Abstract. Low soil fertility is challenging the sustainable production of staple crops in the yam belt of West Africa. Quantitative soil measures are needed to assess soil fertility decline and to improve crop fertilization management in the region. We developed and tested a mid-infrared (mid-IR) soil spectral library to enable timely and cost-efficient assessments of soil properties. Our collection included 80 soil samples from four landscapes (10 km × 10 km) and 20 fields/landscape across a gradient from humid forest to savanna, and 14 additional samples from one landscape that had been sampled within the Land Health Degradation Framework. We derived partial least square regression models to estimate soil properties with spectra.The models produced accurate cross-validated estimates of total carbon, total nitrogen, total sulfur, total iron, total aluminum, total potassium, total calcium, exchangeable calcium, effective cation exchange capacity, diethylenetriaminepentaacetic acid (DTPA) extractable iron and clay content (R² > 0.75). The estimates of total zinc, pH, exchangeable magnesium, bioavailable copper and manganese were less predictable (R² > 0.50). Our results confirm that mid-IR spectroscopy is a reliable and quick method assess the regional-scale variation in most soil properties, especially the ones closely associated with soil organic matter. Although the relatively small mid-IR library shows satisfactory performance, we expect that frequent but small model updates will be needed to adapt the library to the variation of soil quality attributes within individual fields in the regions and their temporal fluctuations.

中文翻译：

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用中红外土壤光谱法估算西非山药生产景观的土壤性质

摘要。低土壤肥力正在挑战西非山药带的主粮可持续生产。需要采取定量土壤措施来评估土壤肥力下降并改善该区域的作物施肥管理。我们开发并测试了中红外（mid-IR）土壤光谱库，以便能够对土壤特性进行及时且经济高效的评估。我们的收集包括从四个景观（10 km×10 km）中的80个土壤样品，以及从潮湿森林到热带稀树草原的梯度的20个田地/每个景观，以及从一个土地景观退化框架中采样的14个其他样品。我们推导了偏最小二乘回归模型以利用光谱估算土壤特性，该模型对总碳，总氮，总硫，总铁，R ²  > 0.75）。总锌，pH，可交换镁，可生物利用的铜和锰的估计值难以预测（R ²  > 0.50）。我们的结果证实，中红外光谱法是评估大多数土壤特性，尤其是与土壤有机质紧密相关的区域尺度变化的可靠且快速的方法。尽管相对较小的中红外库显示出令人满意的性能，但我们希望需要频繁但较小的模型更新，以使该库适应该地区各个田地中土壤质量属性的变化及其时间波动。