The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25-year historical series (1995–2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987–2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four-parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees-day for 70 locations.

中文翻译：

---

非线性农业气象模型可以估计咖啡叶面吗？

病虫害侵袭造成的咖啡叶损失显着降低了其产量和咖啡豆品质。因此，本研究旨在使用作为气候函数的非线性模型来估计巴西阿拉比卡咖啡产量最高的地区的叶面。阿拉比卡咖啡25 年历史系列（1995-2019）叶面 (%) 数据由 Procafé Foundation 在未进行植物检疫处理的栽培中获得。气候数据由 NASA/POWER 平台以每日尺度获得，时间分辨率为 33 年（1987-2019），空间分辨率约为 106 公里，因此可以计算参考蒸散量（PET）。使用四参数 sigmoidal 逻辑模型通过回归分析调整叶面估计模型。从 70 个地点的度日开始对咖啡种植园的落叶趋势进行了分析。