利用拉曼光谱评估温室菠菜中硝酸盐水平:可持续农业和粮食安全的工具

IF 4.8 Q1 AGRICULTURE, MULTIDISCIPLINARY
Paolo Matteini , Carmelo Distefano , Marella de Angelis , Giovanni Agati
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引用次数: 0

摘要

在蔬菜种植中过度使用氮基肥料引起了重大的环境和健康问题,推动了对可持续施肥做法的需要。众所周知,菠菜容易积聚硝酸盐,因此需要精确的监测工具。本研究利用多元线性回归(MLR)和偏最小二乘回归(PLSR)模型,探讨了拉曼光谱在量化温室菠菜硝酸盐含量方面的潜力。两种模型均表现出较强的预测性能,R2均超过0.8。此外,将拉曼光谱与Dualex等光学传感器相结合,可以进一步提高硝酸盐的预测精度。这些发现强调了这种非破坏性、可扩展的方法的可行性,为可持续农业、粮食安全和环境保护提供了一个有希望的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessment of nitrate levels in greenhouse-grown spinaches by Raman spectroscopy: A tool for sustainable agriculture and food security

Assessment of nitrate levels in greenhouse-grown spinaches by Raman spectroscopy: A tool for sustainable agriculture and food security
Excessive use of nitrogen-based fertilizers in vegetable cultivation has raised significant environmental and health concerns, driving the need for sustainable fertilization practices. Spinach, known for its propensity to accumulate nitrates, demands precise monitoring tools. This study investigates the potential of Raman spectroscopy for quantifying nitrate levels in greenhouse-grown spinach, utilizing multiple linear regression (MLR) and partial least squares regression (PLSR) models. Both models exhibit strong predictive performance, with R2 exceeding 0.8. Furthermore, integrating Raman spectroscopy with optical sensors like the Dualex can further enhance nitrate prediction accuracy. These findings underscore the feasibility of this non-destructive, scalable approach, offering a promising solution for sustainable agriculture, food security, and environmental protection.
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来源期刊
CiteScore
5.40
自引率
2.60%
发文量
193
审稿时长
69 days
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