 and 2023 survey respondents The survey also explored how growers utilized their land during the offseason, with a focus on regional differences. Fig. 16. Cover crop practices across regions over time (For the 2023 Survey, refer to Q40 in Appendix 1) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7297 Farmers adopting cover crops reported an increase in cotton yields, especially in the Southwest, where planted cover crops resulted in a 14% increase in cotton yields compared to practices without cover. In the Southeast and Midsouth, a similar practice reported a 5% and an 8% increase in yield, respectively. However, in the Far West region, with its unique environment, the reported yields using planted cover crops were lower compared to those not utilizing these practices. Cotton serves as the main crop in a rotation with other crops every 3 to 4 years. As these fields may include low-residue crops, introducing cover crops becomes an opportunity for cotton farmers to elevate residue levels. This strategy aligns with the common practice of planting cotton following a winter cover crop, which helps safeguard the cotton seedlings from early spring wind damage. Tillage Practices For almost three decades, Cotton Incorporated has been underscoring the benefits of conservation and no-till practices (Daystar et al. 2017). For clarity, each tillage practice can be explained as follows: 1. No-till/strip-till: Soil undisturbed except for narrow strips, preserving surface residue. 2. Conservation tillage: Leaves approximately 15% to 30% or more crop residue on the soil surface after planting. 3. Conventional tillage: Full-width soil disturbance, with weed control via herbicides or cultivation. Over the span of 2008 to 2023, there has been a shift in tillage practices: conventional tillage has declined by approximately 10%, whereas no-till/strip-till methods have increased by 20% (Fig. 17). Regionally, the Southeast region utilizes more no-till/strip-till practices (68%), whereas conventional tillage accounts for 15% (For regional breakdown, refer to ST2, Appendix 2). This shift in tillage approaches may reflect the influence of educational efforts, along with other factors, such as weed pressure which may also drive changes in tillage practices. Additionally, growers may be motivated by broader agronomic benefits, a decrease in input costs, and additional cotton marketing opportunities. The transition from conventional tillage to no-till/strip-tilling holds the promise of cost savings for growers by reducing time and energy requirements (“Soil Health Institute,” 2023). However, concerns loom among many conventional tillage growers about potential reductions in cotton yields. To probe the relationship between tillage practices and cotton yield, a detailed analysis was conducted, plotting the yield for each tillage practice across U.S. regions (Fig. 18). The Far West was the only region where conventional tillage resulted in higher yields, averaging 1672 lbs/acre, while in other regions, conventional tillage practices reported lower average yields. In the Midsouth and Southwest, conservation tillage emerged with the highest reported cotton yields, registering 1200 lbs/acre and 981 lbs/acre, respectively. The Southeast had a high adoption of no-till/strip- till and the highest reported yield for this practice, averaging 1086 lbs/acre. Research shows increased yields on cotton cultivation in no-till fields with cover crops, including (Soil Health Institute 2023) and (University of Arkansas System 2016); however, results are variable and may not correlate to improved yields in all situations. It should also be noted that no-till and cover cropping provide other benefits aside from yield, such as increased soil carbon and soil water holding capacity, among others. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7298 Fig. 17. Tillage systems use identified in the 2008, 2015, and 2023 surveys. (For the 2023 Survey, refer to Q43 in Appendix 1) Fig. 18. U.S. cotton yields based on tillage method and region (Refer to Q43 and Q38 in Appendix 1) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7299 Soil Management In the 2023 survey, 97% of respondents adopted at least one of the listed practices to mitigate soil erosion. Strip-till/no-till remained prevalent, and the usage of other specific practices remained relatively stable between 2008 and 2023. Additionally, in 2008, 39% of respondents reported using winter cover crops, from 48% in 2015 to 65% in 2023. Irrigation management has increased by 5% since 2015, reaching 45%, while the prevalence of precisely leveled fields has nearly halved during the same period. Fig. 19 illustrates a full list of practices to mitigate soil erosion by 2023 survey respondents. For regional breakdown, refer to ST3, Appendix 2). Fig. 19. Practices to minimize soil erosion among 2023 survey respondents (Refer to Q8 in Appendix 1) Since 2008, soil testing to determine fertilizer application rates has remained a predominant practice among producers, with 77% in 2023 (Fig. 20). Most respondents (56%) indicated soil sampling annually, while 6% reported never using soil fertility testing, primarily in the Far West and Southwest regions. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7300 Fig. 20. Fertilizer factors rated by 2023 survey respondents (Refer to Q10 in Appendix 1) Table 4 indicates that more than 50% of growers did soil sampling once or more a year, while 20% – once every 2 years and 13% – once every 3 years. Other factors utilized in the fertilizer evaluation process showed changes as follows: yield goals rose to 67% from 61% in 2015, consultant recommendations increased to 56% from 49% in 2015, and petiole or leaf testing grew to 34% from 23% in 2015. Table 4. Frequency of Soil Fertility Testing in Cotton Fields by 2023 Survey (Refer to Q9 in Appendix 1) Region Once or more a year Once every 2 years Once every 3 years Once every 4 or more years Never Far West 38% 8% N/A 31% 23% Midsouth 31% 35% 33% 1% N/A Southeast 85% 11% 3% N/A 1% Southwest 40% 21% 15% 12% 11% U.S. 56% 20% 13% 6% 6% Source of Organic Matter In the 2023 survey, respondents used various sources of organic matter such as manure, gin trash, or cover crops to enhance soil health. In the Far West region, the respondents' total acreage where manure and gin trash (gin waste) were applied was notably larger compared to other regions where various cover crops were the dominant source of organic cover. When comparing these practices with the 2015 survey results, the average total acreage where gin trash/cotton compost was applied remained unchanged (Fig. 21). However, the use of manure decreased to 8.5%, down from 14.3% in 2015. On the other hand, the application of multispecies cover crops increased to 6.3%, up from 2.5% in 2015, as a percentage of respondents’ total acreage. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7301 Fig. 21. The average percentage of respondents' total acreage attributed to the source of organic matter across regions in the 2023 survey. The average U.S. data is presented by years (Refer to Q11 in Appendix 1). Fertilizer Management The precision in fertilizer management is presented in Fig. 22, which illustrates nutrient use efficiencies for nitrogen, phosphate, and potassium (N, P, K, respectively) by region (mass of cotton fiber produced per mass of nutrient applied), where higher nutrient use efficiency values equate to higher cotton yield per unit of fertilizer applied. Like all crops, N, P, and K are primary nutrients critical to the growth of the plant, and nitrogen is most susceptible to loss due to its high mobility (Wyatt et al. 2019). Maintaining a consistent replacement of nitrogen is crucial in cotton farming, given that nitrogen is extracted from the field in cottonseed. While soils can contain ample phosphate and/or potassium naturally, the availability of these nutrients varies by region and soil type. For example, around 15 to 30 lbs/acre of potassium is removed when cotton is harvested, depending on yield. Additionally, managing nitrogen supplied by soil mineralization is complex, as it is influenced by factors such as soil organic matter content and previous crops. For instance, cotton cultivated on soils containing higher clay contents after peanuts may require lower nitrogen application (Frame et al. 2016). PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7302 Fig. 22. Nutrient use efficiencies for nitrogen, phosphate, and potassium (N, P, K, respectively) by region (mass of cotton fiber produced per mass of nutrient applied, where higher nutrient use efficiency values equate to higher cotton yield per unit of fertilizer applied). Refer to Q48 in Appendix 1 In general, soils with high infiltration rates and low nutrient retention capacities, such as sandy soils or well-aggregated soils with low organic matter, are prone to nutrient leaching compared to soils with higher clay and organic matter content (Wyatt et al. 2019). The classification of soil textures into three main types – light, medium, and heavy – reflects their respective sandy, loamy, and clayey characteristics, determined by the proportions of sand, silt, and clay they contain. Fig. 23 illustrates the mapping of these soil textures through USA regions. Fig. 23. Soil composition across the U.S. by NASA Earth Observatory (Miller and White 1998) PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7303 Nitrogen application levels vary across states depending on whether the field was irrigated or non-irrigated, largely due to the increased yield potential in irrigated fields. For instance, the average nitrogen application for irrigated fields across all regions ranged between 99 and 109 lbs/acre, with the lowest observed in the Midsouth region and the highest in the Far West. Conversely, non-irrigated fields in the Midsouth and Southeast regions exhibited relatively higher nitrogen application levels, at 106 lbs/acre and 97 lbs/acre respectively, in contrast to the Far West and Southwest regions, where the applied levels were notably lower, at 80 and 62 lbs/acre, respectively. Due to the low number of respondents from the Far West, the fertilizer rates in this region, however, may not accurately reflect actual application practices. Potassium application levels also reveal regional disparities, influenced by the irrigation factor and soil type. In the Southwest region, both non-irrigated and irrigated fields exhibited the lowest fertilizer applications, with 18 and 35 lbs/acre respectively. These regional differences, which are illustrated in Fig. 24, highlight the nuanced fertilizer application practices tailored to specific soil, climate conditions, and yield potential. Recommended fertilizer levels also vary by state. In Missouri, for instance, a total range of 80 to 120 lbs/acre of nitrogen is considered adequate, with split applications recommended for both sandy and silt soils (University of Missouri). In Mississippi, for medium-textured soils with a yield potential of two bales per acre, it is recommended to apply 120 to 140 pounds of nitrogen per acre (Mississippi State University 2017). The respondents reported the following as their main sources of nitrogen: during pre-planting, dry blend (42%), liquid blend (23%), urea (9%), and ammonia (2%); while in-season, these practices accounted for 25%, 34%, 15%, and 1%, respectively. Most respondents (77%) indicated that fertilizer application levels were determined based on soil test recommendations, a practice supported by the high nutrient use efficiency values mentioned earlier. Nitrogen (N) application methods varied, with 32% injecting N into the soil profile, 12% applying a band to the surface, 35% broadcasting, and 6% broadcasting followed by incorporation. On average, two trips were made during the season to apply fertilizer, increasing the probability of its availability to the crop when needed. One-third of respondents (34%) reported using nitrification inhibitors with most responses coming from the Midsouth region. Cotton grows optimally within a soil pH range of 5.8 to 6.5, targeting 6.2. Low pH can lead to toxic element concentrations, while pH over 7.0 affects nutrient availability (Frame et al. 2016). Various products are employed to raise pH levels. According to a 2023 survey, 33% of respondents, mainly from the Southeast, favor dolomitic lime, while 21%—predominantly from the Midsouth region— use lime. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7304 (A) (B) Fig. 24. State-wise average fertilizer application (in pounds) vs. yield (in lbs/acre) by 2023 survey. (A) Non-irrigated and (B) irrigated cotton fields Irrigation Management Survey respondents reported that approximately 39% (363,000 acres) of their cotton croplands were irrigated. The primary water source for cotton irrigation is well water, accounting for 85%. Additionally, 8% of respondents reported using on-farm surface water, and 4% reported using off-farm surface water in addition to well water. The PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7305 highest average inches of irrigation water was observed in the Far West region, amounting to 36 inches, while the Midsouth region reported the lowest at 9 inches. This disparity can be attributed to the specific climate of each region and variability in average annual precipitation. The primary energy sources for irrigation reported by respondents are electric (73%), diesel (20%), and natural gas (6%). Figure 25 depicts all the mentioned irrigation aspects, while Table 5 provides the regional percentage of irrigation sources, where on- farm sources are predominant in the Southeast region, and off-farm sources are prevalent in the Far West. Fig. 25. Irrigated and non-irrigated cotton acreage, irrigation inches, water source, and energy source for irrigation by 2023 survey (Refer to Q1, Q30, Q33, and Q37 in Appendix 1) Table 5. Irrigation Source by Region (Refer to Q33 in Appendix 1) Region Well pump On-farm Off-farm Other Southeast 74% 22% 0% 4% Midsouth 93% 6% 0% 2% Southwest 91% 0% 6% 3% Far West 65% 0% 24% 12% U.S. 85% 8% 4% 4% When comparing survey results for producers using irrigation from 2008 and 2015 to 2023, a consistent trend is evident toward reduced use of surface irrigation, as depicted in Fig. 26. Specifically, the utilization of furrow systems has decreased from 44% in 2008 to 26% in 2023, while the adoption of pivot/sprinkler systems has increased from 49% in 2008 to 59% in 2023. In general, the shift to pressurized systems, such as pivot systems, is associated with higher water use efficiencies, given their enhanced precision and PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7306 operational control. Additionally, there is an observable trend towards an increased adoption of drip (surface or subsurface) irrigation systems at approximately 15%. The adoption was observed mainly in the Southwest region (Refer to ST 4 in Appendix 2), where the return on investment is better and irrigation water capacity is limited. Fig. 26. Irrigation systems used in 2008, 2015, and 2023. Less than 1% of respondents selected “Other” in 2023. (For the 2023 Survey, refer to Q32 in Appendix 1) In the management of irrigation tailwater from furrow/basin irrigation, a majority of respondents (68%) reported implementing adjustments to field slope and length to minimize runoff. Additionally, 14% utilize holding ponds, and 10% specifically address tailwater runoff (Refer to ST 5 in Appendix 2). Notably, around 16% of farmers expressed concerns about water salinity in their farm wells, a slight increase from the previous 2015 survey at 11%. Efforts to enhance the efficiency of irrigation water usage can be advanced by promoting greater adoption of flow measuring devices. These devices serve as an effective means to ensure the smooth functioning of an irrigation system. Notably, the utilization of flow meters and irrigation scheduling has increased to 52% for both practices in the 2023 survey year, up from 38% and 34% in 2015, respectively. Additionally, there has been an increase in the adoption of moisture monitoring, climbing from 21% to 44%. Figure 27 illustrates irrigation efficiency improvement practices over the years on regional and national levels. 5.0% 6.3% 15% 44% 35% 26% 49% 56% 59% 2% 2% 0% 20% 40% 60% 80% 100% 2008 2015 2023 P e rc e n t o f A c re s Other Pivot/Sprinkler Furrow/Basin Drip PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7307 Fig. 27. Irrigation efficiency improvement practices adopted by region through 2015 and 2023 (For the 2023 Survey, refer to Q31 in Appendix 1) Precision Farming Technologies The survey data indicate a noticeable upward trend in the adoption of various technologies, except for soil sampling, which has remained steady at 46% (Fig. 28). Autosteer/GPS technology, in particular, has experienced a significant increase, surging from 46% in 2008 to 69% in 2015 and further to 86% in 2023. The rapid rise in autosteer technology adoption, surpassing other options, signifies its emergence as a standard feature on new equipment which may require minimal preparation to use compared to alternatives that involve downloading, interpreting, and re-uploading maps. A new report on precision technologies (McFadden et al. 2023) suggests that these benefits, along with potential savings from reduced skips and overlaps in input costs (like fuel, seed, nutrients, and pesticides), are likely driving the increase in adoption rates. The survey further revealed a significant increase in yield monitor adoption (from 20% in 2015 to 35% in 2023) across all regions, reflecting a growing inclination towards integrating data-collecting technologies into agricultural equipment. According to the same USDA report, yield monitors are predominantly employed to assist in determining crop input usage in cotton farming. As shown in Fig. 29, the Midsouth and Southwest regions experienced the most significant increase, with an average rise of 20% from 2015 to 2023. As new technologies evolved, there were new additions to the question of precision technologies. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7308 Fig. 28. Precision technologies used in 2008, 2015, and 2023. (*: Soil Sampling question wasn’t asked in the 2008 survey; it was only introduced in 2015). (For the 2023 Survey, refer to Q19 in Appendix 1). Fig. 29. Precision technologies by regions and over time by 2023 survey (For the 2023 Survey, refer to Q19 in Appendix 1) These additions included the use of see and spray systems (such as Weed IT, WeedSeeker, John Deere, etc.), swath control, and unpiloted aerial vehicles (UAVs). The PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7309 survey found that most respondents (71%) reported using swath control on their spray boom, and 40% reported using swath control on their planter. Additionally, nearly 6% of respondents reported operating UAVs, while 5% reported deploying see and spray systems (Refer to ST6 in Appendix 2). In general, only 4% of all respondents reported not using precision technologies. Growers utilizing precision technologies have reported higher average cotton yields across all growing regions, except for the Far West region. However, due to the small sample size in the Far West, the differences shown may not be significant. Automation Automation, including the integration of driverless tractor technology, may significantly enhance operational efficiency and precision in agricultural practices by streamlining tasks such as planting, spraying, and harvesting. The 2023 survey introduced some new questions to cotton farmers regarding the benefits and impediments of using driverless tractors on their farms, the machines that are capable of operating without human intervention. More than 50% of respondents reported labor savings as one of the perceived future benefits of driverless tractors, 41% cited improved efficiency, 28% highlighted decreased worker exposure, and 34% considered the technology to have no benefits (Fig. 30). Fig. 30. Perceived benefits of using driverless tractors on farms by 2023 survey respondents (Refer to Q22 in Appendix 1) Another question focused on potential obstacles to the adoption of driverless tractors, as outlined in Table 6. In general, responses exhibited a common trend across regions, except for increased concerns regarding field obstacles and inter-field transportation in the Southeast and Midsouth. This disparity is likely influenced by the increased presence of water features and topographical variations, which may pose challenges to field operations compared to the terrains of the Southwest and Far West. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7310 However, regardless of geographical location, approximately 80% of respondents highlighted costs as the primary barrier to integrating driverless tractors into their farms. Furthermore, among the practices where respondents favored utilizing this technology, planting (40%), spray applications (40%), harvest (35%), and pre-plant weed control (35%) emerged as the most preferred high-priority activities. Table 6. Impediments to Using Driverless Tractors on Farms by 2023 Survey Respondents (Refer to Q21 in Appendix 1) Impediments to using driverless tractors Region Southeast Midsouth Southwest Far West U.S. Costs 80% 80% 76% 80% 78% Risk of accidents resulting in litigation 61% 60% 60% 68% 61% Too many obstacles in field 62% 63% 59% 48% 60% Field-to-field transportation 63% 64% 54% 52% 59% Dependability 52% 45% 52% 44% 50% Skilled labor to supervise 44% 45% 42% 36% 43% No Impediments 5% 5% 6% 4% 6% Other 4% 4% 2% 8% 3% Pesticide Management Cotton growers are embracing new technologies to enhance the precision of their pesticide applications, as previously mentioned regarding the use of swath and other spray technologies. Some of these technologies (like Weed-IT, Weed seeker, John Deere See and Spray) may see increased adoption in the future. Ground rigs remain the predominant method for pesticide applications, with 85% of respondents opting for this approach, mirroring trends observed in 2008 and 2015 (For the 2023 Survey, refer to ST 7, Appendix 2). Additionally, 66% of respondents indicated their reliance on professional consultants to advise on foliar insecticide treatments, marking a slight decline from the 71% reported in 2015. Notably, less than 8% of respondents reported using a calendar-based spray schedule, consistent with the 6% figure recorded in 2015. Also, 37% of respondents reported fields that did not receive foliar insecticides during the season, compared to 33% in 2015 and 29% in 2008. Additionally, an estimated 16% of reported cotton acres went untreated with insecticide, a decrease from 21% in 2015 (For the 2023 Survey, refer to ST 8, Appendix 2). The distribution of target pests has shown a consistent pattern from 2015 to 2023 (Fig. 31). According to respondents’ percentages, there were slight increases in the populations of aphids (+4%), cotton flea hoppers (+10%), and grasshoppers (+8%). Notably, the top three targeted insects reported by respondents have remained unchanged since 2008. Thrips have seen a significant increase of 34%, stink bugs increased by 15%, and aphids by 19% over this period. The trend indicates a persistent focus on these three pests among survey participants; however, it’s important to take regional variations. For instance, stink bugs and plant bugs are predominantly found in the Southeast (87%, 62%) and Midsouth (50%, 86%), whereas their prevalence in the Southwest and Far West is less than 30%. Conversely, cotton fleahoppers are most prevalent in the Southwest (59%), PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7311 while their occurrence in other regions ranges from 4% to 12% (Refer to ST 9, Appendix 2). The primary target pathogens are boll rots in the Southeast (61%) and Midsouth (58%), and verticillium wilt in the Southwest (40%) and Farwest (68%). For a more detailed regional breakdown, refer to ST 10, Appendix 2. (A) (B) Fig. 31. Target pests across U.S. cotton production among respondents (A) in 2008, 2015 and 2023 and (B) through regions PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7312 Integrated pest management (IPM) strategies play a critical role in addressing challenges posed by resilient pests like thrips, emphasizing the importance of a multifaceted approach. For instance, conservation and reduced tillage methods, particularly when integrated with high-residue cover crops, exhibit significant potential in mitigating thrips populations on cotton seedlings by up to 50% (Virginia Cooperative Extension). Cotton growers reported an increased concern regarding herbicide-resistant weeds, as evidenced by the fact that 95% of them expressed worry about the costs associated with herbicides. Moreover, only 1% of growers opt not to cultivate herbicide-tolerant cotton varieties. The major concern about weed resistance to herbicides, indicated by 65% of respondents, is reflected in various practices: - 71% checked for weed escapes (76% in 2008, 72% in 2015). - 81% used a pre-emergent herbicide (70% in 2008, 82% in 2015). - 79% alternated herbicide modes of action (62% in 2008, 79% in 2015). - 49% reported hand hoeing (not asked in 2008, 66% in 2015). - 55% planted cover crops, a significant increase from 33% in 2015. To conveniently observe the main trends and their changes from 2015 to 2023, the data were scaled to 100%, as shown in Fig. 32. Fig. 32. Adopting herbicide control practices among cotton producers over time. The data for both survey years was adjusted to a 100% scale (For the 2023 Survey, refer to Q12 in Appendix 1). When analyzing herbicide control practices across regions, a consistent trend emerges across the majority of practices, except for tilling and cultivating weeds that have escaped herbicide control. In this regard, the Southwest (60%) and Far West (69%) regions exhibit a notably higher preference compared to the Southeast (15%) and Midsouth (24%), as illustrated in Table 7. In general, over 70% of respondents decided to apply foliar herbicide after scouting their crop, while only 14% set a calendar spray schedule. Additionally, 10% of respondents reported that their fields don't require a foliar herbicide, representing 3% of all reported cotton acreage (Refer to ST 7, Appendix 2). Conservation Practices and Natural Habitat Management Conservation practices are pivotal in mitigating the environmental footprint of cotton cultivation and safeguarding the ecosystem, which is essential for the sustained production of cotton. To grasp the extent of the adoption of these practices, the survey asked growers about the conservation methods employed on their farms. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7313 Table 7. Herbicide Control Practices by Regions in the 2023 Survey (Refer to Q12 in Appendix 1) Practices to manage Roundup Ready, Liberty Link, and other herbicide-tolerant cotton varieties % of Respondents by Region Southeast Midsouth Southwest Far West U.S. Using pre-emerged herbicide 78.7% 80.2% 83.9% 69.2% 80.9% Using herbicides with different modes of action 82.8% 69.8% 79.6% 76.9% 79.1% Checking fields for weeds that escaped herbicide control 77.6% 65.1% 69.2% 38.5% 70.9% Planting cover crops to reduce weed pressure 60.8% 48.7% 53.6% 44.4% 55.1% Handing hoe weeds that escaped control 52.1% 46.5% 48.8% 38.5% 49.4% Tilling and cultivating weeds that escaped herbicide control 14.6% 24.4% 55.9% 69.2% 35.1% Not growing herbicide tolerant cotton varieties 0.0% 1.2% 1.9% 0.0% 1.0% Other 0.5% 0.0% 1.4% 0.0% 0.8% Table 8. Percent of Respondents Using Listed Conservation Practices by Regions through 2015 and 2023 (For the 2023 Survey, refer to Q55 in Appendix 1) Conservation Practices 2015 2023 SE MS SW FW U.S. SE MS SW FW U.S. Conservation cover 26.4% 14.6% 18.1% 6.1% 20.7% 46.4% 25.3% 42.7% 15.4% 40.4% Field borders 31.0% 29.7% 16.3% 36.4% 26.5% 32.3% 27.9% 14.7% 53.9% 24.7% Grass waterway 25.5% 15.1% 16.3% 0.0% 19.6% 29.2% 20.9% 10.0% 0.0% 18.9% Recycle farm plastic/paper 9.1% 32.7% 6.1% 15.2% 13.5% 4.7% 23.3% 6.2% 7.7% 8.6% Efforts to improve wildlife habitat N/A 8.9% 10.5% 6.2% 7.7% 8.0% Vegetative border 16.6% 15.6% 10.8% 3.0% 14.2% 10.9% 15.1% 2.4% 0.0% 7.8% Precision leveled 0.2% 26.1% 8.3% 54.6% 10.2% 2.1% 22.1% 5.2% 23.1% 7.4% Drop pipes for erosion control 4.1% 26.6% 6.5% 0.0% 9.5% 5.2% 16.3% 3.3% 0.0% 6.2% Livestock integration N/A 2.6% 2.3% 10.0% 23.1% 6.2% Contour strip cropping 7.0% 2.5% 5.4% 0.0% 5.3% 4.2% 0.0% 8.5% 0.0% 5.2% Leave riparian N/A 6.8% 8.1% 1.4% 0.0% 4.6% Field strip cropping 9.4% 1.0% 4.3% 0.0% 5.7% 5.2% 0.0% 3.3% 0.0% 3.4% Riparian forest buffer 7.0% 2.5% 1.4% 0.0% 4.1% 4.7% 7.0% 1.0% 0.0% 3.4% Water and sediment control basin 2.2% 11.6% 11.8% 0.0% 4.0% 1.6% 9.3% 1.4% 0.0% 2.8% Filter strip 5.3% 3.5% 0.7% 3.0% 3.5% 2.1% 5.8% 1.0% 0.0% 2.2% Riparian herbaceous cover 0.7% 1.5% 0.4% 0.0% 0.8% 1.6% 4.7% 1.0% 0.0% 1.8% Contour buffer strip 3.1% 1.5% 2.2% 0.0% 2.4% 1.6% 4.7% 0.5% 0.0% 1.6% Tailwater recovery system 0.2% 1.5% 1.4% 24.2% 1.7% 0.5% 2.3% 1.4% 15.4% 1.6% Sediment basin 0.5% 8.0% 1.4% 0.0% 2.4% 1.0% 5.8% 0.0% 0.0% 1.4% Stream habitat improvement 1.2% 1.0% 0.4% 0.0% 0.8% 0.0% 2.3% 0.0% 0.0% 0.4% None of the above 28.4% 20.1% 44.8% 15.2% 31.0% 16.2% 18.6% 28.4% 23.1% 21.9% PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7314 Out of the practices listed in Table 8, about 78% of growers indicated using at least one (compared to 69% in 2015). The preferred practices included adopting conservation cover crops (+21% from 2015), establishing field borders (-1% from 2015), and implementing grass waterways (-1% from 2015). In terms of efforts made on farms to enhance wildlife habitat, 47% (+6% from 2015) of respondents reported maintaining field borders conducive to wildlife habitat. Overall, 76% of respondents indicated their efforts to improve wildlife habitat, reflecting an increase of 8% from 2015. When considering barriers to enhancing wildlife habitat, 37% of respondents cited a lack of funding, while 26% highlighted increased pest pressure from conservation areas. Interestingly, nearly 29% indicated they didn’t perceive any significant barriers. Furthermore, there has been an increase in participation in wildlife conservation programs. For instance, 33% joined conservation reserve programs, up from 22% in 2015. Similarly, participation in wildlife habitat incentive programs increased to 19%, compared to 8% in 2015. Evidence concerning wildlife habitat improvement practices is presented in Table 9, derived from survey questions. Table 9. Percent of Respondents Adopting Practices on Wildlife Habitat Improvement in the 2023 Survey Year (Refer to Q24 and Q25 in Appendix 1) Efforts to enhance wildlife habitat % of Respondents by Region Southeast Midsouth Southwest Far West U.S. Some portion of the farm is left unharvested for wildlife feed 33.8% 38.3% 28.4% 33.3% 32.3% Field borders are conducive to wildlife habitat 52.4% 52.3% 40.9% 44.4% 47.4% Manage some field areas during the winter to provide wildlife habitat 28.1% 33.7% 22.3% 7.7% 26.1% Forested areas are preserved 50.0% 39.5% 12.8% 0.0% 31.3% Conservation Reserve Program 27.6% 36.9% 37.6% 27.8% 33.5% Wildlife Habitat Incentive Program 19.8% 22.5% 17.9% 11.1% 19.2% Wetlands Reserve Program 7.3% 16.3% 3.3% 0.0% 7.0% No efforts 16.7% 16.3% 33.7% 46.2% 24.5% Barriers to enhance wildlife habitat Southeast Midsouth Southwest Far West U.S. Lack of funding to incentivize wildlife enhancement practices 42.2% 37.2% 33.0% 40.0% 37.3% Lack of precision agriculture data to support the decision 5.8% 10.1% 10.8% 4.0% 8.6% Increased pest pressure from conservation areas 26.2% 32.6% 23.8% 24.0% 26.2% Lack of guidance on how to enroll in a program that supports wildlife habitat enhancement 19.3% 17.1% 17.9% 24.0% 18.5% Not interested in enhancing wildlife habitat 18.6% 11.6% 16.7% 16.0% 16.5% No barriers 23.3% 31.0% 32.7% 24.0% 28.7% PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7315 Yield and Other Specific Data In the 2021/2022 growing season, the average U.S. cotton yield covering all 4 regions, based on USDA data, was approximately 1038 pounds per acre, nearly aligning with the surveyed average of 1073 pounds per acre. When compared to the average yields from the previous surveys, the average didn’t change much (a 3% increase from 2008 and a 1% decrease from 2015). Numerous factors, including precipitation and climate conditions, impact average yields, making it challenging to pinpoint the causes of year-to- year fluctuations. Notably, the limited number of respondents from the Far West region could be a contributing factor in an observed decrease in average field yield with 1625 lbs/acre in 2008 to 1215 lbs/acre in 2023, representing a 25% decrease (Fig. 33). Fig. 33. Average yield difference by 2008, 2015, and 2023 survey respondents (For the 2023 Survey, refer to Q38 in Appendix 1) On average, farmers spent between $80 and $120 per acre on cotton harvesting, with distinct regional variations (Fig. 34). One factor impacting harvest costs by region is yield, where regions with higher yields will have higher costs for packaging and generally harvest at a slower rate. The Far West region reported the highest costs, exceeding $150 on average (reported by 40% of respondents) due to higher fuel and labor costs than the other regions coupled with high yields, while the Southwest region recorded comparatively lower expenses, ranging from $50 to $100 on average (Table 10). The lower cotton harvesting costs in the Southwest can be explained by the types of harvesting machines used, specifically pickers versus strippers. Historically, most of the cotton grown on the in the Southwest region has been harvested using strippers (Faulkner et al. 2008). The operational and other associated costs of using strippers usually are lower compared to pickers, which likely accounts for the reduced harvesting costs in this region (Yates et al. 2007). Since the harvesting cost typically includes expenses such as transporting cotton from the field to the gin, among others, the distance to the gin may affect the overall expenses for growers. However, according to the surveyed data, the distance between the PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7316 fields and gins has increased in all regions, except for the Southeast. This change is likely attributed to the improved cost-effectiveness of transporting larger cylindrical modules over longer distances and some consolidation of gins over the past decade. Fig. 34. Average cost to harvest cotton among 2023 survey respondents (Refer to Q20 in Appendix 1). Table 10. Regional Averages for Yield and Harvesting Cost, and Distance from Farm to Gin: 2023 Survey Data with Gin Comparison to 2015 Region Yield (lbs/acre) Harvesting Cost ($) Tillage Passes (Avrg) Distance from Farm to Gin in 2023 (miles) Distance from Farm to Gin in 2015 (miles) Southeast 1087 $80-$100 1.3 23 23 Midsouth 1149 $120-$150 1.5 24 15 Southwest 1015 $50-$80 1.9 18 15 Far West 1215 >$150 2 20 12 U.S. 1073 $80-$100 1.6 21 18 CONCLUSIONS 1. The 2023 survey provided a comprehensive dataset of U.S. cotton growers, offering valuable insights into demographics, practices, and challenges regionally and nationwide. 2. Utilizing the 2023 survey results can inform current agricultural systems, track the impact of outreach and technology adoption, and guide decisions for more profitable and sustainable cotton production. 3. Grower concerns over extreme weather events indicate the increasing impact of climate change on cotton production challenges and the need to increase cotton’s climate resilience. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7317 4. While face-to-face interactions remain common and most useful, cotton growers are increasingly turning to digital tools like apps and social media to disseminate information. 5. From 2008 to 2023, a notable shift in tillage practices towards no-till/strip-till methods suggests potential cost savings and reduced energy requirements. 6. A consistent trend is observed among producers using irrigation, with a shift away from surface irrigation methods, such as furrow systems, towards pressurized systems like pivot/sprinkler systems, indicating increased water use efficiencies attributed to enhanced precision and operational control. 7. Autosteer/GPS technology has seen a significant increase in adoption rates, becoming a standard feature on new equipment, driven by simplified setup processes and potential cost savings from reduced skips and overlaps in input costs. 8. The increasing adoption of conservation practices, particularly increased adoption of winter cover crops among U.S. cotton growers highlights their dedication to continual improvement, climate resiliency, and creating positive environmental outcomes. ACKNOWLEDGMENTS The completion of this work was made possible by the funding provided by Cotton Incorporated and the invaluable contributions of cotton farmers who participated in the natural resource survey. REFERENCES CITED Barnes, E. M., Campbell, B. T., Vellidis, G., Porter, W. M., Payero, J. O., Leib, B. G., Sui, R., Fisher, D. K., Anapalli, S., Colaizzi, P. D., Bordovsky, J. P., Porter, D. O., Ale, S., Mahan, J., Taghvaeian, S., and Thorp, K. R. (2020). “Forty years of increasing cotton’s water productivity and why the trend will continue,” Applied Computational Electromagnetics Society Journal 36(4), 457-478. DOI: 10.13031/aea.13911 Cotton Incorporated. (2016). Life Cycle Assessment. CottonToday. Biodiversity and Wildlife Habitat. https://cottontoday.cottoninc.com/our- sustainability-story/land/habitat-preservation/ Daystar, J. S., Barnes, E., Hake, K., and Kurtz, R. (2017). “Sustainability trends and natural resource use in U.S. cotton production,” BioResources 12(1) 362-392. DOI: 10.15376/biores.12.1.362-392 Fannin, B. (2017). “Texas agricultural losses from Hurricane Harvey estimated at more than $200 million,” (https://agrilifetoday.tamu.edu/2017/10/27/texas-agricultural- losses-from-hurricane-harvey-estimated-at-more-than-200-million/), Accessed June 26, 2024. Faulkner, W. B., Wanjura, J. D., Shaw, B. W., and Hequet, E. F. (2008). “Effect of harvesting methods on fiber and yarn quality from irrigated cotton on the High Plains,” 2009 Beltwide Cotton Conferences, San Antonio, TX, USA, pp. 449-461. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7318 Field to Market. (2021). Environmental Outcomes from On-Farm Agricultural Production in the United States (Fourth Edition). ISBN: 978-0-578-33372-4 Foro Económico Mundial., Marsh and McLennan., SK Group., and Zurich Insurance Group. (2022). The Global Risks Report 2022. World Economic Forum. Frame, W. H., Herbert, D. A., Mehl, H., Cahoon, C., Reiter, M., and Flessner, M. (2016). Virginia Cotton Production Guide (https://www.sites.ext.vt.edu/newsletter- archive/cotton-production-guide/2016.pdf), Virginia Cooperative Extension, Virginia Tech, Blacksburg, VA, USA. Geisseler, D., and Horwath, W. R. (2016). Economically Optimal Nitrogen Availability for Cotton, (https://apps1.cdfa.ca.gov/FertilizerResearch/docs/Cotton_EONR.pdf), UC Davis, CA, USA. Grainger, C., Williams, R., Clarke, T., Wright, A. D. G., and Eckard, R. J. (2010). “Supplementation with whole cottonseed causes long-term reduction of methane emissions from lactating dairy cows offered a forage and cereal grain diet,” Journal of Dairy Science 93(6), 2612–2619. DOI: 10.3168/jds.2009-2888 ICAC. (2022). ICAC Cotton Data Book, Technical Information Section of the International Cotton Advisory Committee, Washington DC. Kansas AGGROWTH. (2021). LifestyleMonitor. (2023). Sustainability in Consumers’ Lives and Wardrobes . McFadden, J., Njuki, E., and Griffin, T. (2023). Precision Agriculture in the Digital Era: Recent Adoption on U.S. Farms,” Economic Information Bulletin No. (EIB-248) 52 pp, https://www.ers.usda.gov/publications/pub-details/?pubid=105893. Meyer, L., Dew, T., Grace, M., Lanclos, K., MacDonald, S., and Soley, G. (2023). Cotton Outlook THE WORLD AND UNITED STATES COTTON OUTLOOK. https://www.usda.gov/oce/ag-outlook-forum/commodity-outlooks Miller, D. A., and White, R. A. (1998). Soil Composition Across the U.S., NASA Earth Observatory. Mississippi State University Extension. (2017). Inorganic Nutrient Management for Cotton Production in Mississippi, Publication Number: P1622. Mississippi State University. (2022). Cotton Crop Losses. https://www.biochemistry.msstate.edu/resources/cottoncrop.php Prakash, S., Radha, Sharma, K., Dhumal, S., Senapathy, M., Deshmukh, V. P., Kumar, S., Madhu, Anitha, T., Balamurugan, V., Pandiselvam, R., and Kumar, M. (2024). “Unlocking the potential of cotton stalk as a renewable source of cellulose: A review on advancements and emerging applications,” International Journal of Biological Macromolecules 261, article 129456. DOI: 10.1016/J.IJBIOMAC.2024.129456 PRISM Climate Group. (2020). Prism Climate Data, Oregon State University. Soil Health Institute. (2023). Economics of Soil Health Management Systems on Eight Cotton Farms in the Texas Southern Great Plains, (https://soilhealthinstitute.org/economics/). University of Arkansas System. (2016). Summaries of Arkansas Cotton Research, (https://arkansasagnews.uark.edu/1356.htm). University of Missouri. Cotton Extension. USDA (2022). “Cotton sector at a glance,” (https://www.ers.usda.gov/topics/crops/cotton-and-wool/cotton-sector-at-a-glance/), Accessed June 26, 2024. USDA NASS. (2021). Agricultural Prices. PEER-REVIEWED ARTICLE bioresources.cnr.ncsu.edu Bayramova et al. (2024). “Cotton farming trends,” BioResources 19(4), 7279-7319. 7319 USDA Natural Resources Conservation Service. (1998). Dominant Soil Orders for STATSGO Mapunits . USDA Quick Stats. (2022). USDA NASS. USDA Quick Stats. (2024). USDA NASS. https://quickstats.nass.usda.gov/results/A775E607-A201-33CA-AF2C- 1DE7C7473328 USDA. (2022). Conservation Practices on Cultivated Cropland: A Comparison of CEAP I and CEAP II Survey Data and Modeling - Summary of Findings. Virginia Cooperative Extension. Managing Thrips in Cotton. Wallander, S., Smith, D., Bowman, M., and Claassen, R. (2021). Cover Crop Trends, Programs, and Practices in the United States, (www.ers.usda.gov). Wyatt, B. M., Arnall, D. B., and Ochsner, T. E. (2019). Nutrient Loss and Water Quality, (https://extension.okstate.edu/fact-sheets/print-publications/pss/nutrient-loss-and- water-quality-pss-2286.pdf), Oklahoma Cooperative Extension Service, Oklahoma State University, Stillwater, OK, USA. Yates, J., Gueck, N., Boman, R., Kelley, M., Brown, M., and Klose, S. (2007). Comparison of Costs and Returns for Alternative Cotton Harvest Methods in the Texas High Plains, (https://farmassistance.tamu.edu/files/2013/08/2008-2.pdf), Texas AgriLife Extension Service, Texas A&M University System. Article submitted: June 20, 2024; Peer review completed: July 31, 2024; Revised version received: August 2, 2024; Accepted: August 8, 2024; Published: August 19, 2024. DOI: 10.15376/biores.19.4.7279-7319 COTTON GROWERS NATURAL RESOURCE SURVEY 1 INTRODUCTION DISPLAYONLY Welcome to the Natural Resources Survey. Your feedback is very important to us! The following survey by Cotton Incorporated is critical to shaping our research program and telling your sustainability story. Only aggregated data from this survey will be used and no individual grower data will be shared. This reoccurring survey helps to shape research direction and to complete cotton life cycle assessments. A similar version of this survey was previously administered in 2008 and 2014. Having a representative dataset of U.S. cotton production is critical to help tell our sustainability story and document continuous improvement in the industry. Please note that to keep this survey completely anonymous, it is not possible to save responses to an incomplete session. Therefore, please be sure that you have at least 25 -35 minutes to devote this survey once you begin. The session will time out if you close your browser, so only close the browser when the survey is complete. Also, please note that once an answer is entered and the next button is pressed, answers cannot be changed. Therefore, be sure of your answers before moving on to the next screen. The first 1000 respondents who grew cotton in 2021 and fully complete the survey will receive a Cotton branded 30 oz. Yeti Rambler as a token of appreciation for your time and participation. A link is provided at the end of the survey to provide your shipping information to receive your Cotton Yeti Rambler. We thank you for your time and participation. Link to legal information SCREENER S1 RADIOBUTTON TERM IF S1=2 Did you grow cotton in 2021? Select one. 1 Yes 2 No S2 RADIOBUTTON If you were a member of the U.S. Cotton Trust Protocol in 2022 and would like to give the Trust Protocol permission to share an anonymized copy of your self-assessment questionnaire results and anonymized Fieldprint Calculator data with Cotton Incorporated to conduct an aggregated U.S.-focused cotton production life cycle assessment, please indicate so below. The Trust Protocol will not release your anonymized information – self-assessment questionnaire or Fieldprint Calculator data – without your express consent. To anonymize the data, all personally identifiable information will be removed from the data prior to sharing it with Cotton Incorporated. Sharing data here will save you time in completing the survey. Select one. Selecting yes will serve as your consent to share your anonymized self-assessment questionnaire results and anonymized Fieldprint Calculator data from the Trust Protocol with Cotton Incorporated. 1 Yes 2 No / I was not a U.S. Cotton Trust Protocol Member in 2022 S3 SLINETEXT CASE: ASK IF S2=1 REQUIRE RESPONSE TO HAVE @ CHARACTER ERROR MESSAGE “Please provide a valid email address” If you agree to sharing your aggregated and anonymized self-assessment questionnaire or APPENDIX 1 COTTON GROWERS NATURAL RESOURCE SURVEY 2 aggregated and anonymized Fieldprint Calculator information from the U.S. Cotton Trust Protocol, please provide the email used in your 2022 U.S. Cotton Trust Protocol enrollment. ON MOBILE, HIDE KEYPAD FOR INTEGER QUESTIONS QUESTIONNAIRE Q1 INTEGER_STACKED MIN = 0 MAX = 9999 RANDOMIZE STUBS How many acres did your farming business cover in 2021? Please enter the appropriate crop acreage. Enter a number ROWS 1 Non-irrigated cotton 2 Irrigated cotton 3 Crops other than cotton 4 Non-cropped natural land (this is land not in active farmland and pasture, roads, or buildings. This will include CRP, fallow, forestry, field borders, filter strips, and grass waterways.) INSERT PUNCH: Q1_COTTON_TOTAL=Q1_1 Q1_2 Q2 SLIDER VALUES 0-100 IN INTERVALS OF 5 PLACE A “% owned” label to the right of the number box LABEL 0 AS “All leased” and 100 AS “All owned” underneath the slider What percent of your total farm acreage is owned versus leased? Drag the slider to a point on the scale to indicate your farm ownership. Q3 CHECKBOX In addition to cotton, did you grow any of the following crops or raise livestock commercially in 2021 or 2022? Select all that apply 1 Alfalfa 2 Corn 3 Cotton STUBCASE: DO NOT SHOW, AUTOPUNCH Y IF S1=1 4 Hay 5 Pasture 6 Peanuts 7 Rice 8 Sorghum 9 Soybeans 10 Orchards 11 Vegetables 12 Vines 13 Wheat 17 Cattle 18 Dairy 19 Poultry 20 Swine 14 Natural Vegetation – This land is not in active farmland and pasture. This will include conservation reserve program, fallow, forestry, field borders, and filter strips. COTTON GROWERS NATURAL RESOURCE SURVEY 3 97 Other, specify ANNOTATE, FIXED 98 None of the above EXCLUSIVE, FIXED Q4 CHECKBOX RANDOMIZE STUBS Do you have any of the following renewable energy sources on your farming operation? Select all that apply 1 Wind 2 Solar 97 Other (please describe): ANNOTATE, FIXED 98 Do not have renewable energy sources EXCLUSIVE, FIXED Q5 CHECKBOX RANDOMIZE STUBS What management practices are used to handle tailwater or surface run-off? Select all that apply 1 I have a holding pond to capture run-off. 2 I have an irrigation tailwater return system in place. 3 My field and distribution system are designed and operated to minimize run-off (field slope, length, and flow rate designed to minimize runoff). 4 Tailwater run-off is routed to other fields. 5 Surge system is used to get even distribution across the field. 97 Other method (please describe): ANNOTATE, FIXED Q6 RADIOBUTTON Do you use a flow meter or other device to manage irrigation water volume? Select one 1 Yes 2 No 3 Not Applicable Q7 RADIOBUTTON Do you have wells on your farm where water salinity is a concern? Select one 1 Yes 2 No 3 Not Applicable Q8 CHECKBOX RANDOMIZE STUBS What practices are used to minimize soil erosion on your farm? Select all that apply 1 I maintain ground cover and surface residue. 2 I manage irrigation to minimize runoff. 3 I use strip till or no till planting practices. 4 I use contour terraces or plant rows along the field contour. 5 I use grassed water ways, buffer strips, or silt traps. 6 I precisely (e.g., laser) level fields. 7 I design drains to minimize water velocities. 8 I plant cover crops. 9 I plant wheat or other vegetation to serve as a wind break. 10 I use sand-fighters to minimize wind erosion. 97 Other (please describe): ANNOTATE, FIXED COTTON GROWERS NATURAL RESOURCE SURVEY 4 12 I do not use any of the practices listed above because erosion is not a problem on my farm. EXCLUSIVE, FIXED Q9 RADIOBUTTON CASE: ASK IF S2=2 How often do you conduct soil fertility tests on your cotton fields? Select one 1 Never 2 Once or more a year 3 Once every 2 years 4 Once every 3 years 5 Once every 4 or more years Q10 CHECKBOX CASE: ASK IF S2=2 RANDOMIZE STUBS Please identify the factors that you use in determining your fertilizer rate. Select all that apply 1 Fertilizer costs 2 Soil test recommendations (including state recommendation) 3 Consultant recommendations 4 Yield goal expectations 5 More efficient application techniques such as sub-soil injection of nitrogen 6 Use of spatial technology such as soil and yield maps 7 Petiole or leaf testing 8 Past experience 97 Other (please describe): ANNOTATE, FIXED Q11 CONSTANT_SUM_GRID DOES NOT HAVE TO SUM TO 100 MAX SUM PER STUB=100 Q10_3. Please identify the factors that you use in determining your fertilizer rate. Select all that apply. ... Consultant recommendations PLACE “%” TO THE RIGHT OF EACH STUBS NUMBER BOX Please indicate the percent of your total crop acreage for which the following methods are used. Leave blank or enter a zero beside the method(s) below that you do not use. RANDOMIZEROWS 1 Applied composted materials such as gin trash or cotton compost. 2 Applied animal manure such as chicken or cow manure. 3 Planted legume cover crops such as vetch, clover, or lupine. 4 Planted a multispecies cover crop (more than one plant species). 5 Planted grass, cereal, or grain cover crops such as wheat, rye, barley, or oats. 6 Other source of organic matter, please specify: ANNOTATE, FIXED Q12 CHECKBOX CASE: ASK IF S2=2 RANDOMIZE STUBS What are you doing to manage Roundup Ready, Liberty Link, and other herbicide tolerant cotton varieties on your farm? Select all that apply 1 I check my fields for weeds that have escaped herbicide control. 2 I use pre-emergent herbicides. COTTON GROWERS NATURAL RESOURCE SURVEY 5 3 I use herbicides which have different modes of action. 4 I plant cover crops to reduce weed pressure. 5 I till and cultivate weeds that have escaped herbicide control. 6 I hand hoe weeds that have escaped control. 7 I do not grow herbicide tolerant cotton varieties. EXCLUSIVE, FIXED 97 Other, specify ANNOTATE, FIXED Q13 CHECKBOX CASE: ASK IF S2=2 How do you decide you need to apply a foliar insecticide to cotton fields? Select all that apply RANDOMIZE STUBS 1-3 1 I decide after scouting my crop. 2 My scout or consultant makes recommendations. 3 I have a set program or calendar spray schedule. 4 Where possible I treat only parts of a field – edges/hotspots. 98 None of the above EXCLUSIVE, FIXED Q14 RADIOBUTTON CASE: ASK IF S2=2 Were there any cotton fields that did NOT require foliar insecticides in the most recent year you grew cotton? Select one 1 Yes 2 No Q15 INTEGER CASE: ASK IF S2 =2 AND Q14=1 MIN = 1 MAX <= Q1_COTTON_TOTAL ADD “(In other words, no more than the total acreage of cotton fields you reported growing)” TO THE ERROR STATEMENT Approximately how many cotton acres did NOT require foliar insecticides in the most recent year you grew cotton? Enter a number Q13a CHECKBOX CASE: ASK IF S2=2 RANDOMIZE STUBS How do you decide you need to apply a foliar herbicide to cotton fields? Select all that apply 1 I decide after scouting my crop. 2 My scout or consultant makes recommendations. 3 I have a set program or calendar spray schedule. 4 Where possible I treat only parts of a field – edges/hotspots. 98 None of the above EXCLUSIVE, FIXED Q14a RADIOBUTTON CASE: ASK IF S2=2 Were there any cotton fields that did NOT require foliar herbicides in the most recent year you grew cotton? Select one 1 Yes COTTON GROWERS NATURAL RESOURCE SURVEY 6 2 No Q15a INTEGER CASE: ASK IF Q14a=1 MIN = 0 MAX <= Q1_COTTON_TOTAL ADD “(In other words, no more than the total acreage of cotton fields you reported growing)” TO THE ERROR STATEMENT Approximately how many cotton acres did NOT require foliar herbicides in the most recent year you grew cotton? Enter a number Q16 CHECKBOX CASE: ASK IF S2=2 RANDOMIZE STUBS How do you decide you need to apply a foliar fungicide? Select all that apply 1 I decide after scouting my crop. 2 My scout or consultant makes recommendations. 3 I have a set program or calendar spray schedule. 4 Based on cultivar selected 98 None of the above EXCLUSIVE, FIXED Q17 RADIOBUTTON CASE: ASK IF S2=2 Were there any cotton fields that did NOT require foliar fungicides in the most recent year you grew cotton? Select one 1 Yes 2 No Q18 INTEGER CASE: ASK IF Q17=1 MIN = 1 MAX <= Q1_COTTON_TOTAL ADD “(In other words, no more than the total acreage of cotton fields you reported growing)” TO THE ERROR STATEMENT Approximately how many cotton acres did NOT require foliar fungicides in the most recent year you grew cotton? Enter a number Q19 CHECKBOX RANDOMIZE STUBS Which of the following precision agriculture technologies do you use in your cotton operation? Select all that apply 1 I use a cotton yield monitor to identify yield variability. 9 See and spray system (e.g., Weed-IT, Weed seeker, John Deere see and spray…) 10 Swath control on spray boom 11 Swath control on planter 2 I use an auto steer/guidance system. 3 I use a handheld GPS unit or smartphone to pinpoint field areas requiring special attention. 4 I make use of aerial or satellite images to identify areas needing insecticide, fertilizer or other treatments. COTTON GROWERS NATURAL RESOURCE SURVEY 7 5 I use a soil map for management decisions. 6 I use grid or zone soil sampling. 12 Unpiloted Aerial Vehicles (UAVS) 97 Other (please describe): ANNOTATE, FIXED 98 None of the above EXCLUSIVE, FIXED Q20 RADIOBUTTON What is your average cost to harvest cotton (including defoliation) per acre? Select one 1 Less than $50 per acre 2 $51 to $75 per acre 3 $76 to $100 per acre 4 $101 to $125 per acre 5 $126 to $150 per acre 6 Greater than $150 per acre 99 Don't know Q21 CHECKBOX RANDOMIZE STUBS What impediments do you see to using driverless tractors on your farm? Select all that apply 1 Dependability 2 Skilled labor to supervise 3 Too many obstacles in field 4 Costs 5 Risk of accidents resulting in litigation 6 Field to field transportation 7 Other (please describe): ANNOTATE, FIXED 8 No impediments EXCLUSIVE, FIXED Q22 CHECKBOX RANDOMIZE STUBS What benefits do you see to driverless tractors on your farm? Select all that apply 1 Labor savings 2 Improved efficiency 3 Decrease worker exposure 4 Other (please describe) ANNOTATE, FIXED 5 No benefits EXCLUSIVE, FIXED Q23 RATING_GRID RANDOMIZE ROWS REPEAT HEADERS EVERY 5 ROWS Please rate the following operations as priorities for automation: Please select rating for each operation. COLUMNS A High priority B Medium priority C Low priority D Does not need to be automated ROWS COTTON GROWERS NATURAL RESOURCE SURVEY 8 1 Tillage (including strip till) 2 Pre-plant weed control 3 Planting 4 Cultivation (including sand fighting) 5 In-season weed control 6 Spray applications (all products such as insecticides, PGRs...) 7 Field scouting 8 Staging modules in the field 9 Harvest 10 Ginning 11 Warehouse bale logistics Q24 CHECKBOX CASE: ASK IF S2=2 RANDOMIZE STUBS What efforts are being made on the farm to enhance wildlife habitat? Select all that apply 1 Some portion of the farm is left unharvested for wildlife feed 2 Field borders are conducive to wildlife habitat 3 Manage some field area during the winter to provide wildlife habitat 4 Forested areas are preserved 5 Conservation Reserve Program 6 Wildlife Habitat Incentive Program 7 Wetlands Reserve Program 8 Other (please describe): ANNOTATE, FIXED 9 No special efforts EXCLUSIVE, FIXED Q25 CHECKBOX RANDOMIZE STUBS What are the barriers, if any, to enhancing wildlife habitat on your farm? Select all that apply 2 Lack of funding to incentivize the wildlife enhancement practices 3 Lack of precision agriculture data to support the decision 4 Increased pest pressure from conservation areas 5 Lack of guidance on how to enroll in a program that supports wildlife habitat enhancement 6 Lack of interest/ I am not interested in enhancing wildlife habitat 97 Other (please describe) ANNOTATE, FIXED 98 No barriers FIXED, EXCLUSIVE Q26 RATING_GRID RANDOMIZE ROWS REPEAT HEADERS EVERY 5 ROWS How would you rate the following cotton production concerns or challenges on your farm? Please select a rating for each concern or challenge. COLUMNS 1 Not an issue 2 Moderate issue 3 Major issue ROWS COTTON GROWERS NATURAL RESOURCE SURVEY 9 1 Water quality protection from agricultural runoff 2 Adequate water supply 3 Water salinity of irrigation wells 4 Soil salinity 5 Herbicide drift 29 Insecticide drift 6 Efficient use of fertilizer 7 Weed resistance to herbicides 8 Insect resistance to insecticides and Bt cotton 9 Soil erosion 10 Soil compaction 11 Dust from harvesting, farming, gins 12 Effects of agriculture on wildlife 13 Spread of plant diseases and weeds 14 Increased frequency of drought and extreme weather events 15 Consumer attitudes about agriculture’s impact on the environment 16 Cotton production input costs 17 Variety selection 18 Cotton’s tolerance to heat and drought 19 Weed control 20 Seedling vigor, seed quality, and stand establishment 21 Cottonseed value 22 Lack of new crop protection products (insecticides, herbicides, etc.) 23 Plant bug control 24 Soil sampling and analysis for fertilization 25 Harvest aid materials and application timing 26 Stinkbug control 27 Monitoring cotton’s plant growth 28 Disease concerns related to nematodes, target spot, fusarium wilt, virus or seedling diseases, or another disease not listed Q27 RATING_GRID RANDOMIZE ROWS REPEAT HEADERS EVERY 5 ROWS Are the following production cost concerns a major concern, a minor concern, or not a concern at all? Please select a rating for each concern. COLUMNS 1 Not a concern 2 Minor concern 3 Major concern ROWS 1 Seed 2 Fertilizer 3 Herbicide 4 Insecticide 5 Fungicide 6 Harvest aids 7 Harvest costs (harvester and/or custom harvest cost) 8 Labor cost 9 Labor availability COTTON GROWERS NATURAL RESOURCE SURVEY 10 10 Ginning 11 Land 12 Irrigation 13 Fuel 14 Other equipment (excluding harvester) INTRO2 DISPLAYONLY For the next series of questions, please think about one SPECIFIC cotton field with a harvestable crop that represents typical conditions on your farm in 2021. For example, a field that has: • a production practice that is predominant on your farm (if irrigated, select irrigated) • yield levels representative of your operation (not the “best” or “worst” field) Q28 INTEGER MIN = 1 MAX = Q1_COTTON_TOTAL What is the acreage of the field selected? Enter a number Q29 RADIOBUTTON CASE: ASK IF S2=2 Was the field irrigated? Select one 1 Yes 2 No Q30 INTEGER CASE: ASK IF S2=2 AND Q29=1 MIN = 1 MAX = 99 SHOW_REFUSAL_OPTION=YES REFUSAL_LABEL = Don’t know How many inches of irrigation were applied during the season? Enter a number. Q31 CHECKBOX CASE: ASK IF S2=2 AND Q29=1 RANDOMIZE STUBS Do you utilize any of the following to improve irrigation efficiency? Select all that apply 6 Make a visual assessment of plant vigor 1Irrigation scheduling programs (e.g., use local real time crop water use) 7 I make applications in response to local weather forecasts 2 Moisture monitoring equipment 3 Flow meter 4 Other tools (please describe) ANNOTATE, FIXED 5 None of the above EXCLUSIVE, FIXED Q32 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 RANDOMIZE STUBS What type of irrigation system was used? Select one COTTON GROWERS NATURAL RESOURCE SURVEY 11 1 Surface (furrow or basin) 2 Sprinkler with high pressure nozzles 3 Sprinkler with low pressure drop nozzles 4 Drip (surface or subsurface) 97 Other systems (please describe): ANNOTATE, FIXED Q33 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 RANDOMIZE STUBS What was the source of water? Select one 1 Pumping from a well 2 On-farm surface water (e.g., farm ponds) 3 Off-farm surface water (e.g., irrigation district water) 97 Other (please describe) ANNOTATE, FIXED Q34 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 What was the static water level (e.g., depth to water table)? Select one 1 0- 25 feet 2 26-75 feet 3 76-125 feet 4 126-175 feet 5 176 – 225 feet 6 Greater than 225 feet 7 Don’t know 8 Not pumping from a well Q35 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 How has the static water level changed over the last 10 years? Select one 1 Decreased 2 Stayed the same 3 Increased Q36 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 AND Q33=1 What is the pressure of the well pump? Select one 1 0-5 psi 2 6-10 psi 3 11-15 psi 4 16-20 psi 5 21-30 psi 6 31-40 psi 7 41-50 psi 8 51-60 psi 9 Greater than 60 psi 11 Don’t have a gauge 10 Don’t know COTTON GROWERS NATURAL RESOURCE SURVEY 12 Q37 RADIOBUTTON CASE: ASK IF S2=2 AND Q29=1 RANDOMIZE STUBS What is the dominant energy source for your pumps? Select one 1 Diesel 2 Electric 3 Natural gas 5 Solar 6 Wind 4 Other (please describe): ANNOTATE, FIXED Q38 INTEGER MIN=1 MAX=5,000 CASE: ASK IF S2=2 What was the field average lint yield in pounds per acre? Enter a number Q39 INTEGER CASE: ASK IF S2=2 AND Q29=1 MIN=1 MAX=5,000 SHOW_REFUSAL_OPTION=YES REFUSAL_LABEL = Don’t know Since this field was irrigated, what is your estimate of what the yield would have been if it had been grown without irrigation (e.g., compared to pivot corner yield or base on a nearby non- irrigated field)? Enter a number. Q40 CHECKBOX CASE: ASK IF S2=2 RANDOMIZESTUBS What type of winter cover was used during the (2021-22) season? Select all that apply. 1 The soil had residue from the previous crop most of the winter 2 The soil was bare most of the winter 3 Native vegetation 4 Planted cover crop 5 The field was double cropped 6 Other (please describe) ANNOTATE, FIXED 7 No winter cover was used EXCLUSIVE, FIXED Q41 CHECKBOX CASE: ASK IF S2=2 AND Q40=4 Which type of cover crop(s) did you plant? Select all that apply. 2 Cereal rye 5 Clover COTTON GROWERS NATURAL RESOURCE SURVEY 13 7 Lupine 4 Tillage radish 6 Vetch 1 Winter wheat 8 Perennial cover crop 3 Mixed species cover crop 97 Other, specify ANNOTATE, FIXED Q42 RADIOBUTTON CASE: ASK IF S2=2 How often is cotton planted on this field? Select one. 1 Every year 2 2 of 3 years 3 Every other year 4 1 of 3 years 5 Other (please describe) ANNOTATE Q43 RADIOBUTTON CASE: ASK IF S2=2 RANDOMIZESTUBS What is the primary tillage method used on this field? Select one 1 No-till/strip-till - The soil is left undisturbed from harvest to planting except for strips up to 1/3 of the row width. Surface residue and soil are disturbed only in the strip). 2 Conservation tillage including ridge-till, mulch-till, stale seedbed, or reduced till - approximately 15% to 30% or more crop residue is left on the soil surface after planting. 3 Conventional tillage - Full width tillage which disturbs all the soil surface and is performed prior to and/or during planting. Weeds are controlled by herbicides and/or mechanical cultivation. 4 Other (please describe) ANNOTATE, FIXED Q43a RADIOBUTTON Do you conduct a deep tillage operation in this field (e.g., para-tillage, deep ripping)? Select one. 1 Yes 2 No Q43b RADIOBUTTON CASE: ASK IF Q43A=1 How often do you conduct a deep tillage operation in this field? Select one 1 Every year 2 Every 2 years 3 Every 3 years 4 Every 4 or more years 5 Other (please describe) ANNOTATE COTTON GROWERS NATURAL RESOURCE SURVEY 14 Q43c RADIOBUTTON Excluding deep tillage and planting, how many times per season do you till this field? Select one 1 Once per season 2 Twice per season 3 Three times per season 4 Four or more times per season SHOW Q44 AND Q45 ON SAME PAGE Q44 INTEGER_STACKED CASE: ASK IF S2=2 RANDOMIZESTUBS MIN = 0 MAX = 99 Please list the number of applications of the following used on this field during the (2021-22) season. ROWS 1 Herbicides 2 Insecticides 3 Fungicides 4 Nematicides 5 Harvest aides 6 Plant growth regulators Q45 INTEGER_STACKED SHOW ON SAME PAGE AS Q44 CASE: ASK IF S2=2 RANDOMIZESTUBS MIN = 0 MAX = 99 Please list the total number of spray events made (either total of above or less than the above if using tank mixes) ROWS 1 Aerial 2 Ground Q46 CHECKBOX What are your target insect pests? Select all that apply. 1 Aphids 2 Banded Winged Whitefly 3 Beet Armyworm 4 Boll Weevil 5 Bollworm/Budworm 6 Cotton Fleahopper 7 Cotton Leaf Perforator 8 Cutworms 9 European Cornborer COTTON GROWERS NATURAL RESOURCE SURVEY 15 10 Fall Armyworm 11 Grasshoppers 12 Loopers 13 Lygus 14 Pink Bollworm 15 Plant Bugs 16 Saltmarsh Caterpillars 17 Silverleaf Whitefly (Bemesia) 18 Southern Armyworms 19 Spider Mites 20 Stink Bugs 21 Thrips 22 Other insects (please specify): ANNOTATE, FIXED Q47 CHECKBOX What are your target pathogens? Select all that apply 1 Alternaria leaf spot 2 Areolate mildew (Grey mold, Ramularia) 3 Ascochyta blight (wet weather blight) 4 Boll rots (Hard lock) 5 Cercospora leaf spot 10 Cotton leaf roll dwarf virus 13 Fusarium (FOV), other than FOV Race 4 (FOV 4) 14 Fusarium Race 4 (FOV 4) 6 Reniform nematode 7 Root knot nematode 8 Stemphyllium leaf spot 9 Target spot 11 Verticillium wilt 15 Seedling disease 97 Other diseases (please specify) ANNOTATE, FIXED SHOW Q48 AND Q48B ON SAME PAGE Q48 INTEGER_GRID CASE: ASK IF S2=2 MIN = 0 MAX = 9999 RANDOMIZESTUBS Please provide the pounds (lbs) of applied Nitrogen, Phosphate, and Potash, as well as details related to their application. This includes all applications on this field including pre-plant, at-planting, and side-dress fertilizers. Examples: 100 lbs Urea = 46 lbs of N, 28.2 gal UAN 32 = 100 lbs of N, 100 lbs 0-0-60 = 60 lbs of (K20) Enter a number COLUMNS 1 Nitrogen (N) 2 Phosphate (P2O5) COTTON GROWERS NATURAL RESOURCE SURVEY 16 3 Potash (K2O) ROWS 1 Total lbs per acre per year 2 Number of applications per year Q48b RATING_GRID CASE: ASK IF S2=2 SHOW ON SAME PAGE AS Q48 Application Rate Below, At, or Above soil test or university recommendation. Select one for each. ROWS 1 Nitrogen (N) 2 Phosphate (P2O5) 3 Potash (K2O) COLUMNS 1 Below soil test or university recommendation application rate 2 At soil test or university recommendation application rate 3 Above soil test or university recommendation application rate 4 Don't know Q49 CHECKBOX_GRID CASE: ASK IF S2=2 What is your dominant source of nitrogen during the following times? Select all that apply. COLUMNS 1 Dry blend 2 Liquid blend 3 Anhydrous ammonia 4 Urea 5 UAN (28, 32, etc.) 6 Other 7 Do not apply at this time EXCLUSIVE ROWS 1 Pre-plant 2 In-season Q50 CHECKBOX_GRID CASE: ASK IF S2=2 What is your dominant application method for nitrogen during the following times? Select all that apply COLUMNS 5 Dry blend 1 Injected or placed below the surface 2 Surface banded 3 Broadcast (ground, air, or fertigation) 4 Broadcasted and incorporated 97 Other ROWS RANDOMIZESTUBS COTTON GROWERS NATURAL RESOURCE SURVEY 17 1 Pre-plant 2 In-season Q51 INTEGER CASE: ASK IF S2=2 MIN = 0 MAX = 99 SHOW_REFUSAL_OPTION=YES REFUSAL_LABEL = Don’t know Not including fertilizer applications through an irrigation system, how many trips (ground or air) were necessary to apply all fertilizer products? Enter a number. Q52 RADIOBUTTON Do you use nitrification inhibitors with your fertilizer applications? Select one. 1 Yes 2 No 3 I am not familiar with these products 4 Not applicable Q53 CHECKBOX CASE: ASK IF S2=2 Which of the following, if any, do you use? Select all that apply. 2 Dolomitic lime 3 Gypsum 4 Lime (other than dolomitic and gypsum) 5 Manure 1 Micronutrients such as sulfur or boron 97 Other, specifyANNOTATE, FIXED 98 None of the above EXCLUSIVE, FIXED Q54 INTEGER_STACKED CASE: ASK IF S2=2 AND Q53<98 MATCH ORDER FROM Q53 How many pounds of each of the following did you use on this field during the 2021 growing season? Enter a number. 1 Micronutrients such as sulfur or boron MAX=999999 STUBCASE: DISPLAY IF Q53_001 = Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know 2 Dolomitic Lime MAX=999999 STUBCASE: DISPLAY IF Q53_002 = Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know COTTON GROWERS NATURAL RESOURCE SURVEY 18 3 Gypsum MAX=999999 STUBCASE: DISPLAY IF Q53_003 = Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know 4 Lime (other than dolomitic and gypsum) MAX=999999 STUBCASE:DISPLAY IF Q53_004=Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know 5 Manure MAX=999999 STUBCASE: DISPLAY IF Q53_005 = Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know 97 PIPE IN Q53_097_ANNOTATE MAX=999999 STUBCASE DISPLAY IF Q53_097 = Y SHOW_REFUSAL_OPTION=Y REFUSAL_LABEL = Don’t know Q55 CHECKBOX CASE: ASK IF S2=2 What conservation practices are associated with this field? Select all that apply. 11 Conservation cover 8 Contour buffer strip 6 Contour strip cropping 15 Drop pipes for erosion control 9 Field borders 10 Field strip cropping 7 Filter strip 2 Grass waterway 19 Leave riparian (i.e., vegetated areas bordering streams) areas undisturbed 21 Livestock integration 20 Make efforts to improve wildlife habitat 16 Precision leveled (0.1 to 0.3 % grade) 17 Recycle farm plastic (pesticide containers, poly pipe…) and/or paper and cardboard 4 Riparian (i.e., vegetated areas bordering streams) forest buffer 12 Riparian (i.e., vegetated areas bordering streams) herbaceous cover 1 Sediment basin 14 Stream habitat improvement 3 Tailwater recovery system 13 Vegetative borders 5 Water and sediment control basin 97 Other, specify ANNOTATE, FIXED 98 None of the above EXCLUSIVE, FIXED Q56 INTEGER CASE: ASK IF S2=2 MIN = 0 MAX = 99 COTTON GROWERS NATURAL RESOURCE SURVEY 19 SHOW_REFUSAL_OPTION=YES REFUSAL_LABEL = Don’t know How many miles is this field from the gin? Enter a number. DEMOGRAPHICS DISPLAYONLY The last few questions are for classification purposes only. Q57 DROPDOWN In what state is MOST of your farm located? Select one. 1 Alabama 2 Arizona 3 Arkansas 4 California 5 Florida 6 Georgia 7 Kansas 8 Louisiana 9 Mississippi 10 Missouri 11 New Mexico 12 North Carolina 13 Oklahoma 14 South Carolina 15 Tennessee 16 Texas 17 Virginia Q58_AL DROPDOWN CASE: ASK IF Q57=1 In what county is MOST of your farm located? Select one. 1 Autauga 2 Baldwin 3 Barbour 4 Bibb 5 Blount 6 Bullock 7 Butler 8 Calhoun 9 Chambers 10 Cherokee 11 Chilton 12 Choctaw 13 Clarke 14 Clay 15 Cleburne 16 Coffee 17 Colbert 18 Conecuh 19 Coosa COTTON GROWERS NATURAL RESOURCE SURVEY 20 20 Covington 21 Crenshaw 22 Cullman 23 Dale 24 Dallas 25 DeKalb 26 Elmore 27 Escambia 28 Etowah 29 Fayette 30 Franklin 31 Geneva 32 Greene 33 Hale 34 Henry 35 Houston 36 Jackson 37 Jefferson 38 Lamar 39 Lauderdale 40 Lawrence 41 Lee 42 Limestone 43 Lowndes 44 Macon 45 Madison 46 Marengo 47 Marion 48 Marshall 49 Mobile 50 Monroe 51 Montgomery 52 Morgan 53 Perry 54 Pickens 55 Pike 56 Randolph 57 Russell 58 St. Clair 59 Shelby 60 Sumter 61 Talladega 62 Tallapoosa 63 Tuscaloosa 64 Walker 65 Washington 66 Wilcox 67 Winston COTTON GROWERS NATURAL RESOURCE SURVEY 21 Q58_AZ DROPDOWN CASE: ASK IF Q57=2 In what county is MOST of your farm located? Select one. 1 Apache 2 Cochise 3 Coconino 4 Gila 5 Graham 6 Greenlee 7 La Paz 8 Maricopa 9 Mohave 10 Navajo 11 Pima 12 Pinal 13 Santa Cruz 14 Yavapai 15 Yuma Q58_AR DROPDOWN CASE: ASK IF Q57=3 In what county is MOST of your farm located? Select one. 1 Arkansas 2 Ashley 3 Baxter 4 Benton 5 Boone 6 Bradley 7 Calhoun 8 Carroll 9 Chicot 10 Clark 11 Clay 12 Cleburne 13 Cleveland 14 Columbia 15 Conway 16 Craighead 17 Crawford 18 Crittenden 19 Cross 20 Dallas 21 Desha 22 Drew 23 Faulkner 24 Franklin 25 Fulton 26 Garland 27 Grant 28 Greene COTTON GROWERS NATURAL RESOURCE SURVEY 22 29 Hempstead 30 Hot Spring 31 Howard 32 Independence 33 Izard 34 Jackson 35 Jefferson 36 Johnson 37 Lafayette 38 Lawrence 39 Lee 40 Lincoln 41 Little River 42 Logan 43 Lonoke 44 Madison 45 Marion 46 Miller 47 Mississippi 48 Monroe 49 Montgomery 50 Nevada 51 Newton 52 Ouachita 53 Perry 54 Phillips 55 Pike 56 Poinsett 57 Polk 58 Pope 59 Prairie 60 Pulaski 61 Randolph 62 St. Francis 63 Saline 64 Scott 65 Searcy 66 Sebastian 67 Sevier 68 Sharp 69 Stone 70 Union 71 Van Buren 72 Washington 73 White 74 Woodruff 75 Yell Q58_CA DROPDOWN CASE: ASK IF Q57=4 In what county is MOST of your farm located? Select one. 1 Alameda COTTON GROWERS NATURAL RESOURCE SURVEY 23 2 Alpine 3 Amador 4 Butte 5 Calaveras 6 Colusa 7 Contra Costa 8 Del Norte 9 El Dorado 10 Fresno 11 Glenn 12 Humboldt 13 Imperial 14 Inyo 15 Kern 16 Kings 17 Lake 18 Lassen 19 Los Angeles 20 Madera 21 Marin 22 Mariposa 23 Mendocino 24 Merced 25 Modoc 26 Mono 27 Monterey 28 Napa 29 Nevada 30 Orange 31 Placer 32 Plumas 33 Riverside 34 Sacramento 35 San Benito 36 San Bernardino 37 San Diego 38 San Francisco 39 San Joaquin 40 San Luis Obispo 41 San Mateo 42 Santa Barbara 43 Santa Clara 44 Santa Cruz 45 Shasta 46 Sierra 47 Siskiyou 48 Solano 49 Sonoma 50 Stanislaus 51 Sutter 52 Tehama 53 Trinity 54 Tulare COTTON GROWERS NATURAL RESOURCE SURVEY 24 55 Tuolumne 56 Ventura 57 Yolo 58 Yuba Q58_FL DROPDOWN CASE: ASK IF Q57=5 In what county is MOST of your farm located? DROPDOWN Select one. 1 Alachua 2 Baker 3 Bay 4 Bradford 5 Brevard 6 Broward 7 Calhoun 8 Charlotte 9 Citrus 10 Clay 11 Collier 12 Columbia 13 DeSoto 14 Dixie 15 Duval 16 Escambia 17 Flagler 18 Franklin 19 Gadsen 20 Gilchrist 21 Glades 22 Gulf 23 Hamilton 24 Hardee 25 Hendry 26 Hernando 27 Highlands 28 Hillsborough 29 Homes 30 Indian River 31 Jackson 32 Jefferson 33 Lafayette 34 Lake 35 Lee 36 Leon 37 Levy 38 Liberty 39 Madison 40 Manatee 41 Marion 42 Martin 43 Miami-Dade COTTON GROWERS NATURAL RESOURCE SURVEY 25 44 Monroe 45 Nassau 46 Okaloosa 47 Okeechobee 48 Orange 49 Osceola 50 Palm Beach 51 Pasco 52 Pinellas 53 Polk 54 Putnam 55 St. Johns 56 St. Lucie 57 Santa Rosa 58 Sarasota 59 Seminole 60 Sumter 61 Suwannee 62 Taylor 63 Union 64 Volusia 65 Wakulla 66 Walton 67 Washington Q58_GA DROPDOWN CASE: ASK IF Q57=6 1 Carroll 2 Catoosa 3 Charlton 4 Chatham 5 Chattooga 6 Cherokee 7 Clay 8 Clayton 9 Clinch 10 Cobb 11 Coffee 12 Colquitt 13 Columbia 14 Columbia-Muscogee 15 Cook 16 Coweta 17 Crawford 18 Crisp 19 Cusseta-Chattahoochee 20 Dade 21 Dawson 22 Decatur 23 DeKalb 24 Dodge 25 Dooly COTTON GROWERS NATURAL RESOURCE SURVEY 26 26 Dougherty 27 Douglas 28 Early 29 Echols 30 Effingham 31 Elbert 32 Emanuel 33 Evans 34 Fannin 35 Fayette 36 Floyd 37 Forsyth 38 Franklin 39 Fulton 40 Georgetown-Quitman 41 Gilmer 42 Glascock 43 Glynn 44 Gordon 45 Grady 46 Greene 47 Gwinnett 48 Habersham 49 Hall 50 Hancock 51 Haralson 52 Harris 53 Hart 54 Heard 55 Henry 56 Houston 57 Irwin 58 Jackson 59 Jasper 60 Jeff Davis 61 Jefferson 62 Jenkins 63 Johnson 64 Jones 65 Lamar 66 Lanier 67 Laurens 68 Lee 69 Liberty 70 Lincoln 71 Long 72 Lowndes 73 Lumpkin 74 Macon 75 Macon-Bibb 76 Madison 77 Marion 78 McDuffie COTTON GROWERS NATURAL RESOURCE SURVEY 27 79 McIntosh 80 Meriwether 81 Miller 82 Mitchell 83 Monroe 84 Montgomery 85 Morgan 86 Murray 87 Newton 88 Oconee 89 Oglethorpe 90 Paulding 91 Peach 92 Pickens 93 Pierce 94 Pike 95 Polk 96 Pulaski 97 Putnam 98 Rabun 99 Randolph 100 Rockdale 101 Schley 102 Screven 103 Seminole 104 Spalding 105 Stephens 106 Stewart 107 Sumter 108 Talbot 109 Taliaferro 110 Tattnall 111 Taylor 112 Telfair 113 Terrell 114 Thomas 115 Tift 116 Toombs 117 Towns 118 Treutlen 119 Troup 120 Turner 121 Twiggs 122 Union 123 Upson 124 Walker 125 Walton 126 Ware 127 Warren 128 Washington 129 Wayne 130 Webster 131 Wheeler COTTON GROWERS NATURAL RESOURCE SURVEY 28 132 White 133 Whitfield 134 Wilcox 135 Wilkes 136 Wilkinson 137 Worth Q58_KS DROPDOWN CASE: ASK IF Q57=7 In what county is MOST of your farm located? Select one. 1 Allen 2 Anderson 3 Atchison 4 Barber 5 Barton 6 Bourbon 7 Brown 8 Butler 9 Chase 10 Chautauqua 11 Cherokee 12 Cheyenne 13 Clark 14 Clay 15 Cloud 16 Coffey 17 Comanche 18 Cowley 19 Crawford 20 Decatur 21 Dickinson 22 Doniphan 23 Douglas 24 Edwards 25 Elk 26 Ellis 27 Ellsworth 28 Finney 29 Ford 30 Franklin 31 Geary 32 Gove 33 Graham 34 Grant 35 Gray 36 Greeley 37 Greenwood 38 Hamilton 39 Harper 40 Harvey 41 Haskell COTTON GROWERS NATURAL RESOURCE SURVEY 29 42 Hodgeman 43 Jackson 44 Jefferson 45 Jewell 46 Johnson 47 Kearny 48 Kingman 49 Kiowa 50 Labette 51 Lane 52 Leavenworth 53 Lincoln 54 Linn 55 Logan 56 Lyon 57 Marion 58 Marshall 59 McPherson 60 Meade 61 Miami 62 Mitchell 63 Montgomery 64 Morris 65 Morton 66 Nemaha 67 Neosho 68 Ness 69 Norton 70 Osage 71 Osborne 72 Ottawa 73 Pawnee 74 Phillips 75 Pottawatomie 76 Pratt 77 Rawlins 78 Reno 79 Republic 80 Rice 81 Riley 82 Rooks 83 Rush 84 Russell 85 Saline 86 Scott 87 Sedgwick 88 Seward 89 Shawnee 90 Sheridan 91 Sherman 92 Smith 93 Stafford 94 Stanton COTTON GROWERS NATURAL RESOURCE SURVEY 30 95 Stevens 96 Sumner 97 Thomas 98 Trego 99 Wabaunsee 100 Wallace 101 Washington 102 Wichita 103 Wilson 104 Woodson 105 Wyandotte Q58_LA DROPDOWN CASE: ASK IF Q57=8 In what parish is MOST of your farm located? Select one. 1 Acadia 2 Allen 3 Ascension 4 Assumption 5 Avoyelles 6 Beauregard 7 Bienville 8 Bossier 9 Caddo 10 Calcasieu 11 Caldwell 12 Cameron 13 Catahoula 14 Claiborne 15 Concordia 16 DeSoto 17 East Baton Rouge 18 East Carroll 19 East Feliciana 20 Evangeline 21 Franklin 22 Grant 23 Iberia 24 Iberville 25 Jackson 26 Jefferson 27 Jefferson Davis 28 Lafayette 29 Lafourche 30 LaSalle 31 Lincoln 32 Livingston 33 Madison 34 Morehouse 35 Natchitoches 36 Orleans COTTON GROWERS NATURAL RESOURCE SURVEY 31 37 Ouachita 38 Plaquemines 39 Pointe Coupee 40 Rapides 41 Red River 42 Richland 43 Sabine 44 St. Bernard 45 St. Charles 46 St. Helena 47 St. James 48 St. John the Baptist 49 St. Landry 50 St. Martin 51 St. Mary 52 St. Tammany 53 Tangipahoa 54 Tensas 55 Terrebonne 56 Union 57 Vermilion 58 Vernon 59 Washington 60 Webster 61 West Baton Rouge 62 West Carroll 63 West Feliciana 64 Winn Q58_MS DROPDOWN CASE: ASK IF Q57=9 In what county is MOST of your farm located? Select one. 1 Adams 2 Alcorn 3 Amite 4 Attala 5 Benton 6 Bolivar 7 Calhoun 8 Carroll 9 Chickasaw 10 Choctaw 11 Claiborne 12 Clarke 13 Clay 14 Coahoma 15 Copiah 16 Covington 17 DeSoto 18 Forrest 19 Franklin COTTON GROWERS NATURAL RESOURCE SURVEY 32 20 George 21 Greene 22 Grenada 23 Hancock 24 Harrison 25 Hinds 26 Holmes 27 Humphreys 28 Issaquena 29 Itawamba 30 Jackson 31 Jasper 32 Jefferson 33 Jefferson Davis 34 Jones 35 Kemper 36 Lafayette 37 Lamar 38 Lauderdale 39 Lawrence 40 Leake 41 Lee 42 Leflore 43 Lincoln 44 Lowndes 45 Madison 46 Marion 47 Marshall 48 Monroe 49 Montgomery 50 Neshoba 51 Newton 52 Noxubee 53 Oktibbeha 54 Panola 55 Pearl River 56 Perry 57 Pike 58 Pontotoc 59 Prentiss 60 Quitman 61 Rankin 62 Scott 63 Sharkey 64 Simpson 65 Smith 66 Stone 67 Sunflower 68 Tallahatchie 69 Tate 70 Tippah 71 Tishomingo 72 Tunica COTTON GROWERS NATURAL RESOURCE SURVEY 33 73 Union 74 Walthall 75 Warren 76 Washington 77 Wayne 78 Webster 79 Wilkinson 80 Winston 81 Yalobusha 82 Yazoo Q58_MO DROPDOWN CASE: ASK IF Q57=10 In what county is MOST of your farm located? Select one. 1 Adair 2 Andrew 3 Atchison 4 Audrain 5 Barry 6 Barton 7 Bates 8 Benton 9 Bollinger 10 Boone 11 Buchanan 12 Butler 13 Caldwell 14 Callaway 15 Camden 16 Cape Girardeau 17 Carroll 18 Carter 19 Cass 20 Cedar 21 Chariton 22 Christian 23 Clark 24 Clay 25 Clinton 26 Cole 27 Cooper 28 Crawford 29 Dade 30 Dallas 31 Daviess 32 DeKalb 33 Dent 34 Douglas 35 Dunklin 36 Franklin 37 Gasconade COTTON GROWERS NATURAL RESOURCE SURVEY 34 38 Gentry 39 Greene 40 Grundy 41 Harrison 42 Henry 43 Hickory 44 Holt 45 Howard 46 Howell 47 Iron 48 Jackson 49 Jasper 50 Jefferson 51 Johnson 52 Knox 53 Laclede 54 Lafayette 55 Lawrence 56 Lewis 57 Lincoln 58 Linn 59 Livingston 60 Macon 61 Madison 62 Maries 63 Marion 64 McDonald 65 Mercer 66 Miller 67 Mississippi 68 Moniteau 69 Monroe 70 Montgomery 71 Morgan 72 New Madrid 73 Newton 74 Nodaway 75 Oregon 76 Osage 77 Ozark 78 Pemiscot 79 Perry 80 Pettis 81 Phelps 82 Pike 83 Platte 84 Polk 85 Pulaski 86 Putnam 87 Ralls 88 Randolph 89 Ray 90 Reynolds COTTON GROWERS NATURAL RESOURCE SURVEY 35 91 Ripley 92 St. Charles 93 St. Clair 94 St. Francois 95 St. Louis (county) 96 St. Louis city 97 St. Genevieve 98 Saline 99 Schuyler 100 Scotland 101 Scott 102 Shannon 103 Shelby 104 Stoddard 105 Stone 106 Sullivan 107 Taney 108 Texas 109 Vernon 110 Warren 111 Washington 112 Wayne 113 Webster 114 Worth 115 Wright Q58_NM DROPDOWN CASE: ASK IF Q57=11 In what county is MOST of your farm located? Select one. 1 Bernalillo 2 Catron 3 Chaves 4 Cibola 5 Colfax 6 Curry 7 De Baca 8 Doña Ana 9 Eddy 10 Grant 11 Guadalupe 12 Harding 13 Hidalgo 14 Lea 15 Lincoln 16 Los Alamos 17 Luna 18 McKinley 19 Mora 20 Otero 21 Quay 22 Rio Arriba COTTON GROWERS NATURAL RESOURCE SURVEY 36 23 Roosevelt 24 Sandoval 25 San Juan 26 San Miguel 27 Santa Fe 28 Sierra 29 Socorro 30 Taos 31 Torrance 32 Union 33 Valencia Q58_NC DROPDOWN CASE: ASK IF Q57=12 In what county is MOST of your farm located? Select one. 1 Alamance 2 Alexander 3 Alleghany 4 Anson 5 Ashe 6 Avery 7 Beaufort 8 Bertie 9 Bladen 10 Brunswick 11 Buncombe 12 Burke 13 Cabarrus 14 Caldwell 15 Camden 16 Carteret 17 Caswell 18 Catawba 19 Chatham 20 Cherokee 21 Chowan 22 Clay 23 Cleveland 24 Columbus 25 Craven 26 Cumberland 27 Currituck 28 Dare 29 Davidson 30 Davie 31 Duplin 32 Durham 33 Edgecombe 34 Forsyth 35 Franklin 36 Gaston COTTON GROWERS NATURAL RESOURCE SURVEY 37 37 Gates 38 Graham 39 Granville 40 Greene 41 Guilford 42 Halifax 43 Harnett 44 Haywood 45 Henderson 46 Hertford 47 Hoke 48 Hyde 49 Iredell 50 Jackson 51 Johnston 52 Jones 53 Lee 54 Lenoir 55 Lincoln 56 Macon 57 Madison 58 Martin 59 McDowell 60 Mecklenburg 61 Mitchell 62 Montgomery 63 Moore 64 Nash 65 New Hanover 66 Northampton 67 Onslow 68 Orange 69 Pamlico 70 Pasquotank 71 Pender 72 Perquimans 73 Person 74 Pitt 75 Polk 76 Randolph 77 Richmond 78 Robeson 79 Rockingham 80 Rowan 81 Rutherford 82 Sampson 83 Scotland 84 Stanly 85 Stokes 86 Surry 87 Swain 88 Transylvania 89 Tyrrell COTTON GROWERS NATURAL RESOURCE SURVEY 38 90 Union 91 Vance 92 Wake 93 Warren 94 Washington 95 Watauga 96 Wayne 97 Wilkes 98 Wilson 99 Yadkin 100 Yancey Q58_OK DROPDOWN CASE: ASK IF Q57=13 In what county is MOST of your farm located? Select one. 1 Adair 2 Alfalfa 3 Atoka 4 Beaver 5 Beckham 6 Blaine 7 Bryan 8 Caddo 9 Canadian 10 Carter 11 Cherokee 12 Choctaw 13 Cimarron 14 Cleveland 15 Coal 16 Comanche 17 Cotton 18 Craig 19 Creek 20 Custer 21 Delaware 22 Dewey 23 Ellis 24 Garfield 25 Garvin 26 Grady 27 Grant 28 Greer 29 Harmon 30 Harper 31 Haskell 32 Hughes 33 Jackson 34 Jefferson 35 Johnston 36 Kay COTTON GROWERS NATURAL RESOURCE SURVEY 39 37 Kingfisher 38 Kiowa 39 Latimer 40 Le Flore 41 Lincoln 42 Logan 43 Love 44 Major 45 Marshall 46 Mayes 47 McClain 48 McCurtain 49 McIntosh 50 Murray 51 Muskogee 52 Noble 53 Nowata 54 Okfuskee 55 Oklahoma 56 Okmulgee 57 Osage 58 Ottawa 59 Pawnee 60 Payne 61 Pittsburg 62 Pontotoc 63 Pottawatomie 64 Pushmataha 65 Roger Mills 66 Rogers 67 Seminole 68 Sequoyah 69 Stephens 70 Texas 71 Tillman 72 Tulsa 73 Wagoner 74 Washington 75 Washita 76 Woods 77 Woodward Q58_SC DROPDOWN CASE: ASK IF Q57=14 In what county is MOST of your farm located? Select one. 1 Abbeville 2 Aiken 3 Allendale 4 Anderson 5 Bamberg 6 Barnwell COTTON GROWERS NATURAL RESOURCE SURVEY 40 7 Beaufort 8 Berkeley 9 Calhoun 10 Charleston 11 Cherokee 12 Chester 13 Chesterfield 14 Clarendon 15 Colleton 16 Darlington 17 Dillon 18 Dorchester 19 Edgefield 20 Fairfield 21 Florence 22 Georgetown 23 Greenville 24 Greenwood 25 Hampton 26 Horry 27 Jasper 28 Kershaw 29 Lancaster 30 Laurens 31 Lee 32 Lexington 33 Marion 34 Marlboro 35 McCormick 36 Newberry 37 Oconee 38 Orangeburg 39 Pickens 40 Richland 41 Saluda 42 Spartanburg 43 Sumter 44 Union 45 Williamsburg 46 York Q58_TN DROPDOWN CASE: ASK IF Q57=15 In what county is MOST of your farm located? Select one. 1 Anderson 2 Bedford 3 Benton 4 Bledsoe 5 Blount 6 Bradley 7 Campbell COTTON GROWERS NATURAL RESOURCE SURVEY 41 8 Cannon 9 Carroll 10 Carter 11 Cheatham 12 Chester 13 Claiborne 14 Clay 15 Cocke 16 Coffee 17 Crockett 18 Cumberland 19 Davidson 20 Decatur 21 DeKalb 22 Dickson 23 Dyer 24 Fayette 25 Fentress 26 Franklin 27 Gibson 28 Giles 29 Grainger 30 Greene 31 Grundy 32 Hamblen 33 Hamilton 34 Hancock 35 Hardeman 36 Hardin 37 Hawkins 38 Haywood 39 Henderson 40 Henry 41 Hickman 42 Houston 43 Humphreys 44 Jackson 45 Jefferson 46 Johnson 47 Knox 48 Lake 49 Lauderdale 50 Lawrence 51 Lewis 52 Lincoln 53 Loudon 54 Macon 55 Madison 56 Marion 57 Marshall 58 Maury 59 McMinn 60 McNairy COTTON GROWERS NATURAL RESOURCE SURVEY 42 61 Meigs 62 Monroe 63 Montgomery 64 Moore 65 Morgan 66 Obion 67 Overton 68 Perry 69 Pickett 70 Polk 71 Putnam 72 Rhea 73 Roane 74 Robertson 75 Rutherford 76 Scott 77 Sequatchie 78 Sevier 79 Shelby 80 Smith 81 Stewart 82 Sullivan 83 Sumner 84 Tipton 85 Trousdale 86 Unicoi 87 Union 88 Van Buren 89 Warren 90 Washington 91 Wayne 92 Weakley 93 White 94 Williamson 95 Wilson Q58_TX DROPDOWN CASE: ASK IF Q57=16 In what county is MOST of your farm located? Select one. 1 Anderson 2 Andrews 3 Angelina 4 Aransas 5 Archer 6 Armstrong 7 Atascosa 8 Austin 9 Bailey 10 Bandera 11 Bastrop 12 Baylor 13 Bee COTTON GROWERS NATURAL RESOURCE SURVEY 43 14 Bell 15 Bexar 16 Blanco 17 Borden 18 Bosque 19 Bowie 20 Brazoria 21 Brazos 22 Brewster 23 Briscoe 24 Brooks 25 Brown 26 Burleson 27 Burnet 28 Caldwell 29 Calhoun 30 Callahan 31 Cameron 32 Camp 33 Carson 34 Cass 35 Castro 36 Chambers 37 Cherokee 38 Childress 39 Clay 40 Cochran 41 Coke 42 Coleman 43 Collin 44 Collingsworth 45 Colorado 46 Comal 47 Comanche 48 Concho 49 Cooke 50 Coryell 51 Cottle 52 Crane 53 Crockett 54 Crosby 55 Culberson 56 Dallam 57 Dallas 58 Dawson 59 Deaf Smith 60 Delta 61 Denton 62 DeWitt 63 Dickens 64 Dimmit 65 Donley 66 Duval COTTON GROWERS NATURAL RESOURCE SURVEY 44 67 Eastland 68 Ector 69 Edwards 70 Ellis 71 El Paso 72 Erath 73 Falls 74 Fannin 75 Fayette 76 Fisher 77 Floyd 78 Foard 79 Fort Bend 80 Franklin 81 Freestone 82 Frio 83 Gaines 84 Galveston 85 Garza 86 Gillespie 87 Glasscock 88 Goliad 89 Gonzales 90 Gray 91 Grayson 92 Gregg 93 Grimes 94 Guadalupe 95 Hale 96 Hall 97 Hamilton 98 Hansford 99 Hardeman 100 Hardin 101 Harris 102 Harrison 103 Hartley 104 Haskell 105 Hays 106 Hemphill 107 Henderson 108 Hidalgo 109 Hill 110 Hockley 111 Hood 112 Hopkins 113 Houston 114 Howard 115 Hudspeth 116 Hunt 117 Hutchinson 118 Irion 119 Jack COTTON GROWERS NATURAL RESOURCE SURVEY 45 120 Jackson 121 Jasper 122 Jeff Davis 123 Jefferson 124 Jim Hogg 125 Jim Wells 126 Johnson 127 Jones 128 Karnes 129 Kaufman 130 Kendall 131 Kenedy 132 Kent 133 Kerr 134 Kimble 135 King 136 Kinney 137 Kleberg 138 Knox 139 Lamar 140 Lamb 141 Lampasas 142 La Salle 143 Lavaca 144 Lee 145 Leon 146 Liberty 147 Limestone 148 Lipscomb 149 Live Oak 150 Llano 151 Loving 152 Lubbock 153 Lynn 154 McCulloch 155 McLennan 156 McMullen 157 Madison 158 Marion 159 Martin 160 Mason 161 Matagorda 162 Maverick 163 Medina 164 Menard 165 Midland 166 Milam 167 Mills 168 Mitchell 169 Montague 170 Montgomery 171 Moore 172 Morris COTTON GROWERS NATURAL RESOURCE SURVEY 46 173 Motley 174 Nacogdoches 175 Navarro 176 Newton 177 Nolan 178 Nueces 179 Ochiltree 180 Oldham 181 Orange 182 Palo Pinto 183 Panola 184 Parker 185 Parmer 186 Pecos 187 Polk 188 Potter 189 Presidio 190 Rains 191 Randall 192 Reagan 193 Real 194 Red River 195 Reeves 196 Refugio 197 Roberts 198 Robertson 199 Rockwall 200 Runnels 201 Rusk 202 Sabine 203 San Augustine 204 San Jacinto 205 San Patricio 206 San Saba 207 Schleicher 208 Scurry 209 Shackleford 210 Shelby 211 Sherman 212 Smith 213 Somervell 214 Starr 215 Stephens 216 Sterling 217 Stonewall 218 Sutton 219 Swisher 220 Tarrant 221 Taylor 222 Terrell 223 Terry 224 Throckmorton 225 Titus COTTON GROWERS NATURAL RESOURCE SURVEY 47 226 Tom Green 227 Travis 228 Trinity 229 Tyler 230 Upshur 231 Upton 232 Uvalde 233 Val Verde 234 Van Zandt 235 Victoria 236 Walker 237 Waller 238 Ward 239 Washington 240 Webb 241 Wharton 242 Wheeler 243 Wichita 244 Wilbarger 245 Willacy 246 Williamson 247 Wilson 248 Winkler 249 Wise 250 Wood 251 Yoakum 252 Young 253 Zapata 254 Zavala Q58_VA DROPDOWN CASE: ASK IF Q57=17 In what county is MOST of your farm located? Select one. 1 Accomack 2 Albemarle 3 Alleghany 4 Amelia 5 Amherst 6 Appomattox 7 Arlington 8 Augusta 9 Bath 10 Bedford 11 Bland 12 Botetourt 13 Brunswick 14 Buchanan 15 Buckingham 16 Campbell 17 Caroline 18 Carroll COTTON GROWERS NATURAL RESOURCE SURVEY 48 19 Charles City 20 Charlotte 21 Chesterfield 22 Clarke 23 Craig 24 Culpeper 25 Cumberland 26 Dickenson 27 Dinwiddie 28 Essex 29 Fairfax 30 Fauquier 31 Floyd 32 Fluvanna 33 Franklin 34 Frederick 35 Giles 36 Gloucester 37 Goochland 38 Grayson 39 Greene 40 Greensville 41 Halifax 42 Hanover 43 Henrico 44 Henry 45 Highland 46 Isle of Wight 47 James City 48 King and Queen 49 King George 50 King William 51 Lancaster 52 Lee 53 Loudoun 54 Louisa 55 Lunenburg 56 Madison 57 Mathews 58 Mecklenburg 59 Middlesex 60 Montgomery 61 Nelson 62 New Kent 63 Northampton 64 Northumberland 65 Nottoway 66 Orange 67 Page 68 Patrick 69 Pittsylvania 70 Powhatan 71 Prince Edward COTTON GROWERS NATURAL RESOURCE SURVEY 49 72 Prince George 73 Prince William 74 Pulaski 75 Rappahannock 76 Richmond 77 Roanoke 78 Rockbridge 79 Rockingham 80 Russell 81 Scott 82 Shenandoah 83 Smyth 84 Southampton 85 Spotsylvania 86 Stafford 87 Surry 88 Sussex 89 Tazewell 90 Warren 91 Washington 92 Westmoreland 93 Wise 94 Wythe 95 York 96 Independent city Q59 INTEGER MIN = 18 MAX = 99 What is your age? Enter a number. Q59b HIDDEN DO NOT DISPLAY AUTOPUNCH BASED ON ANSWER TO Q59 – 1 18-30 2 31-40 3 41-50 4 51-60 5 61+ Q60 RADIOBUTTON How many total years have you been growing cotton? Select one. 1 0-5 2 6-10 3 11-20 4 21-30 5 31+ Q61 RATING_GRID REPEAT HEADERS EVERY 5 ROWS To help Cotton Incorporated and the Cotton Board improve your access to results from its cotton production research program, please rate how much you depend on the sources of COTTON GROWERS NATURAL RESOURCE SURVEY 50 information below. Select one for each. COLUMNS 1 1 - None 2 2 - Slightly 3 3 - Moderately 4 4 - Greatly ROWS RANDOMIZESTUBS 1 Ag. magazines such as Cotton Grower, Cotton Farming, Progressive Farmer 2 University/Extension specialists or agents 3 Crop consultants 4 Other cotton producers 5 Agribusiness sales representatives 6 Cotton industry organizations such as the U.S. Cotton Trust Protocol, National Cotton Council, Cotton Incorporated 7 Internet websites 8 Smartphone apps 13 Twitter 14 Facebook 15 LinkedIn 16 YouTube 17 Other social media such as Instagram, TikTok, or Snapchat 9 Email newsletters 10 Field days/ Demonstrations 11 Technical publications/ Journals/ Fact sheets 12 Agricultural conferences Q62 RADIOBUTTON Are you interested in or already participating in an ecosystem service market program (i.e., carbon markets)? Select one. 1 Yes, I am already participating 2 No, I am not participating but I am interested 3 No, I am not participating nor interested END PAGES TERM DISPLAYONLY Thank you for your time. You have completed the survey. CLOSE DISPLAYONLY That completes the survey. Thank you very much for your time! Please follow this link to claim your 30oz. Cotton Yeti: https://forms.office.com/r/EGiZntEwLR https://forms.office.com/r/EGiZntEwLR APPENDIX 2 Supplementary Tables (ST): ST1: Cotton Production Challenges ST2: Primary Tillage Methods ST3: Practices to Mitigate Soil Erosion ST4: Irrigation Systems ST5: Practices to Handle Tailwater ST6: Precision Agriculture Technologies ST7: Spray Events ST8: Herbicide/Insecticide/Fungicide Management ST9: Target Insects ST10: Target Pathogens Abbreviations: SE - Southeast MS - Midsouth SW - Southwest FW – Far West Q – Question ST 1. Q26: How would you rate the following cotton production concerns or challenges on your farm? Please, select a rating for each concern or challenge. Cotton Production Challenges in the 2023 Survey Not an Issue Moderate Issue Major Issue SE MS SW FW U.S. SE MS SW FW U.S. SE MS SW FW U.S. Cotton production input costs 4% 5% 4% 8% 4% 19% 16% 19% 12% 18% 77% 80% 77% 80% 78% Weed resistance to herbicides 7% 5% 3% 8% 5% 36% 29% 26% 40% 31% 57% 65% 72% 52% 65% Weed control 9% 0% 4% 8% 7% 43% 39% 33% 48% 38% 48% 54% 63% 44% 55% Cottonseed value 10% 8% 8% 4% 8% 42% 44% 39% 60% 42% 48% 48% 53% 36% 50% Increased frequency of drought and extreme weather events 13% 16% 7% 12% 11% 46% 53% 30% 20% 39% 41% 32% 63% 68% 50% Seedling vigor and stand establishment 14% 17% 9% 12% 12% 40% 44% 41% 48% 42% 46% 39% 50% 40% 46% Adequate water supply 33% 50% 13% 4% 27% 41% 33% 24% 8% 31% 25% 16% 63% 88% 42% Cotton’s tolerance to heat and drought 14% 22% 14% 8% 15% 49% 47% 42% 44% 45% 37% 32% 44% 48% 40% Consumer attitudes about agriculture’s impact on the environment 20% 24% 20% 32% 21% 43% 43% 39% 24% 41% 37% 33% 41% 44% 38% Lack of new crop protection products (insecticides, herbicides, etc.) 19% 15% 18% 32% 18% 46% 45% 51% 52% 48% 35% 40% 31% 16% 34% Spread of plant diseases and weeds 13% 12% 14% 20% 14% 53% 58% 57% 72% 56% 34% 29% 29% 8% 30% Insect resistance to insecticides and Bt cotton 18% 13% 27% 28% 21% 49% 47% 50% 44% 49% 33% 40% 23% 28% 30% Efficient use of fertilizer 17% 22% 23% 24% 21% 52% 51% 49% 56% 51% 31% 26% 27% 20% 28% Cotton Production Challenges in the 2023 Survey Not an Issue Moderate Issue Major Issue SE MS SW FW U.S. SE MS SW FW U.S. SE MS SW FW U.S. Herbicides drift 29% 19% 18% 24% 22% 48% 49% 52% 60% 51% 23% 32% 30% 16% 27% Disease concerns related to nematodes, target spot, virus etc. 11% 12% 25% 32% 18% 54% 63% 59% 48% 57% 35% 25% 16% 20% 24% Variety selection 29% 33% 30% 40% 31% 43% 41% 48% 44% 45% 27% 26% 22% 16% 24% Plant bug control 16% 9% 36% 28% 24% 61% 40% 52% 52% 53% 22% 52% 11% 20% 23% Soil erosion 27% 22% 26% 64% 27% 55% 57% 54% 32% 54% 18% 21% 20% 4% 19% Harvest aid materials and application timing 31% 36% 29% 28% 31% 51% 45% 53% 40% 51% 18% 19% 18% 32% 19% Stinkbug control 15% 32% 52% 48% 35% 54% 48% 40% 40% 46% 31% 20% 8% 12% 19% Monitoring cotton’s plant growth 29% 33% 35% 28% 32% 51% 45% 51% 64% 51% 19% 22% 14% 8% 17% Soil sampling and analysis for fertilization 37% 39% 44% 40% 40% 39% 38% 47% 44% 43% 24% 23% 9% 16% 17% Soil compaction 28% 21% 28% 16% 26% 57% 59% 57% 72% 58% 15% 20% 15% 12% 16% Insecticides drift 51% 51% 56% 44% 53% 41% 35% 31% 40% 36% 8% 14% 12% 16% 11% Water salinity of irrigation wells 80% 74% 50% 40% 65% 16% 19% 32% 32% 24% 4% 7% 18% 28% 11% Effects of agriculture on wildlife 51% 53% 59% 80% 56% 36% 36% 34% 20% 35% 13% 12% 7% 0% 10% Soil salinity 72% 65% 47% 44% 59% 26% 27% 39% 32% 32% 2% 8% 14% 24% 9% Water quality protection from agricultural runoff 48% 49% 58% 60% 53% 41% 41% 36% 36% 39% 11% 10% 6% 4% 8% Dust from harvesting, farming, gins 70% 67% 65% 40% 66% 28% 27% 31% 48% 30% 1% 5% 4% 12% 4% ST 2. Q43. What is the primary tillage method used in this field? Select one. Primary Tillage Systems % of respondents by region Southeast Midsouth Southwest Far West U.S. No-till/strip-till 68% 46% 50% 33% 56% Conservation till 16% 33% 19% 33% 21% Conventional till 15% 21% 31% 33% 23% Other 1% 1% 0% 0% 1% ST 3. Q8. What practices are used to minimize soil erosion on your farm? Select all that apply. Practices to minimize soil erosion % of respondents by region Southeast Midsouth Southwest Far West U.S. Strip-till/No-till 85.5% 50.4% 57.4% 36.0% 65.7% Planted cover crops 72.7% 62.8% 59.9% 52.0% 64.8% Ground cover 56.7% 48.1% 56.5% 44.0% 54.7% Irrigation management 37.5% 47.3% 48.2% 68.0% 44.8% Contour terraces/Plant rows 46.9% 27.1% 38.0% 28.0% 39.0% Grassed waterways/Buffer strips 52.7% 36.4% 16.4% 16.0% 33.1% Planted wheat/Vegetation as a windbreak 13.1% 21.7% 42.0% 20.0% 27.2% Sand fighters 0.0% 3.9% 49.4% 20.0% 22.6% Drain design 21.1% 36.4% 8.3% 16.0% 18.1% Precisely level fields 3.6% 38.0% 7.4% 48.0% 12.6% No practices 0.7% 3.9% 3.4% 4.0% 2.5% Other 0.4% 1.6% 0.6% 12.0% 1.1% ST 4. Q32. What type of irrigation system was used? Select all that apply. Irrigation Systems % of respondents by region Southeast Midsouth Southwest Far West U.S. Sprinkler with low pressure drop nozzles 68.0% 9.3% 44.9% 29.4% 45.1% Sprinkler with high-pressure nozzles 14.4% 7.4% 8.0% 0.0% 9.5% Surface (Furrow/Basin) 3.1% 66.7% 10.1% 58.8% 20.6% Drip (Surface/Subsurface) 2.1% 5.6% 20.3% 5.9% 11.1% Other* 12.4% 11.1% 16.7% 5.9% 13.7% *Other- The majority of respondents claimed the "other" category as Central Pivot (Sprinkler) systems ST 5. Q5. What management practices are used to handle tailwater or surface run-off? Select all that apply. Management practices % of respondents by region Southeast Midsouth Southwest Far West U.S. Field slope/length 72.7% 70.5% 64.5% 56.0% 68.3% Holding pond 16.4% 8.5% 12.7% 24.0% 13.7% Tailwater run-off 6.6% 17.1% 9.9% 24.0% 10.4% Surge system 1.5% 19.4% 2.8% 16.0% 5.6% Tailwater return system 2.2% 4.7% 6.5% 32.0% 5.4% ST 6. Q19. Which of the following precision agriculture technologies do you use in your cotton operation? Select all that apply Precision Technologies % of respondents by region Southeast Midsouth Southwest Far West U.S. Autosteer/GPS 83% 85% 89% 72% 86% Soil sampling 66% 72% 21% 20% 46% Soil map 47% 49% 27% 28% 38% Yield monitor 33% 58% 28% 20% 35% Imagery 17% 24% 18% 24% 19% Hand-held GPS 17% 22% 16% 44% 18% Other 3% 1% 1% 0% 1% New additions to the 2023 survey question Southeast Midsouth Southwest Far West U.S. Swath control on the spray boom 70% 78% 71% 56% 71% Swath control on a planter 43% 49% 34% 40% 40% Unpiloted Aerial Vehicles (UAVs) 5% 7% 6% 12% 6% See and spray system: Weed-IT, Weed seeker, John Deere see and spray. 4% 5% 6% 4% 5% Not using precision technologies 4% 1% 4% 16% 4% ST 7. Q44. Please list the number of applications of the following used in this field during the 2021-22 season. Q45. Please list the total number of spray events made (either a total of above or less than the above if using tank mixes). Application practices The average number of applications during the 2021/22 growing season SE MS SW FW U.S. Herbicides 3.5 4.4 3.7 3.1 3.7 Insecticides 2.9 4.6 1.7 1.6 2.7 Fungicides 1.2 1.1 0.5 0.1 0.8 Nematicides 1.2 1.3 0.4 1.7 2.2 Harvest aids 1.4 2.8 1.7 1.5 1.8 Plant growth regulators 3.3 4.1 2.2 2.0 3.0 Spray events using tank mixes SE MS SW FW U.S. Ground 6.7 7.8 5.5 3.5 6.3 Aerial 1.1 1.7 1.3 1.3 1.3 ST 8. Q13. How do you decide you need to apply a foliar herbicide/insecticide to cotton fields? Q14. Were there any cotton fields that did NOT require foliar herbicides/insecticides in the most recent year you grew cotton? Q15. Approximately, how many cotton acres did NOT require foliar herbicides/insecticides in the most recent year you grew cotton? Q16. How do you decide you need to apply a foliar fungicide to cotton fields? Q17. Were there any cotton fields that did NOT require foliar fungicides in the most recent year you grew cotton? Q18 Approximately how many cotton acres did NOT require foliar fungicides in the most recent year you grew cotton? Pesticide Management Practices Herbicides Insecticides Fungicides SE MS SW FW U.S. SE MS SW FW U.S. SE MS SW FW U.S. Cotton fields that did not require foliar pesticides (% of responses) 8.9% 4.7% 15.6% 7.9% 11.0% 22.9% 9.3% 59.2% 53.9% 36.7% 69.8% 69.8% 77.3% 76.9% 73.1% Cotton acres did not require foliar pesticides (total acres) 1,920 1,825 28,884 105 32,734 8,811 2,315 139,168 1,605 151,899 55,787 40,678 203,726 2,250 302,441 Cotton fields did not require foliar pesticides (% of total acres by region) 1% 1% 5% 1% 3% 4% 1% 26% 9% 16% 26% 24% 38% 13% 32% Decision to apply a foliar pesticide (% of responses) After scouting a crop 71.9% 58.1% 76.8% 76.9% 71.7% 57.8% 33.7% 63.5% 46.2% 55.8% 53.1% 31.4% 40.3% 46.2% 43.8% Consultant recommendations 51.6% 83.7% 49.3% 61.5% 56.4% 65.1% 90.7% 58.3% 53.9% 66.3% 51.6% 72.1% 44.1% 38.5% 51.6% Treating only part of a field hotspots 18.2% 32.6% 22.8% 7.7% 22.3% 12.5% 25.6% 20.4% 15.4% 18.1% 12.0% 5.8% 2.4% 0.0% 6.6% Calendar spray schedule (only for herbicides and insecticides) 22.9% 8.1% 9.5% 0.0% 14.1% 13.0% 2.3% 4.7% 7.7% 7.6% Based on cultivar selected (only for fungicide) 9.4% 3.5% 6.2% 0.0% 6.8% None of the above 0.0% 1.2% 4.3% 0.0% 2.0% 0.0% 1.2% 6.6% 7.7% 3.2% 11.5% 16.3% 31.3% 23.1% 20.9% ST 9. Q46. What are your target insect pests? Select all that apply. Target insect pests % of respondents by region SE MS SW FW Thrips 69.5% 75.2% 66.7% 64.0% Aphids 48.7% 53.5% 59.3% 64.0% Stink Bugs 87.3% 49.6% 28.7% 32.0% Plant Bugs 61.8% 86.1% 14.8% 24.0% Cotton Fleahopper 3.6% 7.0% 59.0% 12.0% Bollworm/Budworm 28.4% 37.2% 23.8% 4.0% Spider Mites 21.8% 46.5% 13.9% 40.0% Grasshoppers 19.6% 5.4% 25.3% 8.0% Fall Armyworm 13.1% 14.0% 10.8% 0.0% Lygus 6.6% 10.9% 2.0% 56.0% Boll Weevil 8.0% 10.9% 10.5% 4.0% Cutworms 6.2% 19.4% 6.8% 12.0% Beet Armyworm 6.9% 7.8% 9.0% 4.0% Loopers 9.8% 5.4% 2.2% 0.0% Banded Winged Whitefly 8.0% 0.8% 2.5% 20.0% Pink Bollworm 5.1% 6.2% 2.5% 12.0% Silverleaf Whitefly (Bemesia) 6.9% 0.8% 1.9% 16.0% Southern Armyworms 4.4% 3.9% 2.5% 0.0% Cotton Leaf Perforator 1.5% 1.6% 1.9% 4.0% European Cornborer 1.8% 0.8% 0.3% 0.0% Saltmarsh Catepillars 0.7% 2.3% 0.3% 4.0% Other 0.0% 0.0% 1.5% 4.0% ST 10. Q47. What are your target pathogens? Select all that apply. Target pathogens % of respondents by region SE MS SW FW Boll rots (Hard lock) 60.7% 58.1% 17.0% 20.0% Seedling disease 32.7% 39.5% 35.8% 20.0% Root-knot nematode 36.4% 27.9% 25.6% 20.0% Verticillium wilt 11.3% 20.9% 39.8% 68.0% Target spot 34.9% 31.0% 4.0% 0.0% Reniform nematode 25.1% 16.3% 8.0% 4.0% Alternaria leaf spot 12.7% 7.0% 6.5% 8.0% Fusarium (FOV), other than FOV Race 4 (FOV 4) 7.6% 6.2% 9.3% 12.0% Areolate mildew (Grey mold, Ramularia) 16.7% 2.3% 1.5% 0.0% Other diseases 2.9% 1.6% 8.6% 12.0% Ascochyta blight (wet weather blight) 4.4% 4.7% 4.6% 0.0% Stemphylium leaf spot 9.5% 1.6% 0.6% 0.0% Cercospora leaf spot 6.6% 1.6% 2.8% 0.0% Fusarium Race 4 (FOV 4) 2.2% 1.6% 2.8% 20.0% Cotton leaf roll dwarf virus 6.6% 7.0% 2.5% 4.0% Z40819_FINAL_23728_Bayramova_PBMKD_Sustainable_Cotton.pdf Appendix_1 revised for final Appendix 2 revised