近端感应土壤分析服务能力测试

IF 6.6 1区 农林科学 Q1 SOIL SCIENCE
Tiago R. Tavares , José A.M. Demattê , Abdul M. Mouazen , Eyal Ben-Dor , Adriano A. Anselmi , Victor Monseff de A. Campos , Budiman Minasny , Sérgio H. Godinho Silva , Sabine Chabrillat , Konstantinos Karyotis , Heitor Cantarella , Cristiano A. Andrade , Maurício R. Cherubin , Hudson W.P. de Carvalho , José Lavres
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引用次数: 0

摘要

土壤光谱库(SSL)和基于光谱的方法使用不同区域的电磁波谱进行直接土壤分析,在农业和环境应用中迅速获得了吸引力。然而,缺乏专门为这些新方法设计的标准化测试,引发了对市场表现一致性和透明度的担忧。本讨论文件强调了影响预测性能的关键因素,并强调需要针对基于传感器的技术进行能力测试。它还强调了误差度量对准确解释的重要性。建立强大的能力测试对于确保可靠的土壤分析服务和促进采用该技术的最佳实践至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Proficiency tests for soil analysis services via proximal sensing

Proficiency tests for soil analysis services via proximal sensing
Soil Spectral Libraries (SSL) and spectroscopy-based methods using varied regions of the electromagnetic spectrum for direct soil analysis are rapidly gaining traction in agricultural and environmental applications. However, the absence of standardized tests, specifically designed for these new methods, prompts concerns about performance consistency and transparency in the marketplace. This discussion paper underscores the critical factors that influence predictive performance and stresses the need for proficiency tests tailored to sensor-based techniques. It also highlights the significance of error metrics for accurate interpretation. Establishing robust proficiency tests is crucial for ensuring reliable soil analysis services and promoting the adoption of best practices in this technology.
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来源期刊
Geoderma
Geoderma 农林科学-土壤科学
CiteScore
11.80
自引率
6.60%
发文量
597
审稿时长
58 days
期刊介绍: Geoderma - the global journal of soil science - welcomes authors, readers and soil research from all parts of the world, encourages worldwide soil studies, and embraces all aspects of soil science and its associated pedagogy. The journal particularly welcomes interdisciplinary work focusing on dynamic soil processes and functions across space and time.
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