Desenvolvimento de modelos preditores de acúmulo de forragem em pastagens tropicais
Desenvolvimento de modelos preditores de acúmulo de forragem em pastagens tropicais
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发表时间：
2010
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通讯作者：
J. V. Malaquias
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作者：
F. Tonato;L. Barioni;C. G. S. Pedreira;Ozanival Dario Dantas;J. V. Malaquias
这项工作的目的是识别、量化和模拟巴西中部牧草积累的条件属性，并根据气候参数建立牧草积累潜力的估计模型。针对牧草生长数据插入问题，建立并实现了一个数据库结构。对狗牙根、狗牙根和尾叶草品种进行了初步数据试验。该数据库允许生成每个生长期的牧草平均积累率(TMA)、平均温度、最高和最低温度(Tmin)、全球入射辐射和一年中的一天的排序列表。以气候变量为回归变量，TMA为响应变量，进行了一元线性回归和多元线性回归。确定系数、Akaike准则和贝叶斯准则的最佳取值选择了以Tmin为自变量的模型作为标准。采用符合检验将模型分为6组。模型对不同品种有不同的估测能力。利用本地数据进行模型校正，可以考虑在其公式中忽略的影响，并提高潜在产量估计的精度。
The objective of this work was to identify, quantify and model conditioning attributes of forage accumulation in Central Brazil, and to develop estimating models of the forage accumulation potential, based on climatic parameters. A database structure was modeled and implemented for forage growth data insertion. Primary data experiments with Cynodon, Panicum and Urochloa cultivars were inserted. The databank allowed the generation of sorted lists of forage mean accumulation rates (TMA), average temperature, maximum and minimum (Tmin) temperatures, global incident radiation and day of the year, for each growth period. Simple and multiple linear regressions were made, with climatic variables as regressors and TMA as response variable. The model with Tmin as independent variable was adopted as standard because it stood out for the best values of determination coefficient, Akaike criterion and Bayesian criterion. The models were grouped by the coincidence test in six groups. The models have different estimating capacities for each cultivar. Model calibration using local data can accommodate effects disregarded in its formulation, and enhances potential yield estimative accuracy.