Chalchissa Fedhasa Benti, Diga Girma Mamo, Feyisa Gudina Legese, Tolossa Alemayehu Regassa
Jimma University, Department of Natural Resource Management, Jimma, Ethiopia.
Ethiopia Agricultural Research Institute, Addis Ababa, Ethiopia.
Heliyon. 2022 Aug 8;8(8):e10136. doi: 10.1016/j.heliyon.2022.e10136. eCollection 2022 Aug.
Estimating crop biomass is critical for countries whose primary source of income is agriculture. It is a valuable indicator for evaluating crop yields and provides information to growers and managers for developing climate change adaptation strategies. The objective of the study was to model the impacts of agroclimatic indicators on the performance of aboveground biomass (AGB) in Arabica coffee trees, a critical income source for millions of Ethiopians. One hundred thirty-five coffee tree stump diameters were measured at 40 cm above ground level. The historical (1998-2010) and future (2041-2070) agroclimatic data were downloaded from the European Copernicus climate change services website. All datasets were tested for missing data, outliers, and multicollinearity and were grouped into three clusters using the K-mean clustering method. The parameter estimates (coefficients of regression) were analyzed using a generalized regression model. The performance of coffee trees' AGB in each cluster was estimated using an artificial neural network model. The future expected change in AGB of coffee trees was compared using a paired t-test. The regression model's results reveal that the sensitivity of to agroclimatic variables significantly differs based on the kind of indicator, RCP scenario, and microclimate. Under the current climatic conditions, the rise of the coldest minimum (TNn) and warmest (TXx) temperatures raises the AGB of the coffee tree, but the rise of the warmest minimum (TNx) and coldest maximum (TXn) temperatures decreased it (P < 0.05). Under the RCP4.5, the rise of consecutively dry days (CDD) and TNx would increase the AGB of the coffee tree, while TNx and TXx would decrease it (P < 0.05). Except for TXx, all indicators would significantly reduce the AGB of coffee trees under RCP8.5 (P < 0.05). The average values of AGB under the current, RCP4.5, and RCP85 climate change scenarios, respectively, were 26.66, 28.79, and 24.41 kg/tree. The predicted values of AGB under RCP4.5 and RCP8.5 will be higher in the first and third clusters and lower in the second cluster in the 2060s compared to the current climatic conditions. As a result, early warning systems and adaptive strategies will be necessary to reduce the detrimental consequences of climate change. More research into the effects of other climatic conditions on crops, such as physiologically effective degree days, cold, hot, and rainy periods, is also required.
对于以农业为主要收入来源的国家来说，估算作物生物量至关重要。它是评估作物产量的一个重要指标，能为种植者和管理者制定气候变化适应策略提供信息。本研究的目的是建立农业气候指标对阿拉比卡咖啡树地上生物量（AGB）表现影响的模型，阿拉比卡咖啡树是数百万埃塞俄比亚人的重要收入来源。在离地面40厘米处测量了135个咖啡树树桩的直径。从欧洲哥白尼气候变化服务网站下载了历史（1998 - 2010年）和未来（2041 - 2070年）的农业气候数据。所有数据集都进行了缺失数据、异常值和多重共线性检验，并使用K均值聚类方法分为三个聚类。使用广义回归模型分析参数估计值（回归系数）。使用人工神经网络模型估计每个聚类中咖啡树AGB的表现。使用配对t检验比较咖啡树AGB未来预期的变化。回归模型的结果表明，AGB对农业气候变量的敏感性因指标类型、代表性浓度路径（RCP）情景和小气候而有显著差异。在当前气候条件下，最冷最低温度（TNn）和最热温度（TXx）的升高会增加咖啡树的AGB，但最热最低温度（TNx）和最冷最高温度（TXn）的升高会使其降低（P < 0.05）。在RCP4.5情景下，连续干旱天数（CDD）和TNx的升高会增加咖啡树的AGB，而TNx和TXx会使其降低（P < 0.05）。在RCP8.5情景下，除TXx外，所有指标都会显著降低咖啡树的AGB（P < 0.05）。在当前、RCP4.5和RCP8.5气候变化情景下，AGB的平均值分别为每棵树26.66千克、28.79千克和24.41千克。与当前气候条件相比，在20世纪60年代，RCP4.5和RCP8.5情景下AGB的预测值在第一和第三聚类中会更高，在第二聚类中会更低。因此，需要建立预警系统和适应性策略来减少气候变化的不利影响。还需要更多关于其他气候条件对作物影响的研究，如生理有效积温、寒冷、炎热和多雨期等。
