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首页> 外文期刊>Journal of Agricultural Science >Land Suitability Assessment for Soybean (Glycine max (L.) Merr.) Production in Kabwe District, Central Zambia
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Land Suitability Assessment for Soybean (Glycine max (L.) Merr.) Production in Kabwe District, Central Zambia

机译：赞比亚中部Kabwe区大豆（Glycine max（L.）Merr。）的土地适宜性评估

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Soybean (Glycine max (L.) Merr.), is a high value crop that can generate income for households. As a legume, soybean is incorporated in cropping systems to improve soil fertility. Soybean productivity is however limited by factors including declined soil fertility, climate change and partly due to inadequate land suitability information. This study aimed at identifying suitable land for soybean production in Kabwe district. Data layers of selected attributes relevant to soybean production were generated with slope and wetness data layers extracted from the digital elevation model (DEM). Elevation was used as a proxy for climate (rainfall and temperature) and was generated by reclassifying the elevation grid into elevation classes. Data layers for soil reaction (pH), soil organic carbon, phosphorus and texture were generated by inverse distance weighting interpolation method based on soil point data. A distance to roads layer was created using the euclidean distance tool. A spatial process model based on multi-criteria evaluation was used to integrate data layers in a weighted sum overlay to generate a soybean suitability map, whose quality was assessed using an error matrix. Results showed that 15.07% of the investigated area was highly suitable for soybean production, whereas 26.53% was suitable and 25.18% was moderately suitable. The other 20.57% was marginally suitable, 10.74% was currently not suitable and 1.92% was permanently not suitable. Based on ground truth data, the overall classification accuracy of the suitability map was 65%. The map was therefore good enough for use as a guide in selecting suitable sites for soybean production.
机译：大豆（Glycine max（L.）Merr。）是一种高价值农作物，可以为家庭带来收入。作为一种豆科植物，大豆被纳入作物系统以改善土壤肥力。但是，大豆生产力受到土壤肥力下降，气候变化等因素的限制，部分原因是土地适应性信息不足。这项研究旨在确定卡布韦地区适合大豆生产的土地。与大豆生产相关的选定属性的数据层是使用从数字高程模型（DEM）中提取的坡度和湿度数据层生成的。高程被用作气候（降雨和温度）的替代，并且是通过将高程网格重新分类为高程类别而生成的。通过基于土壤点数据的逆距离加权插值法生成土壤反应（pH），土壤有机碳，磷和质地的数据层。使用欧氏距离工具创建了到道路的距离层。使用了基于多准则评估的空间过程模型，将数据层以加权总和叠加的方式进行整合，以生成大豆适宜性图，并使用误差矩阵对其质量进行了评估。结果表明，调查面积的15.07％非常适合大豆生产，而26.53％的适合大豆和25.18％的适合大豆。其余20.57％勉强合适，目前10.74％不合适，而1.92％永久不合适。根据地面真实数据，适用性地图的总体分类准确性为65％。因此，该地图足够好，可以用作选择合适的大豆生产地点的指南。

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