Soil fertility is one of the most critical bases for high productivity and sustainability in crop production. Within-field heterogeneity is often problematic in both crop management practices and crop productivity. Besides, appropriate soil management practices leads to the effective carbon sequestration. Since the soil carbon content (SCC) is the most simple and effective indicator of soil fertility, accurate and high-resolution mapping of SCC is an essential basis for addressing these issues. Here, we developed a tractor-based hyperspectral sensing system for speedy and accurate mapping of SCC. A new hybrid spectral algorithm linking normalized difference spectral index (h-NDSI) and machine learning proved superior. Appropriate algorithms were implemented to generate diagnostic map and prescription map from SCC map for the variable-rate application of pellet manure. The field performance of the sensing/mapping system was tested in the farmers' fields in the Fukushima region of Japan where the within-field heterogeneity of soil fertility was disastrous due to the decontamination after the nuclear power-plant disaster. The structure and functioning of the system proved promising. Moreover, the spatial simulation by linking the SCC data and a dynamic simulation model clearly showed the significant impact of variable-rate application of pellet manure on the chronosequential change of SCC, within-field heterogeneity, and carbon stock. The systematic linkage of the sensing/mapping system with the variable-rate spreader and dynamic simulation model would be effective for improving soil fertility and soil carbon stock. Applicability of the system will be extended through an extensive validation of the predictive models.

土壤肥力是作物生产高生产力和可持续性的最关键基础之一。田间异质性通常在作物管理实践和作物生产力方面都存在问题。此外，适当的土壤管理实践可以实现有效的碳固存。由于土壤碳含量（SCC）是土壤肥力最简单、最有效的指标，因此准确、高分辨率的SCC制图是解决这些问题的重要基础。在这里，我们开发了一种基于拖拉机的高光谱传感系统，用于快速、准确地绘制 SCC 地图。事实证明，一种将归一化差异光谱指数 ( h -NDSI) 和机器学习联系起来的新型混合光谱算法具有优越性。采用适当的算法从 SCC 图生成诊断图和处方图，用于颗粒肥料的可变施用量。传感/测绘系统的现场性能在日本福岛地区的农田中进行了测试，由于核电站灾难后的净化工作，田间土壤肥力的异质性是灾难性的。该系统的结构和功能被证明是有前途的。此外，通过将SCC数据与动态模拟模型联系起来进行的空间模拟清楚地表明了颗粒肥的可变施用量对SCC的时间顺序变化、田间异质性和碳储量的显着影响。传感/测绘系统与可变速率撒布器和动态模拟模型的系统连接将有效提高土壤肥力和土壤碳储量。该系统的适用性将通过预测模型的广泛验证得到扩展。