Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 8534-8544 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: jreyna@unheval.edu.pe Simulation of blueberry production in Lambayeque, Peru: An agent-based approach Julissa Elizabeth Reyna-González1*, Andy Williams Chamoli Falcon2, Luis Vladimir Urrelo Huiman3, Marco Alberto Suárez Pozo4, Yamileé Melissa Cáceres Vilca5 1,4Universidad Nacional Hermilio Valdizán-Huánuco, Peru; jreyna@unheval.edu.pe (J.E.R.G.) msuarez@unheval.edu.pe (M.A.S.P.) 2,5Universidad Tecnológica del Perú, Lima, Peru; chamoliss@hotmail.com (A.W.C.F.) c25202@utp.edu.pe (Y.M.C.V.) 3Universidad Privada Antenor Orrego – Trujillo, Perú; lurreloh@upao.edu.pe (L.V.U.H.) Abstract: This study presents an agent-based simulation to analyze and optimize blueberry production in Lambayeque, Peru. Using data [1]and various academic sources, a model was developed on the NetLogo platform. This model simulates the interactions between climatic, agronomic and logistical factors that affect the production and export of blueberries. The results suggest that the implementation of advanced technologies and optimized agricultural practices can significantly improve the efficiency and competitiveness of Peruvian producers in the global market. Simulation offers a valuable tool for making informed decisions in the agro-export sector. Keywords: Agent-based simulation, Agricultural technology, Agroexport, Blueberry production, Lambayeque. 1. Introduction The blueberry supply chain in Peru is at a crucial stage of development, where the incorporation of good management and production practices is essential to increase the competitiveness of companies. Various studies have highlighted the importance of improving these practices to boost the long-term growth of small businesses in the sector. (Ramos, Espichan, Rodriguez, Lo, & Wu, 2018)emphasize the need to integrate and efficiently execute the blueberry supply chain in Peru to improve its competitiveness in the global market. In addition, (Escalante Yaulilahua, Olivera Recuay, Miranda Galván, & Venegas Rodríguez,, Sector Agroexportador Peruano: un Estudio de Competitividad de sus Principales Productos en el Período 2010-2019, 2023)they highlight that Peruvian agro-export products, such as blueberries, have shown a high level of specialization and competitiveness compared to other Latin American countries, particularly in the period before the pandemic and the energy crisis. (Viera, Huanca, Trujillo, & Fernández, 2023)analyze the impact of green logistics as a strategy for agro-export companies in the Lambayeque region, Peru, concluding that the implementation of sustainable practices not only improves customer perception and the company's image, but also optimizes costs and increases profits. earnings. (Chaman-Cortez, Palomino-Encarnación, Perez-Paredes, Alvarez, & Raymundo-Ibañez, 2019)present a precision agriculture model that incorporates advanced technologies and management tools to improve the production of exportable blueberries, emphasizing the importance of adaptation to change and risk assessment in agricultural companies in the coastal regions of Peru. Regarding blueberry production in the northern region of Peru, particularly in Lambayeque, it has experienced significant growth due to high international demand and favorable climatic conditions. According to the National Institute of Statistics and Informatics (INEI), blueberry production in 2022 reached 42,040 tons, with 59% of exports directed to the United States (Parraga-Arotinco, Cárdenas- Martinez, & Vilchez-Baca, 2023). This growth in blueberry production and export highlights the importance of implementing advanced technologies to improve efficiency and quality in post-harvest processing. 8535 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate One of the most relevant technological innovations in this context is the development of automated systems for the classification of blueberries. (Parraga-Arotinco, Cárdenas-Martinez, & Vilchez-Baca, 2023)have designed an automated system that classifies blueberries by size and degree of maturity, using tools such as Factory IO and TIA PORTAL connected to an S7-1200 PLC. This system not only allows for accurate sorting, but also improves operational efficiency, demonstrating the potential of automation in agribusiness. Technological innovations, the dynamics of the international blueberry market have been the subject of detailed studies. (Soto-Caro, Wu, Xia, & Guan, 2023)investigated the impact of increasing blueberry imports on the US market, concluding that a significant increase in imports from Mexico could negatively affect domestic production in the United States. This analysis highlights the importance of understanding global market interactions to maintain the competitiveness of Peruvian producers. Pollination is another critical factor for optimal blueberry production. (Ramírez-Mejía, y otros, 2024)identified optimal pollination thresholds that maximize fruit diameter, demonstrating that both deficiency and excess of pollination can affect fruit quality. These findings provide a basis for more precise pollination management, which can translate into significant improvements in blueberry yields and quality. The ability of farmers to adapt to climate change and the livelihood strategies they employ are essential for the sustainability of agricultural production. (Lan, Song, Li, & Liu, 2023)investigated how different livelihood strategies affect farmers' sensitivity to climate change, highlighting that diversification, commercialization and ecological sustainability are key to mitigating associated risks. (Montoya, María, Llatas, & del Pilar Pintado Damian, 2023)analyzes the survival of agro-export companies in the department of Lambayeque, Peru, during the period 2013-2022. The main objective is to understand the challenges that companies face when entering the international market. The findings reveal a high business mortality rate. Around 50% of companies leave the market during their first year, and only 4% manage to survive after 10 years and even more so at this time of the pandemic that affects many express producers . This study proposes an agent-based simulation to analyze and optimize blueberry production in Lambayeque. Through this simulation, we seek to better understand the interactions between various factors that affect production and export, providing valuable information for farmers, exporters and policy makers. The implementation of these technologies and strategies can improve the competitiveness of Peruvian producers in the global market. 2. Method 2.1. Research Design The research design was based on a quantitative approach (Dugheri, y otros, 2022), using data obtained (Moore Morey & Rogger O. , 2023)and other relevant academic articles. The methodology followed a structure that included data collection, analysis of this data, development of an agent-based simulation model, and model validation (Yakimenk, Zhertovskaja, Gorelova, & Pshenichnykh, 2018). 2.2. Investigation Procedure 2.2.1. Data Collection 2.2.1.1. Data Sources: Lambayeque Export Statistical Bulletin (January-February 2023): Provided data on exported value, exported quantity, destination markets and companies exporting blueberries and other agricultural products. Promperú and Infotrade: Provided additional data on foreign trade and export statistics. Scientific Articles: Data on agricultural practices, climatic and logistical effects on the production and export of blueberries. 2.3. Specifications of the Data Collected Climate: Temperature, precipitation and relative humidity. Soil: Composition, water and nutrient retention capacity. 8536 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate Agronomic : Blueberry varieties, agricultural practices (irrigation, fertilization) and historical yields. Logistics: Storage capacity, transportation routes, shipping times and costs. 2.4. Data Analysis The analysis of the collected data involved the use of statistical and simulation tools to identify patterns and trends in the production and export of blueberries in Lambayeque (Flores, Aranibar-Molina, Palomino-Peralta, & Soto-Palomino, 2023). 2.5. Analysis Method Descriptive Analysis: Identification of trends and patterns. Regression and Correlation Analysis: To understand the relationships between climatic, agronomic and logistical variables. Time Series Analysis: To predict future trends in production and export. 2.6. Modeling and Simulation 2.6.1. Definition of Agents • Blueberry Plants: They represent individual production units that grow and develop depending on climatic conditions and agricultural practices. • Climate: Daily variables that affect the growth and development of plants. • Soil: Dynamic characteristics that influence water and nutrient retention. • Farmers: Implement specific agricultural practices . • Climate: Daily variables that affect the growth and development of plants. • Logistics: Storage, transportation and export processes. 2.6.2. Daily Simulation • Climatic Conditions: Update on temperature, precipitation and relative humidity. Formula for Evapotranspiration ( ETc ): 𝐸𝑇𝑐 = 𝐸𝑇0𝑥 𝐾𝑐 Where: • 𝐸𝑇𝑐= Crop evapotranspiration. • 𝐸𝑇0 = Reference evapotranspiration. • 𝐾𝑐= Crop coefficient. Formula for Soil Water Balance: 𝛥𝑊 = 𝑃 − 𝐸𝑇𝑐 − 𝐷 − 𝑅 Where: • 𝛥𝑊= Change in soil water content. • P = Precipitation • 𝐸𝑇𝑐= Crop evapotranspiration. • D = Deep drainage. • R = Surface runoff. • Plant growth: Evaluation of vegetative growth and fruit development based on climatic conditions and agricultural practices. 8537 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate 𝑷(𝒕) = 𝑲 𝟏 + ( 𝒌−𝑃𝑜 𝑃𝑜 )𝒆−𝒓𝒕 Where: • P(t) = Blueberry production at time t. • K = Load capacity (maximum possible production). • 𝑃𝑜= Initial production. • r = Growth rate. • t = Time. • Agricultural Practices : Application of irrigation, fertilization and pest control according to the established calendar. Formula for Soil Water Balance: 𝑁(𝑡) = 𝑁𝑜 − (𝑁𝑎𝑝𝑙𝑖𝑐𝑎𝑑𝑜𝑥 𝐹) Where: • 𝑁(𝑡)= Level of nutrients in the soil at time t. • 𝑁𝑜= Initial level of nutrients. • 𝑁𝑎𝑝𝑙𝑖𝑐𝑎𝑑𝑜= Amount of nutrients applied. • 𝐹= Fertilization efficiency. • Production Monitoring: Recording of daily fruit production and updating of soil resources. Crop Yield Formula 𝑌 = 𝑃𝑥𝐴 Where: • 𝑌= Total crop yield. • 𝑃= Production per unit area. • 𝐴= Total cultivated area. - Formula for harvest index 𝐻𝐼 = 𝑊𝑓 𝑊𝑡 Where: • 𝐻𝐼= Harvest index. • 𝑊𝑓= Weight of harvested fruits. • 𝑊𝑡= Total weight of the plant biomass. 2.6.3. Harvest and Logistics • Harvesting blueberries on harvest days. • Preparation for export, including storage and transportation. • Evaluation of logistics times and costs, and registration of export data. 8538 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate 2.6.4. Implementation in Netlogo NetLogo platform , an agent-based simulation model was developed that represents the components and dynamics of the blueberry production system in Lambayeque (Walker & Johnson, 2019). This approach allows us to simulate interactions between different agents of complex agricultural systems (Aqib & Ukil, 2020), such as blueberry plants, climatic conditions, soil and management practices. Initialization: Configuration of climatic agents, soils and plants with historical data and predictions. Daily Cycle: Update of climatic variables, plant growth, application of agricultural practices, and logistics management. Validation: Comparison of simulated results with real data, parameter adjustment, and evaluation under different scenarios. 2.7. Model Validation The validation of the model was carried out by comparing the simulation results with data collected from 2023 on blueberry production and export in Lambayeque. Statistical techniques were used to verify the accuracy of the model and necessary adjustments were made to improve its reliability (González, Campano, & López, 2018). Comparisons were made between the results of the simulation model and the actual production data obtained from the region. Cross-validation techniques were used to ensure the robustness of the model (Echávarri, y otros, 2018). Model calibration was carried out by adjusting the parameters until the model predictions agreed with the empirical observations. (Albayrak & Özdemir, 2018) 2.7.1. Soil Data Data were collected on soil quality, composition and water retention capacity. 2.7.1.1. Agricultural Practices Local agricultural practices, including irrigation, fertilization, and pest management, were documented through interviews with local producers and literature review. 2.7.1.2. Production Data Recent blueberry production and export statistics were obtained (Moore Morey & Rogger O. , 2023). 8539 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate Figure 1. 3. Results and Discussion • The blue dots represent blueberry plants in the initial stage of growth. This is the stage in which the plants are planted or transplanted and have not yet begun their significant vegetative development. • The purple dots represent blueberry plants in the vegetative stage. At this stage, the plants are undergoing active growth of stems, leaves and roots, but have not yet reached the flowering stage. • White dots represent blueberry plants in the flowering stage. At this stage, the plants have produced flowers and are ready for pollination and fruit development. • The red dots represent blueberry plants in the fruiting stage. At this stage, the plants have been successfully pollinated and are producing fruit (blueberries). • The yellow dots represent blueberry plants with low health. This can be caused by various factors, such as adverse environmental conditions (inappropriate temperature or precipitation), presence of pests or diseases, or lack of nutrients in the soil. • The orange dots represent blueberry plants in critical or near-death health. These plants are experiencing significant decline and are likely to die if conditions do not improve. 8540 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate Figure 2. Figure 3. 8541 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate Figure 4. 3.1. Results Production: The "Total Production Over Time" graph shows that total blueberry production increases over time, which is expected as blueberry plants mature and reach their fruiting stage as time passes. Total Exports: The "Total Export " graph Over Time" shows a sudden increase in total exports, suggesting that once plants reach the fruiting stage, production goes largely to export. export - value ", "NL- export - value ", "UK- export - value " and "EC- export - value " monitors show the export values for each market according to market shares. established market. These values reflect the distribution of total exports between the different target markets. Plant Health: The “Average Health Monitor” monitor displays a numerical value that represents the average health of blueberry plants. This value can be used to evaluate the impact of environmental factors and pests on plant quality and, therefore, production. 3.2. Discussion The simulation model captures several important aspects of blueberry cultivation and export, such as plant growth, production, environmental factors and market shares. The results suggest that production and exports increase over time, but also depend on plant health, which in turn is influenced by factors such as temperature, precipitation and pests. One of the strengths of the model is its ability to simulate different scenarios by varying initial parameters, such as market shares, export prices and costs. This allows researchers and decision makers to explore different strategies and evaluate their impact on production and export earnings. 4. Conclusion • The blueberry production simulation model in NetLogo provides a useful representation of the key processes involved in growing and exporting blueberries, including plant growth, production, environmental factors and market shares. 8542 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate • Model results suggest that blueberry production and exports increase over time, but are influenced by plant health, which in turn depends on factors such as temperature, precipitation and pests. • The model allows exploring different scenarios by varying the initial parameters, which can be valuable to evaluate strategies and make informed decisions in the blueberry production and export sector. • While the model provides a useful overview, it is important to note its limitations and consider incorporating additional factors to obtain a more complete and accurate representation of reality. • The results and conclusions of the model can be used as a basis for future research, policy development or decision-making in the blueberry production and export sector, as long as its limitations are considered and complemented with other approaches and sources of information. Copyright: © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] Anselmo Moore Morey and Moran Santamaria Rogger O. (2023, August) Statistical Bulletin of Lambayeque Exports - January/February 2023. [Online]. https://cdn.www.gob.pe/uploads/document/file/5238683/BOLET%C3%8DN%20ENERO%20A%20FEBRERO%2 02023.pdf?v=1696610835 [2] Edgar Ramos, Karen Espichan, Kerly Rodriguez, Wei-Shuo Lo, and Zilin Wu, "Blueberry supply chain in Perú: Planning, integration and execution," International Journal of Supply Chain Management , vol. 7, no. 2, p. 12, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85046372753&origin=resultslist&sort=plf- f&src=s&sid=82df3a626831a181488a8002f70f6a67&sot=b&sdt=b&s=TITLE-ABS-KEY%28Blueberry+suppl y+ chain+in+Per%C3%BA%3A+Planning%2C+integration+and+execution%29&sl=82&s [3] Danton Arturo Escalante Yaulilahua, Jimena Melissa Olivera Recuay, Mayte Rocio Miranda Galván, and Pedro Bernabé Venegas Rodríguez, "Peruvian Agro-Export Sector: a Study of the Competitiveness of its Main Products in the Period 2010-2019," Journal Globalization, Competitiveness and Governability , vol . 17, no. 2, p. 50, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85160819601&origin=scopusAI [4] Paola Patricia Candiotti Viera, Leunela Hurtado Huanca, Pablo-Alfredo Rituay Trujillo, and Francisco Eduardo Cúneo Fernández, "Green logistics as a strategy for agro-export companies in the Lambayeque-Peru region," Revista de Ciencias Sociales , p. 65, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85165490926&origin=resultslist&sort=plf- f&src=s&sid=0c914d8562bfb98869a14d1d62d8d394&sot=b&sdt=b&s=TITLE-ABS-KEY%28Green+logistics + as+a+strategy+for+agro-export+companies+in+the+Lambayeque-Peru+region%2 [5] Carlos Chaman-Cortez, Adrian Palomino-Encarnación, Maribel Perez-Paredes, Jose Maria Alvarez, and Carlos Raymundo-Ibañez, "Precision farming model to increase the production of exportable blueberries by implementing an adapting-to-change approach and risk assessment in agribusinesses in Peru's coastal regions," ACM International Conference Proceeding Series , p. 255, September 2019. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85076675238&origin=resultslist&sort=plf- f&src=s&sid=f62298f4eb1e0e0adb50a1f0ae99e9c2&sot=b&sdt=b&s=TITLE-ABS-KEY%28Precision+farming+ model+to+increase+the+production+of+exportable+blueberries+by+impleme [6] Eduardo Antony Parraga-Arotinco, Rosmeri Pilar Cárdenas-Martinez, and Herbert Antonio Vilchez-Baca, "Automated System for Sorting Blueberries by Size and Degree of Ripeness," Proceedings - 2023 6th International Conference on Control, Robotics and Informatics, ICCRI 2023 , p . 80, May 2023. [Online]. https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85186534188&doi=10.1109%2fICCRI58865.2023.00021&partnerID=40&md5=79ce85e76f8ee0e001a8f2aa4b981c15 [7] Ariel Soto-Caro, Feng Wu, Tian Xia, and Zhengfei Guan, “Demand analysis with structural changes: Model and application to the US blueberry market,” Agribusiness , vol. 39, no. 4, p. 1116, 2023. [Online]. https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85153607172&doi=10.1002%2fagr.21815&partnerID=40&md5=eede605c47716799a5cc4b0bacd8fef3 [8] Andrés F. Ramírez-Mejía et al., "Optimal pollination thresholds to maximize blueberry production," Agriculture, Ecosystems and Environment , vol. 365, p. 9, May 2024. [Online]. https://www.scopus.com/inward/record.uri?eid=2- s2.0-85184042184&doi=10.1016%2fj.agee.2024.108903&partnerID=40&md5=9ed626bcf8ecced65c89bb139e495d0a [9] Jing Lan, Biqing Song, Qiuming Li, and Zhen Liu, "Farmers' livelihood strategies and sensitivity to climate change: Evidence from southwest China," Indoor and Built Environment , vol. 32, no. 8, p. 1561, 2023. [Online]. https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85130504151&doi=10.1177%2f1420326X221097065&partnerID=40&md5=d69ed0a2d79009f064e7f7d3f5a25087 https://creativecommons.org/licenses/by/4.0/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153607172&doi=10.1002%2fagr.21815&partnerID=40&md5=eede605c47716799a5cc4b0bacd8fef3 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153607172&doi=10.1002%2fagr.21815&partnerID=40&md5=eede605c47716799a5cc4b0bacd8fef3 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184042184&doi=10.1016%2fj.agee.2024.108903&partnerID=40&md5=9ed626bcf8ecced65c89bb139e495d0a https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184042184&doi=10.1016%2fj.agee.2024.108903&partnerID=40&md5=9ed626bcf8ecced65c89bb139e495d0a https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130504151&doi=10.1177%2f1420326X221097065&partnerID=40&md5=d69ed0a2d79009f064e7f7d3f5a25087 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130504151&doi=10.1177%2f1420326X221097065&partnerID=40&md5=d69ed0a2d79009f064e7f7d3f5a25087 8543 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate [10] Katherin Vanessa Carrasco Montoya, Alberto Luis Pantaleón Santa María, Flor Delicia Heredia Llatas, and Mónica del Pilar Pintado Damian, "Survival of Agro-exporting Companies in the Lambayeque Department, Peru, 2013-2022," Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology , p. 50, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85187301289&origin=scopusAI [11] Stefano Dugheri et al., "Quantitative Occupational Exposure Risk," Stanislav Kovshov , vol. 8, no. 32, p. 20, 2022. [Online]. https://doi.org/10.3390/safety8020032 [12] Marianna Yakimenk, Elena Zhertovskaja, Galina Gorelova, and Yulia Pshenichnykh, "Elaboration of the system of indicators for the territorial tourist potential evaluation based on the cluster approach to tourism development," Espacios , vol. 39, no. 36, p. 15, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85054085172&origin=scopusAI [13] Edward Flores, Anabel Aranibar-Molina, Carmen Palomino-Peralta, and Wilfredo Soto-Palomino, "Blueberry cultivation venture in Peru for national and international commercialization," Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology , p. 150, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85187250490&origin=scopusAI [14] Broday Walker and Tina V. Johnson, "Netlogo and GIS: A powerful combination," Proceedings of 34th International Conference on Computers and Their Applications, CATA 2019 , p. 264, March 2019. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85078030853&origin=scopusAI [15] Muhammad Aqib and Abhisek Ukil, "Modelling of electric vehicle charging and discharging profile to mimic real life scenarios at charging stations," IEEE Region 10 Annual International Conference, Proceedings/TENCON , p. 505, 2020. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85098942244&origin=scopusAI [16] Medardo Aguirre González, Claudio Candia Campano, and Lilliam Antón López, "A gravity model of trade for Nicaraguan agricultural exports," Cuadernos de Economia (Colombia) , vol. 37, no. 74, p. 391, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85056668091&origin=scopusAI [17] Orietta Echávarri et al., "Validation of the reasons for living inventory in mental health patients in the Metropolitan Region of Chile," Psykhe , vol. 27, no. 2, p. 10, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85058145322&origin=scopusAI [18] Gülçağ Albayrak and Ilker Özdemir, "Multimodal optimization for time-cost trade-off in construction projects using a novel hybrid method based on FA and PSO," Revista de la Construccion , vol. 17, no. 2, p. 218, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85052557864&origin=scopusAI [19] Danton Arturo Escalante Yaulilahua, Jimena Melissa Olivera Recuay, Mayte Rocio Miranda Galván, and Pedro Bernabé Venegas Rodríguez, "Peruvian Agro-Export Sector: a Competitiveness Study on Their Main Products in the Period 2010-2019," Journal Globalization, Competitiveness and Governability , vol. 17, no. 2, p. 50, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85160819601&origin=resultslist&sort=plf- f&src=s&sid=82df3a626831a181488a8002f70f6a67&sot=b&sdt=b&s=TITLE-ABS-KEY%28Peruvian+ Agro- Export+Sector%3A+a+Competitiveness+Study+on+Their+Main+Products+in+the+Pe [20] Oleksandr Mialyk et al., “Water footprints and crop water use of 175 individual crops for 1990–2019 simulated with a global crop model,” Scientific Data , vol. 11, no. 1, p. 16, December 2024. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85185343139&origin=resultslist&sort=plf- f&src=s&sid=8ab74817d12a871602e609cf36a7d166&sot=b&sdt=b&s=TITLE-ABS-KEY%28Water+footprints+ and+crop+water+use+of+175+individual+crops+for+1990%E2%80%932019+simul [21] Jan C. Thiele, “R Marries NetLogo: Introduction to the RNetLogo Package,” Journal of Statistical Software , vol. 58, no. 2, p. 41, 2014. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-84944313980&origin=scopusAI [22] Maria Florencia Degano et al., "Analysis of Priestley-Taylor method in different environments and coverages," 2021 19th Workshop on Information Processing and Control, RPIC 2021 , p. 20, 2021. [Online].https://www.scopus.com/record/display.uri?eid=2-s2.0-85124155794&origin=scopusAI [23] Pieter H. Groenevelt, "Thermodynamics of soil water," Encyclopedia of Soils in the Environment, Second Edition , vol. 5, no. 262,270, p. 60, 2023. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85191922268&origin=scopusAI [24] Jose Leal-Almanza et al., "Vegetable growth promoter microorganisms with agricultural plaster on potatoes (solanum tuberosum l.) under shadow housing," Agrociencia , vol. 52, no. 8, p. 1159, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85058541181&origin=scopusAI [25] Maysoun A. Mustafa, Kumbirai I. Mateva, and Festo Massawe, "Sustainable crop production for environmental and human health - the future of agriculture," Annual Plant Reviews Online , vol. 2, no. 4, p. 1140, 2019. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85109789471&origin=scopusAI [26] Marcio Funchal, "Market indicators for the forestry asset producer," O Papel , vol. 84, no. 3, p. 32, 2023. [Online].https://www.scopus.com/record/display.uri?eid=2-s2.0-85163856198&origin=scopusAI [27] E. L. Goud, J. Singh, and P. Kumar, "Climate change and its impact on global food production," Microbiome under a changing climate: implications and solutions , p. 436, 2022. [Online]. https://www.scopus.com/record/display.uri?eid=2- s2.0-85129793196&origin=scopusAI [28] Shichao Chen et al., "Quantifying the effects of spatial-temporal variability of soil properties on crop growth in management zones within an irrigated maize field in Northwest China," Agricultural Water Management , vol. 244, no. 1, p. 70, 2021. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85187301289&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85054085172&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85054085172&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85078030853&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85098942244&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85056668091&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85058145322&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85058145322&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85052557864&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85160819601&origin=resultslist&sort=plf-f&src=s&sid=82df3a626831a181488a8002f70f6a67&sot=b&sdt=b&s=TITLE-ABS-KEY%28Peruvian+Agro-Export+Sector%3A+a+Competitiveness+Study+on+Their+Main+Products+in+the+Pe https://www.scopus.com/record/display.uri?eid=2-s2.0-85160819601&origin=resultslist&sort=plf-f&src=s&sid=82df3a626831a181488a8002f70f6a67&sot=b&sdt=b&s=TITLE-ABS-KEY%28Peruvian+Agro-Export+Sector%3A+a+Competitiveness+Study+on+Their+Main+Products+in+the+Pe https://www.scopus.com/record/display.uri?eid=2-s2.0-85160819601&origin=resultslist&sort=plf-f&src=s&sid=82df3a626831a181488a8002f70f6a67&sot=b&sdt=b&s=TITLE-ABS-KEY%28Peruvian+Agro-Export+Sector%3A+a+Competitiveness+Study+on+Their+Main+Products+in+the+Pe https://www.scopus.com/record/display.uri?eid=2-s2.0-85185343139&origin=resultslist&sort=plf-f&src=s&sid=8ab74817d12a871602e609cf36a7d166&sot=b&sdt=b&s=TITLE-ABS-KEY%28Water+footprints+and+crop+water+use+of+175+individual+crops+for+1990%E2%80%932019+simul https://www.scopus.com/record/display.uri?eid=2-s2.0-85185343139&origin=resultslist&sort=plf-f&src=s&sid=8ab74817d12a871602e609cf36a7d166&sot=b&sdt=b&s=TITLE-ABS-KEY%28Water+footprints+and+crop+water+use+of+175+individual+crops+for+1990%E2%80%932019+simul https://www.scopus.com/record/display.uri?eid=2-s2.0-85185343139&origin=resultslist&sort=plf-f&src=s&sid=8ab74817d12a871602e609cf36a7d166&sot=b&sdt=b&s=TITLE-ABS-KEY%28Water+footprints+and+crop+water+use+of+175+individual+crops+for+1990%E2%80%932019+simul https://www.scopus.com/record/display.uri?eid=2-s2.0-84944313980&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85191922268&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85191922268&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85058541181&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85129793196&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85129793196&origin=scopusAI 8544 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8534-8544, 2024 DOI: 10.55214/25768484.v8i6.3827 © 2024 by the authors; licensee Learning Gate https://www.scopus.com/record/display.uri?eid=2-s2.0-85091740899&origin=scopusAI [29] Fehr WR, "Genetic contributions to yield gains of five major crop plants," Genetic Contributions to Yield Gains of Five Major Crop Plants , p. 101, 2015. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85027555582&origin=scopusAI [30] Schipanski ME et al., "Multivariate relationships influencing crop yields during the transition to organic management," Agriculture, Ecosystems and Environment , p. 126, 2014. [Online]. https://www.scopus.com/record/display.uri?eid=2- s2.0-84897937341&origin=scopusAI [31] Alvaro Moreno Ramírez, Jorge García Regalado, and Sunny Giler Sánchez, "Evolution of Ecuador's small private banking and its projections based on the new productive matrix," Espacios , vol. 39, p. 41, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85055945830&origin=scopusAI [32] Técia Maria Santos Carneiro e Cordeiro, Tânia Maria de Araújo, and Kionna Oliveira Bernardes Santos, "Exploratory study of the validity and internal consistency of the Work Ability Index among health workers," Salud Colectiva , vol. 14, no. 4, p. 724, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85059257540&origin=scopusAI [33] Ariel S. Loyarte, Luis A. Clementi, and Jorge R. Vega, "Assignment of Maximum Non-Manageable Power in an Electric Grid with Quality Constraints," 2018 IEEE Biennial Congress of Argentina, ARGENCON 2018 , p. 230, July 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0-85063542203&origin=scopusAI [34] Danylo I. Kuropiatnyk, "Actuality of the problem of parametric identification of a mathematical model," CEUR Workshop Proceedings , p. 75, 2018. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 85060062349&origin=scopusAI [35] Leonardo Vera, René Montalba, Lorena Vieli, Emili Jorquera, and Isabel González, "Methodology to determine the suitability of land for the cultivation of tall blueberries: A case study on a farm in southern Chile," Ciencia e Investigacion Agraria , vol . 42, no. 3, p. 364, 2015. [Online]. https://www.scopus.com/record/display.uri?eid=2-s2.0- 84981745030&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85027555582&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85027555582&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-84897937341&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-84897937341&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85059257540&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85059257540&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85063542203&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85060062349&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-85060062349&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-84981745030&origin=scopusAI https://www.scopus.com/record/display.uri?eid=2-s2.0-84981745030&origin=scopusAI