Agricultural Policy Environmental eXtender (APEX) Simulation of Spring Peanut Management in the North China Plain
Autor: | Qingquan Chu, Jie Zhao, Jaehak Jeong, Yao Jiang, Manyowa N. Meki, Huadong Zang, Zhaohai Zeng, Mengjie Shang, Nicole Norelli, Yadong Yang |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
0106 biological sciences
Canopy Irrigation water use efficiency sowing date lcsh:S Sowing 04 agricultural and veterinary sciences seeding rate 01 natural sciences lcsh:Agriculture Agronomy Evapotranspiration alternative crop 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Seeding peanut Water-use efficiency Leaf area index APEX model Agronomy and Crop Science Water use 010606 plant biology & botany |
Zdroj: | Agronomy Volume 9 Issue 8 Agronomy, Vol 9, Iss 8, p 443 (2019) |
ISSN: | 2073-4395 |
DOI: | 10.3390/agronomy9080443 |
Popis: | Spring peanut is a valuable alternative crop to mitigate water scarcity caused by excessive water use in conventional cropping systems in the North China Plain (NCP). In the present study, we evaluated the capability of the Agricultural Policy Environmental eXtender (APEX) model to predict spring peanut response to sowing dates and seeding rates in order to optimize sowing dates, seeding rates, and irrigation regimes. Data used for calibration and validation of the model included leaf area index (LAI), aboveground biomass (ABIOM), and pod yield data collected from a field experiment of nine sowing dates and seeding rate combinations conducted from 2017 to 2018. The calibrated model was then used to simulate peanut yield responses to extended sowing dates (5 April to 4 June with a 5-day interval) and seeding rates (15 plants m&minus 2 to 50 plants m&minus 2 with a 5 plants m&minus 2 interval) using 38 years of weather data as well as yield, evapotranspiration (ET), and water stress days under different irrigation regimes (rainfed, one irrigation before planting (60 mm) or at flowering (60 mm), and two irrigation with one time before planting and one time at flowering (60 mm each time) or at pod set (60 mm each time)). Results show that the model satisfactorily simulates pod yield of peanut based on R2 = 0.70, index of agreement (d value) being 0.80 and percent bias (PBIAS) values &le 4%. Moreover, the model performed reasonably well in predicting the emergence, LAI and ABIOM, with a R2 = 0.86, d = 0.95 and PBIAS = 8% for LAI and R2 = 0.90, d = 0.97 and PBIAS = 1% for ABIOM, respectively. Simulation results indicate that the best combination of sowing dates and seeding rates is a density of 35&ndash 40 plants m&minus 2 and dates during early-May to mid-May due to the influence of local climate and canopy structure to the growth and yield of peanut. Under the optimal sowing date and plant density, an irrigation depth of 60 mm during flowering gave a pod yield (5.6 t ha&minus 1) and ET (464 mm), which resulted in the highest water use efficiency (12.1 kg ha&minus 1 mm&minus 1). The APEX model is capable of assessing the effects of management practices on the growth and yield of peanut. Sowing 35&ndash 2 during early-May to mid-May with 60 mm irrigation depth is the recommended agronomic practice for peanut production in the water-constrained NCP. |
Databáze: | OpenAIRE |
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