{"title":"Corn Growth Model Based on Yield Statistical Model","authors":"Adityan Kumare","doi":"10.38007/ajas.2022.030305","DOIUrl":null,"url":null,"abstract":": Corn is one of the main agricultural crops in China, but the agricultural technology conversion rate of corn cultivation is not high. The growth cycle of corn is longer and the process is more complicated. In addition to being affected by internal physiological mechanisms, the growth of maize has a great influence on its growth environment, especially the light environment. During the growth process, the interaction between corn and light environment is constantly underway. Corn planting time is also an important factor affecting corn yield. The difference in sowing date directly affects the growth and development stages of corn. The purpose of this paper is to study the growth pattern of corn based on a statistical model of yield. In terms of methods, it is proposed to use the inverse ray tracing algorithm to calculate the light energy reflected and absorbed by the corn, and establish a model to analyze the sensitivity of the area, mainly in terms of leaf area index, temperature, and moisture to analyze corn yield. Establish a corn growth model, and construct it from four aspects: yield, photosynthesis, temperature, and moisture. Finally, comprehensive supplements were made, and planting conditions continued to be optimized at planting density. In terms of experiments, the meteorological data and soil parameters of the plantation site were investigated. Finally, the experiment was divided into four groups, one was for home planting; the other was for planting at different intervals, the other was normal; the three were for drip irrigation, and the other was normal Four groups were planted using the improved strategies proposed in this paper. It is concluded that under drip irrigation conditions, the grain filling rate can be significantly increased, which will lead to an increase in 100-grain weight during maturity. With the increase of the population density, the competition among individuals within the group for light, temperature, water, and fertilizer is intensified. For better individual development, the individual plant height and ear height have been continuously increased in order to obtain more light energy","PeriodicalId":396836,"journal":{"name":"Academic Journal of Agricultural Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Academic Journal of Agricultural Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38007/ajas.2022.030305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: Corn is one of the main agricultural crops in China, but the agricultural technology conversion rate of corn cultivation is not high. The growth cycle of corn is longer and the process is more complicated. In addition to being affected by internal physiological mechanisms, the growth of maize has a great influence on its growth environment, especially the light environment. During the growth process, the interaction between corn and light environment is constantly underway. Corn planting time is also an important factor affecting corn yield. The difference in sowing date directly affects the growth and development stages of corn. The purpose of this paper is to study the growth pattern of corn based on a statistical model of yield. In terms of methods, it is proposed to use the inverse ray tracing algorithm to calculate the light energy reflected and absorbed by the corn, and establish a model to analyze the sensitivity of the area, mainly in terms of leaf area index, temperature, and moisture to analyze corn yield. Establish a corn growth model, and construct it from four aspects: yield, photosynthesis, temperature, and moisture. Finally, comprehensive supplements were made, and planting conditions continued to be optimized at planting density. In terms of experiments, the meteorological data and soil parameters of the plantation site were investigated. Finally, the experiment was divided into four groups, one was for home planting; the other was for planting at different intervals, the other was normal; the three were for drip irrigation, and the other was normal Four groups were planted using the improved strategies proposed in this paper. It is concluded that under drip irrigation conditions, the grain filling rate can be significantly increased, which will lead to an increase in 100-grain weight during maturity. With the increase of the population density, the competition among individuals within the group for light, temperature, water, and fertilizer is intensified. For better individual development, the individual plant height and ear height have been continuously increased in order to obtain more light energy