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Rapid and inexpensive assessment of soil total iron using Nix Pro color sensor

التفاصيل البيبلوغرافية
العنوان: Rapid and inexpensive assessment of soil total iron using Nix Pro color sensor
المؤلفون: Gaurav Jha, Debjani Sihi, Biswanath Dari, Harpreet Kaur, Mallika Arudi Nocco, April Ulery, Kevin Lombard
المصدر: Agricultural & Environmental Letters, Vol 6, Iss 3, Pp n/a-n/a (2021)
بيانات النشر: Wiley, 2021.
سنة النشر: 2021
المجموعة: LCC:Agriculture
LCC:Environmental sciences
مصطلحات موضوعية: Agriculture, Environmental sciences, GE1-350
الوصف: Abstract In this study, an inexpensive Nix Pro (Nix Sensor Ltd.) color sensor was used to develop prediction models for soil iron (Fe) content. Thirty‐eight soil samples were collected from five agricultural fields across the Animas watershed to develop and validate soil Fe prediction models. We used color space models to develop three different parameter sets for Fe prediction with Nix Pro. The different color space sets were used to develop three new predictive models for Nix Pro‐based Fe content against the lab‐based inductively coupled plasma analyzed Fe content. The model performances were assessed using the coefficient of determination, root mean square error, and model p‐value. Three models (International Commission on Illumination's lightness, ±a axis (redness to greenness), and ± b axis (yellowness to blueness) [CIEL*a*b]; red, green, blue [RGB]; and cyan, magenta, yellow, key [black] [CMYK]) were significant in predicting the Fe content using colorimetric variables with R2 ranging from 0.79 to 0.81. The mean square prediction error (MSPE) and Kling–Gupta efficiency (KGE) Index were calculated to validate models and CMYK was predicted to be a better model (MSPE = 0.13; KGE = 0.601) than CIEL*a*b and RGB models. The results suggest Nix Pro is useful in predicting soil Fe content.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2471-9625
Relation: https://doaj.org/toc/2471-9625
DOI: 10.1002/ael2.20050
URL الوصول: https://doaj.org/article/05f7c57737504bddaa0811b1aa1e47a7
رقم الأكسشن: edsdoj.05f7c57737504bddaa0811b1aa1e47a7
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24719625
DOI:10.1002/ael2.20050