Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels

Daniele Masseroni, Bianca Ortuani, Martina Corti, Pietro Marino Gallina, Giacomo Cocetta, Antonio Ferrante and Arianna Facchi
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Daniele Masseroni: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Bianca Ortuani: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Martina Corti: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Pietro Marino Gallina: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Giacomo Cocetta: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Antonio Ferrante: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy
Arianna Facchi: Department of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milan, Italy

Sustainability, 2017, vol. 9, issue 9, 1-20

Abstract: Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques—thermal indices ( I g (stomatal conductance index) and CWSI (Crop Water Stress Index)) and optical indices ( NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))—as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p -value lower than 0.05), and the highest R 2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI ) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI , NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions.

Keywords: optical imaging sensor; thermal camera; spectral imaging index; crop water status; crop water stress prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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