Paolo Matteini , Carmelo Distefano , Marella de Angelis , Giovanni Agati
{"title":"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","authors":"Paolo Matteini , Carmelo Distefano , Marella de Angelis , Giovanni Agati","doi":"10.1016/j.jafr.2025.101839","DOIUrl":null,"url":null,"abstract":"<div><div>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 R<sup>2</sup> 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.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"21 ","pages":"Article 101839"},"PeriodicalIF":4.8000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of nitrate levels in greenhouse-grown spinaches by Raman spectroscopy: A tool for sustainable agriculture and food security\",\"authors\":\"Paolo Matteini , Carmelo Distefano , Marella de Angelis , Giovanni Agati\",\"doi\":\"10.1016/j.jafr.2025.101839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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 R<sup>2</sup> 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.</div></div>\",\"PeriodicalId\":34393,\"journal\":{\"name\":\"Journal of Agriculture and Food Research\",\"volume\":\"21 \",\"pages\":\"Article 101839\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Agriculture and Food Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666154325002108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Agriculture and Food Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666154325002108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
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.