Spatial prediction of soil organic matter in Adingnigon (Benin) using Bayesian Maximum Entropy (BME)

E. E. Gongnet, C. Agbangba, Tranquillin Sédjro Affossogbe, R. G. Kakaï
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Abstract

Demographic pressure and climate change have heavily affected soil fertility. Proper soil management requires the understanding of the spatial variation of soil properties. In this study, Bayesian maximum Entropy (BME) was used to explore the variation of soil pH and soil organic matter (SOM) at Adingningon (Benin) using 106 soil samples. The predicting maps indicated a lower concentration (0.6 to 0.8g/kg) of SOM toward the center and pH mostly around 5.8 to 6.5 with lower error variance, suggesting an acidic soil. This results provide useful information for managing soil fertility to improve crop yields.\\
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基于贝叶斯最大熵(BME)的贝宁阿丁尼贡土壤有机质空间预测
人口压力和气候变化严重影响了土壤肥力。正确的土壤管理需要了解土壤性质的空间变化。本研究利用贝叶斯最大熵(BME)分析了贝宁Adingningon地区106个土壤样品的pH和有机质的变化。预测图显示,土壤中SOM浓度较低(0.6 ~ 0.8g/kg), pH值在5.8 ~ 6.5之间,误差方差较小,表明土壤为酸性土壤。这一结果为管理土壤肥力以提高作物产量提供了有用的信息
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