Simulation of Growth and Leaf Area Index of Quality Protein Maize Varieties in the Southwestern Savannah Region of the DR-Congo
Simulation of Growth and Leaf Area Index of Quality Protein Maize Varieties in the Southwestern Savannah Region of the DR-Congo作者机构:Programme National Mais INERA Mvuazi RD-Congo Université Pédagogique Nationale Kinshasa RD-Congo Direction Scientifique Biométrie et Expérimentation INERA DG & Université de Kinshasa Kinshasa RD-Congo Département des Sciences Biologiques Université Laurentienne Sudbury Canada
出 版 物:《American Journal of Plant Sciences》 (美国植物学期刊(英文))
年 卷 期:2019年第10卷第6期
页 面:976-986页
学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题:Modeling Simulation Climate Change Leaf Area Index Quality Protein Maize INERA RD-Congo
摘 要:Logistic and exponential approaches have been used to simulate plant growth and leaf area index (LAI) in different growing conditions. The objective of the present study was to develop and evaluate an approach to simulate maize LAI that expresses key physiological and phonological processes using a minimum entry requirement for Quality Protein maize (QPM) varieties grown in the southwestern region of the DR-Congo. Data for the development and testing of the model were collected manually in experimental plots using a non-destructive method. Simulation results revealed measurable variations between crop seasons (long season A and short season B) and between the two varieties (Mudishi-1 and Mudishi-3) for height, number of visible leaves, and LAI. For both seasons, Mudishi-3, a short stature variety was associated with expected stable yield based on simulation data. In general, the model simulated reliably all the parameters including the LAI. The LAI value for mudishi-1 was higher than that of Mudishi-3. There were significant differences among the model parameters (K, Ti, a, b, Tf) and between the two varieties. In all crop conditions studied and for the two varieties, the senescence rate (a) was higher, while the growth rate (b) was lower compared to the estimates based on the STICS model.