Soil acidification is a major and growing concern in many cropping regions globally. Whilst spatial variability in acidification is a common consideration in the management of soil health and fertility at sub-paddock scale, insufficient focus has been directed toward the identification of this variability. Suitability of portable visible near infrared reflectance (vis–NIR) spectroscopy was assessed in this study as a potential technique to achieve rapid, precise, inexpensive and spatially specific quantification of key soil parameters to inform lime requirements. Spectral fingerprints were taken using a 1 ha grid sampling approach, with four sampling protocols investigated as follows, scans: (i) directly on cleared soil surfaces; (ii) on 0–100 mm undisturbed cores; (iii) on dried 0–100 mm cores; and finally (iv) on dried, ground, sieved and mixed cores. Data was analysed using a partial least squares regression (PLSR) model to identify the strength of linear relationship between reference chemistry data and predictions derived from spectral readings. Lime requirement maps using vis–NIR predictions were then theoretically compared against traditional aggregated sampling patterns while considering the trade-offs between accuracy, economics and agronomy associated with the identification of spatial variability. The vis–NIR measurements demonstrated moderate predictive capabilities in field for determining pH (R² = 0.3–0.5) and liming requirements (R² = 0.5–0.6) rapidly at high spatial resolution. Vis–NIR in field mapping techniques, which enable the use of site specific management of soil resources, were found to positively redirect lime resources from alkaline areas toward acidic areas of the paddock, resulting in minimal difference to overall expenditure on lime purchase and potential for increased agronomic benefits over the long-term. Further spectral library development, calibration, and research on in-field sampling methods is recommended.

在全球许多种植区，土壤酸化是一个主要且日益严重的问题。虽然酸化的空间变异性是亚牧场规模土壤健康和肥力管理中的一个常见考虑因素，但对这种变异性的识别还不够重视。本研究评估了便携式可见近红外反射 (vis-NIR) 光谱作为一种潜在技术的适用性，可实现关键土壤参数的快速、精确、廉价和空间特定量化，以告知石灰需求。光谱指纹是使用 1 公顷网格采样方法获取的，四种采样协议调查如下，扫描：（i）直接在清除的土壤表面上；(ii) 在 0-100 毫米未受干扰的核心上；(iii) 在干燥的 0-100 毫米芯上；最后 (iv) 在干燥的地面上，筛分和混合核。使用偏最小二乘回归 (PLSR) 模型分析数据，以确定参考化学数据与光谱读数预测之间线性关系的强度。然后在理论上将使用 vis-NIR 预测的石灰需求图与传统的聚合采样模式进行比较，同时考虑与识别空间变异性相关的准确性、经济性和农学之间的权衡。vis-NIR 测量表明在现场确定 pH (R 然后在理论上将使用 vis-NIR 预测的石灰需求图与传统的聚合采样模式进行比较，同时考虑与识别空间变异性相关的准确性、经济性和农学之间的权衡。vis-NIR 测量表明在现场确定 pH (R 然后在理论上将使用 vis-NIR 预测的石灰需求图与传统的聚合采样模式进行比较，同时考虑与识别空间变异性相关的准确性、经济性和农学之间的权衡。vis-NIR 测量表明在现场确定 pH (R²  = 0.3–0.5) 和石灰要求 (R ²  = 0.5–0.6) 在高空间分辨率下迅速。现场测绘技术中的 Vis-NIR 能够使用特定地点的土壤资源管理，被发现可以将石灰资源从碱性区域转移到围场的酸性区域，从而对石灰采购的总体支出和潜在的长期增加农艺效益。建议进一步开发、校准和研究现场采样方法的光谱库。