使用视觉和近红外光谱测量来确定液体有机肥的营养素,干物质和pH值
Michael Horf1, Robin Gebbers2, Hans-Werner Olfs3
1Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Department of Agromechatronics, Max-Eyth-Allee 100, 14469 Potsdam, Germany.
The Science of the total environment
|November 3, 2023
概括
光学光谱仪准确地预测液态有机肥 (LOM) 中的营养含量,为传统分析提供了具有成本效益的替代方案. 这项技术可以实现精确的施肥,减少过度应用造成的环境污染.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 分析化学 分析化学
背景情况:
- 使用液态有机肥料 (LOM) 的过度施肥导致了诸如肥化和地下水酸盐污染等环境问题.
- 精确的,以需求为导向的受精需要对LOM营养成分的准确知识.
- 传统的化学分析是耗时的,昂贵的,并且依赖于代表性采样.
研究的目的:
- 评估光学光谱法作为确定LOM营养含量的有效替代方法.
- 研究光谱预处理和回归算法,以改进化学测量校准.
- 评估使用低成本光谱仪用于LOM分析的可行性.
主要方法:
- 收集了391个猪,155个牛和89个生物气消化样本的反射频谱.
- 使用化学模型预测植物宏观营养素,微量营养素,干物质 (DM) 和pH值.
- 基于干重与湿重度的比较预测.
- 模拟低分辨率光谱来评估低成本光谱仪的性能.
主要成果:
- 光谱仪准确地预测了LOM中的DM,pH和大多数营养素 (除外),即使使用模拟的低成本仪器.
- 实现了高预测准确度:r2 0.800.97,RPIQ 2.17.8,nMAE 536%. 预测的准确度是:r2 0.800.97,RPIQ 2.17.8,nMAE 536%. 预测的准确度是:r2 0.800.97,RPIQ 2.17.8,nMAE 536%. 预测的准确度是:r2 0.800.97,RPIQ 2.17.8,nMAE 536%.
- PLSR,LASSO和最小角度回归是表现最好的回归方法;简单比率 (SR) 和规范差异 (ND) 改善了N和P的预测.
结论:
- 光谱法是一种可行的,高效的方法,用于精确的LOM营养分析.
- 化学测量模型,特别是先进的预处理,提高了预测的准确性.
- 这项技术支持可持续的农业实践,允许以需求为导向的施肥.
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