Quantitative design of yield components to simulate yield formation for maize in China
| Autor: | Li-Yuan Tang, Cong-feng Li, Ming Zhao, Mehmood Ali Noor, Haipeng Hou, Zai-song Ding, Wei Ma |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Normalization (statistics) Quantitative design Mean squared error Agriculture (General) Plant Science maize Inner mongolia 01 natural sciences Biochemistry yield performance parameters quantitative design S1-972 Nutrient Food Animals yield prediction process Leaf area index Mathematics high yield Ecology Plant density Sowing 04 agricultural and veterinary sciences Agronomy 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Animal Science and Zoology Agronomy and Crop Science 010606 plant biology & botany Food Science |
| Zdroj: | Journal of Integrative Agriculture, Vol 19, Iss 3, Pp 668-679 (2020) |
| ISSN: | 2095-3119 |
| DOI: | 10.1016/s2095-3119(19)62661-4 |
| Popis: | Maize (Zea mays L.) stands prominently as one of the major cereal crops in China as well as in the rest of the world. Therefore, predicting the growth and yield of maize for large areas through yield components under high-yielding environments will help in understanding the process of yield formation and yield potential under different environmental conditions. This accurate early assessment of yield requires accuracy in the formation process of yield components as well. In order to formulate the quantitative design for high yields of maize in China, yield performance parameters of quantitative design for high grain yields were evaluated in this study, by utilizing the yield performance equation with normalization of planting density. Planting density was evaluated by parameters including the maximum leaf area index and the maximum leaf area per plant. Results showed that the variation of the maximum leaf area per plant with varying plant density conformed to the Reciprocal Model, which proved to have excellent prediction with root mean square error (RMSE) value of 5.95%. Yield model estimation depicted that the best optimal maximum leaf area per plant was 0.63 times the potential maximum leaf area per plant of hybrids. Yield performance parameters for different yield levels were quantitatively designed based on the yield performance equation. Through validation of the yield performance model by simulating high yields of spring maize in the Inner Mongolia Autonomous Region and Jilin Province, China, and summer maize in Shandong Province, the yield performance equation showed excellent prediction with the satisfactory mean RMSE value (7.72%) of all the parameters. The present study provides theoretical support for the formulation of quantitative design for sustainable high yield of maize in China, through consideration of planting density normalization in the yield prediction process, providing there is no water and nutrient limitation. |
| Databáze: | OpenAIRE |
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