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首页> 外文期刊>European Journal of Agronomy >MIMYCS.Moisture, a process-based model of moisture content in developing maize kernels
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MIMYCS.Moisture, a process-based model of moisture content in developing maize kernels

机译：MIMYCS.Moisture，基于过程的玉米粒发育过程中的水分含量模型

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摘要

Moisture content influences harvest timing and the consequent drying process and drying costs, and the development of spoilage fungi during pre- and post-harvest phases. Maize kernel development in the field can be partitioned into three phases: i) lag phase, ii) grain filling and maturation drying, and iii) post-maturity dry-down. A model simulating maize kernel moisture content during maturation can help either monitoring or foreseen maize kernel humidity during the harvest period. Also, it would be useful in simulation studies via crop models to estimate the infield feasibility of harvest but also the interaction with diseases responsible for mycotoxin production, against weather scenarios. A process-based model was developed, called MIMYCS.Moisture. When the hybrids were analyzed all together, MIMYCS.Moisture showed a good general predictive capability with an average error in moisture estimation of +/- 3.28% moisture (considering the root mean square error - RMSE). The model efficiency (EF) was positive (0.85) and the model was able to explain the 89.7% of variation. When the two sub-models were analyzed separately, the RMSE remained approximately at the same level of the general model, while the other indicators changed revealing the different characteristics of the two models. The developmental moisture sub-model has a slight tendency to overestimate, while the dry-down sub-model tended to underestimate final moisture content. However, when the model was analyzed separately for each hybrid, both calibration and validation results suggested that more data are needed to improve the model likely with respect to kernel characteristics of hybrids. Finally, the equilibrium moisture content equation used, taken from industrial drying models, might not be adequate for simulating the field conditions where temperature is well below the one in dryers and environmental air humidity may vary considerably across sites and harvest periods
机译：水分含量会影响收获时机以及随之而来的干燥过程和干燥成本，以及收获前和收获后阶段腐败菌的发展。田间玉米籽粒的发育可分为三个阶段：i）滞后阶段，ii）籽粒充填和成熟干燥，以及iii）成熟后的干燥。一个模拟成熟期玉米籽粒水分含量的模型可以帮助监测或预测收获期的玉米籽粒湿度。而且，在通过作物模型进行的模拟研究中，评估收割在野外的可行性，以及与天气情况下与造成霉菌毒素产生的疾病的相互作用，都将是有用的。开发了基于过程的模型，称为MIMYCS.Moisture。综合分析杂种后，MIMYCS.Moisture表现出良好的一般预测能力，且水分估计的平均误差为+/- 3.28％水分（考虑均方根误差-RMSE）。模型效率（EF）为正（0.85），该模型能够解释89.7％的变化。当分别分析两个子模型时，RMSE大致保持与通用模型相同的水平，而其他指标发生变化，从而揭示了两个模型的不同特征。发育的水分模型有一个高估的趋势，而干燥的水分模型倾向于低估最终的水分含量。但是，当分别对每个杂种进行模型分析时，校准和验证结果均表明，需要更多数据来改善模型的杂种核心特性。最后，从工业干燥模型得出的平衡水分含量方程可能不足以模拟田间条件，在该条件下，温度远低于干燥机中的温度，环境空气湿度在不同地点和收获期可能会有很大差异

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