Farmer’s data sourcing: A best practise example for mapping soil properties in permanent crops in South Tyrol (northern Italy)

In agriculture, detailed knowledge of soil properties is a key element for high-quality food production. However, soil data at a single parcel scale are generally unavailable. In this study, a best practice framework is presented where, through an operational chain from an individual farmer through a centralised database and with a geostatistical approach, new knowledge has been generated that enables application far beyond a single soil sample at the parcel scale. This study was carried out in intensively managed permanent crops in South Tyrol, Italy, where 16,000 soil samples taken in the framework of an integrated production program have been used to show the capability to predict accurate soil property maps. Geospatialisation was conducted using Kriging interpolation. Finally, the resulting maps of soil texture, soil organic matter (SOM), and pH are shown and discussed. The results showed that combining agricultural production guidelines, a long-term data collection program, farmers, public administration services, and scientific analysis can provide a successful framework for digital soil mapping. The large number of samples combined with their spatial distribution has contributed to the robust estimation of the soil texture, pH, and SOM prediction. The maps show the complex interplay of fluvial processes, topography, and anthropogenic influences on the variability of soil texture, pH, and SOM. Finally, this study was focused on a fixed time span and a subset of the available agronomic variables. Thus, the long-term soil monitoring program and the combination of all the available variables will allow digital assessment of the spatial patterns of nutrient availability, ecological risk assessments, change detection studies, and an overall long-term plan for soil security.

在农业领域，对土壤特性的深入了解是保证高品质食品生产的关键要素。然而，在单一地块尺度上，土壤数据的获取通常并不可得。本研究提出了一种最佳实践框架，通过从单个农民到集中式数据库的操作链条，并结合地理统计学方法，生成的新知识使得预测能力远超单一地块尺度上的土壤样本。该研究在意大利南蒂罗尔地区集约化管理的永久性作物中开展，利用了在该地区综合生产计划框架下采集的16,000个土壤样本，展示了预测精确土壤特性地图的能力。地理空间化处理采用了克里金插值。最终，展示了土壤质地、土壤有机质（SOM）和pH值的地图，并对其进行了讨论。结果表明，结合农业生产指南、长期数据收集计划、农民、公共行政服务以及科学分析，可以构建一个成功的数字土壤制图框架。大量样本及其空间分布有助于土壤质地、pH和SOM预测的稳健估计。地图展示了河流过程、地形和人类活动对土壤质地、pH和SOM变异性之间复杂的相互作用。最后，本研究聚焦于一个固定的时间跨度及可用农业变量的子集。因此，长期的土壤监测计划和所有可用变量的结合，将允许对营养空间分布模式进行数字评估，进行生态风险评估、变化检测研究，并制定土壤安全性的长期总体计划。