1 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 Research on World Agricultural Economy https://ojs.nassg.org/index.php/rwae Copyright © 2022 by the author(s). Published by NanYang Academy of Sciences Pte. Ltd. This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. (https://creativecommons.org/licenses/by-nc/4.0/). DOI: http://dx.doi.org/10.36956/rwae.v3i1.482 Received: 12 January 2022; Received in revised form: 14 February 2022; Accepted: 22 February 2022; Published: 4 March 2022 Citation: Guo, S.J., Li, S.J., Huang, G.Q., 2022. Effects of Different Intercropping Models on Growth and Yield Traits of Maize in Red Soil Dryland. Research on World Agricultural Economy. 3(1), 482. http://dx.doi.org/10.36956/rwae.v3i1.482 *Corresponding Author: Guoqin Huang, Ecological Science Research Center, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China; Email: hgqjxes@sina.com RESEARCH ARTICLE Effects of Different Intercropping Models on Growth and Yield Traits of Maize in Red Soil Dryland Shujian Guo Shujuan Li Guoqin Huang* Ecological Science Research Center, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China Abstract: In order to develop the suitable planting mode of maize in red soil dryland, improve the related plant and ear characters of maize, promote high quality and high yield, and improve economic benefits. The experiment was conducted in the Science and Technology Park of Jiangxi Agricultural University from May 13, 2020 to October 18, 2020 and from May 5, 2021 to October 7, 2021. Taking maize as the control, three intercropping treatments of maize intercropping soybean, maize intercropping peanut and maize intercropping sweet potato were set up to compare their effects on agronomic characters such as plant height, stem diameter and ear width of maize and yield. The results showed that the plant height and ear height of maize intercropping soybean reached the maximum in two years, with plant height of 208.9 cm and 191.9 cm, ear height of 80.2 cm and 58.4 cm, respectively. The ear length and grain number per row of intercropping treatment were better than that of monoculture treatment. The ear length of maize intercropping and soybean reached the maximum, which were 16.5 cm and 19.0 cm respectively, and the grain number per row was also higher than that of other treatments. The yield of maize intercropping soybean was the highest, 42.1 kg and 43.5 kg respectively in two years. Compared with monoculture, intercropping can improve stem diameter, ear height, ear length, grain number per row and other ear traits, so as to improve corn yield, among which maize intercropping soybean is the best. The results of grey correlation showed that ear length and plant height had a great influence on maize yield. The comprehensive analysis shows that the use of maize intercropping soybean model is conducive to achieve high quality and high yield. Keywords: Red soil dryland; Intercropping models; Maize; Agronomic characters; Yield 1. Introduction Maize is the main food crop, as well as an important fodder and economic crop, and it occupies an impor- tant position in agricultural production and the national economy. Its quality and output also directly affect the development of food security and agricultural production in my country and the world [1]. The dry land in southern my country is dominated by red dry land. The southern red soil area has a tropical and subtropical climate with a long frost-free period, concentrated rain, abundant water, light and heat resources, superior natural conditions, and huge production potential [2], but for a long time, due to 2 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 the existence of various production limiting factors such as acid, thinness, stickiness, drought, erosion, etc., cou- pled with extensive cultivation and unreasonable devel- opment and utilization, have resulted in low productivity and poor economic benefits in red soil dryland farmland [3]. Intercropping can maximize the utilization of resources [4-6], increase production and income [7,8], increase the pro- ductivity of arable land, and effectively alleviate the con- tradiction of crop land competition [9]. Intercropping, mixing, interplanting and multiple crop- ping are widely used in maize production to make full use of soil fertility, light, heat and water resources in time and space [10]. The land equivalent ratio of intercropping maize with dwarf grain crops such as soybean, peanut and sweet potato is higher than that of monoculture, which makes full use of spatial advantages and effectively improves the dynamic leaf area coefficient and light energy utilization rate. Intercropping corn with soybean, peanut and sweet potato has significant yield increase and high economic benefit [11]. Zhang Xiangqian et al. [12] showed that the intercropping of corn with soybean, peanut and legume crops significantly increased the economic yield and bio- logical yield of corn per plant, significantly increased the economic yield in the field, and significantly improved the nutritional quality of corn grains. Chu Fengli et al. [13] con- sidered that the intercropping of sweet potato and maize has obvious yield advantages. The yield of intercropping maize is 9.76% higher than that of monoculture maize, and the land equivalent ratio of intercropping treatment is 1.12. Jiangxi is a typical area of red soil dry land, and the area of soybeans, peanuts, sweet potatoes, etc. is large, which can be used for intercropping of corn, make full use of light and heat resources, and give full play to one area for multiple purposes. Predecessors have studied corn in- tercropping soybeans [14], peanuts [15], and sweet potatoes [16,17], but there are relatively few reports comparing the effects of the three intercropping on agronomic traits and yield [18,19]. This study combines the actual production of maize in the arid regions of red soil in Jiangxi, and com- pares the characteristics of maize plants and ears, yield and other indicators under different intercropping modes, and plans to screen out the maize intercropping models suitable for planting in the drylands of red soil in Jiangxi, and make full use of land resources to promote corn qual- ity High yield, improve economic efficiency. 2. Materials and Methods 2.1 Experimental Site This experiment was carried out in the Science and Technology Park of Jiangxi Agricultural University (28°76′N, 115°84′E), where the terrain is flat, has a sub- tropical monsoon climate, and sufficient light and heat re- sources. The average annual rainfall is 2223.2 mm and the annual average temperature is 16.5 °C . The experimental field soil is a typical red loam, and the soil is slightly acidic. Before the experiment, the basic nutrient status of the soil was basically the same, and the plots were equally and randomly arranged. The initial soil properties of the experiment were: pH 4.68, total nitrogen 0.129%, available phosphorus 62.27 mg·kg-1, available potassium 98.79 mg·kg-1, organic matter 26.50 g·kg-1, and alkali hy- drolyzed nitrogen 100.00 mg·kg-1. 2.2 Experimental Design In this study, a randomized complete block design was adopted, and a total of 4 treatments were designed, maize monoculture (T1) control, maize intercropping soybean (T2), maize intercropping peanut (T3), maize intercrop- ping sweet potato (T4). Three repetitions are set for each treatment, with a total of 12 plots, with a length of 6m, a width of 5.5 m and a plot area of 33.0 m2. The corn variety is Ganxinnuo 7, the soybean variety is 75-3, the peanut variety is Huagan 1, and the sweet potato variety is Guangshu 87, which is purchased by Nanchang seed store. The row spacing between corn and corn is 35 cm, and the row spacing between soybean and soybean, pea- nut and sweet potato and sweet potato is 30 cm. The row spacing of beans, peanuts, sweet potatoes and corn was 50 cm. The three intercropping treatments were 2 rows of corn, 2 rows of soybean, 2 rows of peanut and 2 rows of sweet potato. The plant spacing of corn, soybean, peanut and sweet potato was 25 cm. The row spacing of maize in monoculture is 35 cm, the plant spacing is 25 cm, and the spacing between two rows of maize is 130 cm. The density of corn per unit area (667 m2) is 3880 plants, and the density of soybean, peanut and sweet potato is 2910 plants. 2.3 Field Management Corn, soybean, peanut and sweet potato sowed on May 13, 2020 and May 5, 2021 respectively. In 2020, corn and soybean harvested on August 5, peanut on September 6 and sweet potato on October 18. In 2021, corn and soy- beans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/ hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, 3 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potas- sium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potas- sium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/ hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis For maize agronomic traits under different intercrop- ping patterns, plant height (X1), stem thickness (X2), ear height (X3), ear length (X4), ear thickness (X5), bald tip length (X6), ear row number ( X7), the number of grains in a row (X8), and the output (X0) are analyzed for cor- relation. First determine the sequence and perform dimension- less processing, and then use Excel 2019 software to cal- culate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then (k) is the correlation coefficient be- tween X0 and Xi at the k-th point: 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. In the formula: 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. represents the absolute difference between the sequence of numbers and the se- quence of numbers at the k-th point, denoted as: 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. Calculate the degree of relevance: 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. Where: 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. is the second least difference, 4 6 and sweet potato on October 18. In 2021, corn and soybeans harvested on July 29, peanuts on August 30 and sweet potatoes on October 7. Base fertilizer: 1500 kg/hm2 organic fertilizer, pure potassium sulfate (15-15-15) compound fertilizer 750 kg/hm2, sowing in furrows after spreading. Urea 55 kg/hm2 was applied at jointing stage of maize and 135 kg/hm2 at heading stage. Urea 45 kg/hm2, potassium chloride 90 kg/hm2, urea 30 kg/hm2 and potassium chloride 75 kg/hm2 were applied at branching stage of soybean combined with intercropping. Urea and potassium chloride 45 kg/hm2 were applied at seedling stage of peanut, urea 120 kg/hm2 and potassium chloride 90 kg/hm2 were applied at flowering stage. Sweet potato In the middle stage, 120 kg/hm2 urea and 75 kg/hm2 potassium sulfate were applied. Other management is the same as land for growing field crops. 2.4 Measurement Items and Methods 2.4.1 Determination of Agronomic Characters At heading stage, 10 plants were randomly selected from each plot to examine plant height, stem diameter, ear height, empty stem rate, lodging rate and tillinging rate. After harvest, 10 ears were randomly selected from each plot for ear length, ear width, rows per ear, grain number per row and bald tip length. 2.4.2 Determination of Yield At the maturity stage of corn, 10 ears were selected to measure the weight of fresh ears, and the actual yield of each plot was calculated. 2.4.3 Grey Relational Analysis First determine the sequence and perform dimensionless processing, and then use Excel 2019 software to calculate the gray correlation degree. Suppose the yield traits of maize are the reference series X0, and the agronomic traits are the comparison series Xi, i = 1, 2, 3,..., N, and X0 = {X0(1), X0(2), X0(3 ),..., X0 (N)}, Xi = {Xi (1), Xi (2), Xi(3),...Xi(N)}, then εi(k) is the correlation coefficient between X0 and Xi at the k-th point: 휀푖 = 푚푖푛푚푖푛|푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 푖 푘 |푋0(푘)−푋푖(푘)|+휌푚푎푥푚푎푥|푋0(푘)−푋푖(푘)| 푖 푘 , In the formula: |X0(k) − Xi(k)| represents the absolute difference between the sequence of numbers and the sequence of numbers at the k-th point, denoted as: ∆푖(푘) = |푋0(푘) − 푋푖(푘)|, Calculate the degree of relevance: 푟푖 = 1 푁 푘=1 푛 휀푖(푘)∑ , Where: 푚푖푛푚푖푛|푋0(푘) − 푋푖(푘)| 푖 푘 is the second least difference, 푚푎푥푚푎푥|푋0(푘) − 푋푖(푘)| 푖 푘 is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. is the second-level maximum difference, is the resolution coefficient, N is the number of samples, the value range is 0~1, and the value is 0.5. 2.5 Data Analysis Use Excel 2019 to statistically process the data and graph, use SPSS 20.0 to perform one-way analysis of vari- ance on the data, use Duncan method to perform multiple comparisons and Pearson’s two-tailed correlation analysis for each measurement data. 3. Results 3.1 Effects of Different Intercropping Models on Plant and Ear Characters of Maize 3.1.1 Plant Characters There was no significant difference between the plant height and ear height of each treatment in 2020 and 2021, but the plant height of maize intercropping soybean (T2) reached the maximum value of 208.9 cm in 2020, and the ear height of maize intercropping soybean (T2) also reached the maximum value of 80.2 cm. There was no significant difference in the stem diameter of maize inter- cropping soybean (T2), maize intercropping peanut (T3), maize intercropping sweet potato (T4) in 2020, and the stem diameter of maize monoculture (T1) was signifi- cantly lower than that of other intercropping treatments. In 2021, there was no obvious regularity in stem diam- eter, and the differences in plant traits between treatments were not obvious, maintaining good stability. However, the plant height, stem diameter, and ear position of maize intercropping soybean (T2) are as high as the maximum. The plant height is 191.9 cm, the stem diameter is 2.4 cm, and the ear position height is 58.4 cm. Under dif- ferent intercropping modes, the empty stem rate, tilling rate,lodging rate and reversal rate of corn are all 0. Taken together, there is no obvious difference in plant traits between different corn intercropping treatments, but the overall performance of the intercropping treatment is bet- ter than that of the monoculture treatment. Among them, the plant growth of maize intercropping soybean (T2) is better, and the plant height, stem diameter, and ear height are better (Table 1). 3.1.2 Ear Characters Under different intercropping modes, there is no signif- icant difference in ear width and bald tip length of maize in 2020 and 2021, and there is no obvious regularity in the 4 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 rows per ear and the grain number per row in two years. However, the ear length and the grain number per row in the two-year intercropping treatment were better than those of the monoculture treatment. Among them, the ear length of maize intercropping soybean (T2) reached the maximum, which were 16.5 cm and 19.0 cm, respectively, and the grain number per row was also higher than other treatments. In 2021, the ear width of maize intercropping soybean (T2) reached the maximum value of 4.8 cm, the length of the bald tip was the shortest, 2.4 cm, and the grain number per row was the largest, reaching 33 grains per row. The rows per ear were not obvious compared with other treatments (Table 2). Different intercropping treatments can increase the fresh fruit ear weight. The fresh fruit ear weight of maize inter- cropping soybean (T2) is the largest in two years, 219.3 g and 256.1 g respectively. According to the ear characters of two years, intercropping treatment has more advantages than monoculture treatment, and the ear characters of maize intercropping soybean (T2) are better (Figure 1). Table 1. Main plant characters under different intercropping models Year Treatment Plant height(cm) Stem diameter(cm) Ear height(cm) 2020 T1(CK) 196.4±4.4a 1.8±0.1b 70.5±5.1a T2 208.9±4.1a 2.1±0.1a 80.2±2.7a T3 208.8±5.2a 2.0±0.1ab 77.3±2.4a T4 208.4±1.9a 2.1±0.1ab 76.2±1.4a Mean 205.63 2.04 76.05 CV(%) 3.60 5.79 7.60 2021 T1(CK) 186.4±3.9a 2.2±0.1a 52.7±2.9a T2 191.9±5.5a 2.4±0.1a 58.4±4.7a T3 184.8±1.6a 2.2±0.3a 51.7±1.7a T4 186.8±2.7a 2.3±0.2a 57.7±1.3a Mean 187.48 2.28 55.13 CV(%) 3.35 6.74 8.82 Note: The data in the table of agronomic traits are the average value of three repetitions. Different lowercase letters in the same column represent the level of 0.05, with significant difference. Table 2. Main characters of ear under different intercropping models Year Treatment Ear length(cm) Ear width (cm) Bald tip length(cm) Rows per ear Grain number per row 2020 T1(CK) 14.9±0.5a 4.3±0.5a 1.7±0.5a 12.3±0.2b 27.3±1.3b T2 16.5±0.4a 4.6±0.1a 2.6±0.3a 13.0±0.3ab 31.5±1.4a T3 15.4±0.3a 4.6±0.1a 1.9±0.3a 12.4±0.2b 28.4±0.8ab T4 15.9±0.7a 4.7±0.2a 2.4±0.2a 13.7±0.5a 28.4±0.6ab 2021 T1(CK) 17.0±0.5b 4.5±0.1a 2.7±0.5a 13.3±0.7a 26.0±1.2a T2 19.0±0.7a 4.8±0.3a 2.4±0.6a 13.0±0.0a 33.0±4.5a T3 18.1±0.3ab 4.3±0.4a 2.6±0.6a 13.3±0.3a 29.7±0.1a T4 18.6±0.3ab 4.5±0.6a 2.9±0.4a 13.0±0.0a 28.7±2.7a Note: The data in the table of agronomic traits are the average value of three repetitions. Different lowercase letters in the same column represent the level of 0.05, with significant difference. 5 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 3.2 Effects of Different Intercropping Models on Maize Yield In the two years, the yield of maize intercropping was higher than that of monoculture. Although there was no significant difference among all treatments, maize inter- cropping soybean (T2) showed the highest yield, with an average yield of 42.1 kg and 43.5 kg respectively, fol- lowed by maize intercropping sweet potato (T4). Corn intercropping with soybean plays a great role in increasing corn yield and is a better choice, which can improve eco- nomic benefits (Figure 2). 3.3 Grey Correlation Analysis of Agronomic Characters and Yield in Different Intercropping Models According to the requirements of grey theory, the cor- relation degree and order of correlation degree of agro- nomic traits to yield in 2020 and 2021 are shown in Table 3. The correlation degree of all traits to yield are as fol- lows: ear length (0.7324) > grain number per row (0.7144) > plant height (0.7073) > ear height (0.6857) > stem di- ameter (0.6481) > rows per ear (0.6009) > bald tip length (0.5910) > ear width (0.5461); Ear length (0.8141) > 192.1 212.2219.3 236.4 203.3 231.3 206.8 234.7 0.0 50.0 100.0 150.0 200.0 250.0 300.0 2020 2021 Fr es h fr ui t e ar w ei gh t( g) T1 T2 T3 T4 Figure 1. Ear weight of fresh fruit under different intercropping models Note: The data in the table are SEm. 36.9 42.1 39.0 40.9 36.9 43.5 39.9 42.4 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 T1 T2 T3 T4 yi el d（ kg ） Production in 2020 Production in 2021 linearity（Production in 2020） linearity（Production in 2021） Figure 2. Yield of fresh ear plots under different intercropping models Note: The data in the table are SEm. 6 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 rows per ear (0.8034) > plant height (0.7961) > ear height (0.7887) > ear width (0.7718) > bald tip length (0.6358) > grain number per row (0.6032) > stem diameter (0.4379). The correlation order of ear diameter, number of rows per ear, number of grains per row and yield changed greatly in different years, while the correlation order of ear length, plant height, ear position height and yield was relatively stable. The correlation between ear length, plant height and yield was the first and third in two years, indicating that ear length and plant height had a great impact on yield. The grey correlation analysis of Maize Yield and ag- ronomic traits can explore the relationship between maize yield and agronomic traits, help to clarify the yield trait factors affecting maize high yield, and provide a basis for the theory of high yield of different intercropping maize in the later stage. The results showed that the development of different maize intercropping modes should pay atten- tion to strengthening field management and improving ear length, plant height and stem diameter. The selection of maize intercropping mode suitable for red soil dryland is helpful to improve the yield of maize intercropping (Table 3). Table 3. Correlation degree and order between agronomic characters and yield of Maize under different intercrop- ping modes Agronomic traits 2020 2021 Correlation degree Correlation order Correlation degree Correlation order Plant height 0.7073 3 0.7961 3 Stem diameter 0.6481 5 0.4379 8 Ear height 0.6857 4 0.7887 4 Ear width 0.5461 8 0.7718 5 Ear length 0.7324 1 0.8141 1 Rows per ear 0.6009 6 0.8034 2 Grain number per row 0.7144 2 0.6032 7 Bald tip length 0.5910 7 0.6358 6 4. Discussion 4.1 Effects of Different Intercropping Models on Agronomic Characters and Yield Studies have shown that in intercropping systems such as maize soybean [20] and maize peanut [21,22], the yield of intercropping maize is significantly higher than that of monocropping, showing obvious advantages in intercrop- ping yield [23]. The research results of Xie Xinghua et al. [24] showed that the yield per plant of intercropping maize was higher than that of monocropping maize. The inter- cropping of corn and sweet potato can increase the crop yield per unit land area, which is conducive to ensuring food security and increasing farmers’ income. The re- search results of Shen Lei et al. [25] showed that compared with monocropping, corn intercropping can promote the growth of corn and increase the yield of corn, and it has better planting advantages. The results of this study show that corn intercropping can increase the plant height, ear height, stem diameter, ear length, number of rows and grains, and yield of corn, and has advantages in promoting corn growth and yield. 4.2 Grey Correlation Analysis of Agronomic Characters and Yield in Different Intercropping Models The research results of Wang Pingxi et al. [26] showed that the correlation degree between the main agronomic characters and yield of each maize line was as follows: ear width > grain number per row > leaf length per ear > stem diameter > ear length > ear height > number of male ear branches > leaf width per ear > main shaft length of male ear > angle between upper ear leaves > plant height > leaf area per ear > rows per ear > bald tip length, including ear width, grain number per row, stem diameter had a great effect on maize yield. Sun Fengcheng et al. [27] applied grey correlation analysis to show that the agronomic traits closely related to maize yield are seed yield, grain number per row, ear width, 100 grain quality and plant height. The results showed that different agronomic characters would have different effects on maize, such as ear length, plant height and so on. Therefore, when developing dif- ferent intercropping models of maize in red soil dryland, we should pay attention to the selection of varieties with appropriate ear length and plant height. In this study, only one variety of Gancainuo 7 was selected. There may be differences among different maize varieties. Different geographical locations, climatic conditions and cultivation and management measures can also lead to different test results. 5. Conclusions The results showed that maize intercropping could not only improve plant height, stem diameter and ear height, promote ear length, grain number per row and other ear characters, but also improve maize yield. The main agro- nomic factors affecting the yield of intercropping maize are ear length and plant height. Selecting suitable varieties and strengthening field management are conducive to bet- ter correlation and improve the yield. The comprehensive 7 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 analysis shows that the intercropping advantage of maize and soybean is obvious, which is conducive to high qual- ity and high yield. Funding This research was funded by the National Research Foundation of China (32160310); National Key Research and Development Program of China (2016YFD0300208); Scientific Project of Department of Jiangxi Education of China (GJJ200444); Key disciplines (construction) of ecology in the 13th Five-Y ear Plan of Jiangxi Agricultural University. Conflict of Interest The authors declare no conflict of interest. References [1] Zhao, K., 2019. Current status and development trend of corn production in my country. New Agriculture. 24, 49. [2] Cui, A.H., Zhou, L.H., Yang, B.J., et al., 2017. Eco- logical function evaluation of different multiple cropping methods in red dry land. Chinese Journal of Applied Ecology. 28(02), 456-464. [3] Huang, G.Q., Liu, X.Y., Liu, L.W., et al., 2006. Comprehensive benefit evaluation of multi-cropping planting system in dryland of red soil. Acta Ecologi- ca Sinica. 8, 2532-2539. [4] Willey, R., 1979. Intercropping Its Importance And Research Needs Part 1. Competition And Yield Ad- vantages Vol-32. Field Crop Abstracts. 32. [5] Rengel, L.L.A.J., 2001. Wheat/maize or wheat/ soybean strip intercropping: I. Yield advantage and interspecific interactions on nutrients. Field Crops Research. [6] Liu, G.C., Yang, Q.F., Li, L., et al., 2008. The advan- tages of wheat/maize intercropping and the relative contribution of aboveground and underground fac- tors. Chinese Journal of Plant Ecology. 2, 477-484. [7] Yang, W.Y., 2008. A new high-efficiency ecological multi-cropping planting model in dry land “Wheat- Jade-Bean”. World Agriculture. 9, 78-79. [8] Chen, F., 1997. New progress of multi-cropping system in my country. Farming and Cultivation. 1997(Z1), 9-11. [9] Liu, X.H., Chen, F., Wu, Y., 2015. Multi-crop plant- ing-the mainstay of Chinese agriculture. Crop Jour- nal. 6, 1-9. [10] Gao, Sh.J., 2017. The current situation and develop- ment trend of corn production in my country. Friends of Farmers to Get Rich. 22, 77. [11] Yang, R.Zh., Lu, J.Sh., Zhao, L.F., et al., 1996. Re- search on the intercropping method of corn with soy- bean, peanut and sweet potato. Maize Science. 4, 50- 53. [12] Zhang, X.Q., Huang, G.Q., Bian, X.M., et al., 2012. Effects of intercropping on corn quality, yield, soil microbial quantity and enzyme activity. Acta Ecolog- ica Sinica. 32(22), 7082-7090. [13] Chu, F.L., Li, Sh.M., Liu, Y.J., et al., 2020. The effect of sweet potato and corn intercropping on soil prop- erties and crop yields. Shanxi Agricultural Sciences. 48(09), 1445-1448. [14] Gao, Y., Duan, A.W., Liu, Z.G., et al., 2009. Effects of monocropping and intercropping on the radiation efficiency and yield of maize and soybean popula- tions. Chinese Journal of Eco-Agriculture. 17(01), 7-12. [15] Yang, H., Zhou, Y., Chen, P., et al., 2021. The effect of corn-legume intercropping on nutrient absorption and utilization and yield advantages. Acta Crops, 2021, 1-14. [16] Zhang, Y., Guo, Sh.Y., Shang, Sh., et al., 2020. Ef- fects of different sweet potato/maize intercropping methods on soil nutrients, enzyme activities and crop yields. Shanxi Agricultural Sciences. 48(08), 1234- 1238. [17] Xie, X.H., Guo, Sh.Y., Lu, G.Y., et al., 2016. Effects of corn and sweet potato intercropping on related factors of corn yield formation. Journal of Anhui Ag- ricultural Sciences. 44(09), 39-41. [18] Wang, X.W., Yang, W.T., Miao, J.Q., et al., 2014. Effects of maize-soybean intercropping and nitrogen application on maize yield and agronomic character- istics. Acta Ecologica Sinica. 34(18), 5275-5282. [19] Li, Q.Ch., Wang, L.D., Zhao, X.M., et al., 2020. Ef- fects of different sowing dates and planting methods on related traits and yield of waxy corn. Heilongjiang Agricultural Sciences. 9, 20-23. [20] Tsubo, M., Walker, S., Ogindo, H.O., 2005. A simu- lation model of cereal–legume intercropping systems for semi-arid regions: I. Model development. Field Crops Research. 93(1), 10-22. [21] Jiao, N.Y., Zhao, C., Ning, T.Y., et al., 2008. Effects of maize-peanut intercropping on economic yield and light response of photosynthesis. Chinese Journal of Applied Ecology. 19(5), 981-985. [22] Banik, P., Sharma, R.C., 2009. Yield and Resource Utilization Efficiency in Baby Corn—Legume-In- tercropping System in the Eastern Plateau of India. Journal of Sustainable Agriculture. 33(4), 379-395. 8 Research on World Agricultural Economy | Volume 03 | Issue 01 | March 2022 [23] Jiao, N.Y., Ning, T.Y., Yang, M.K., et al., 2013. Ef- fects of maize and peanut intercropping on photosyn- thetic characteristics and yield formation of maize. Acta Ecologica Sinica. 33(14), 4324-4330. [24] Xie, X.H., Guo, Sh.Y., Lu, G.Y., et al., 2016. Effects of corn and sweet potato intercropping on related factors of corn yield formation. Journal of Anhui Ag- ricultural Sciences. 44(09), 39-41. [25] Shen, L., Wang, X.Y., Teng, Y.X., et al., 2021. Study on the influence of maize soybean on crop growth and yield in arid area. Journal of Shihezi University (Natural Science). DOI: https://doi.org/10.13880/ j.cnki.65-1174/n.2021.21.034. [26] Wang, P.X., Jin, X.N., Wu, X.Y., et al., 2021. Grey Correlation Analysis of Main Agronomic Characters and Yield of 14 Maize Lines. Journal of Henan In- stitute of Science and Technology (Natural Science). 49(05), 12-18. [27] Sun, F.Ch., Feng, Y., Yu, Zh., et al., 2012. Grey cor- relation analysis of main agronomic traits, yield and quality of 12 maize populations. North China Agri- cultural Journal. 27(01), 102-105.