Giesco
21st GiESCO International Meeting: ‘A Multidisciplinary Vision towards Sustainable Viticulture’ SENSITIVITY OF VIS‐NIR SPECTRAL INDICES TO DETECT NITROGEN DEFICIENCY AND CANOPY FUNCTION IN CV. BARBERA (VITIS VINIFERA L.) GRAPEVINES 1,2*
Matteo GATTI 1 1,2 1 1 1,2 , Alessandra GARAVANI , Alberto VERCESI , Cecilia SQUERI , Michele CROCI , 2 2 1,2 Ferdinando CALEGARI , Massimo VINCINI , Stefano PONI DIPROVES Università Cattolica del Sacro Cuore, Via E. Parmense 84, I-29122 Piacenza, Italy 2 CRAST Università Cattolica del Sacro Cuore, Via E. Parmense 84, I-29122 Piacenza, Italy *Corresponding author: matteo.gatti@unicatt.it
Abstract: Context and purpose of the study ‐ Precision nutrient management in viticulture can be addressed on the basis of a spatial characterization of within‐vineyard vine nutritional status derived from proximal or remote spectral observations. However, a key challenge is the discrimination between mineral deficiencies and water stress related issues, often coexisting under low vigor conditions. In addition several mineral disorders are associated to a decrease in chlorophyll concentration in leaves resulting in a wide array of symptoms classified as chlorosis. Despite clearly associated to their origin, visible symptoms appear too late for supporting an efficient mineral management; thus, non‐destructive early detection of either asymptomatic excess or deficient status become a challenging task of precision viticulture. This work evaluates the Vis‐NIR reflectance spectra and the sensitivity of the derived‐spectral indices to detect nitrogen deficiency in grapevines. Material and methods ‐ Well N‐fertilized vs. unfertilized vines were compared over two seasons (2016 and 2017) on Vitis vinifera L. cv. Barbera potted vines. For each treatment, 24 leaves from eight representative vines were tagged in order to collect, at different phenological stages, contact Vis‐NIR spectra and perform physiological measurements. The performance of several spectral vegetation indices sensitive to different biophysical (i.e. chlorophyll and carotenoids content, leaf area index) and physiological parameters (light use efficiency) was measured by means of a sensitivity (signal to noise ratio) analysis. Leaf greenness index was monitored with a handheld chlorophyll meter SPAD 502 whilst single‐leaf gas exchanges were assessed by using a handheld analyzer. Multispectral analysis was associated to a rigorous ground‐truthing as it concerns shoot growth, yield, fruit composition and pruning weight. Results – In both years the differential fertilization increased leaf N concentration of N+ vines at veraison. Vine performance varied according to plant vigor and nutritional status. N+ increased canopy growth, vine productivity, and bunch compactness whilst N0 enhanced the proportion of shot berries and reduced titratable acidity and malate in juice. N deficiency resulted in lower SPAD readings and assimilation rates as compared to well N‐fertilized vines. N0 vs N+ contact Vis‐NIR spectra differed in Green and Red‐edge regions with faster responses on basal leaves. Data were associated to a different sensitivity of Vis‐NIR spectral indices specially when based on the Red‐edge bands showing higher efficiency in detecting leaf N concentration since early stages of canopy growth.
Keywords: Mineral nutrition, Visual symptoms, Leaf age, Assimilation, Yield components, Phenotyping.
Abstract: Context and purpose of the study ‐ Precision nutrient management in viticulture can be addressed on the basis of a spatial characterization of within‐vineyard vine nutritional status derived from proximal or remote spectral observations. However, a key challenge is the discrimination between mineral deficiencies and water stress related issues, often coexisting under low vigor conditions. In addition several mineral disorders are associated to a decrease in chlorophyll concentration in leaves resulting in a wide array of symptoms classified as chlorosis. Despite clearly associated to their origin, visible symptoms appear too late for supporting an efficient mineral management; thus, non‐destructive early detection of either asymptomatic excess or deficient status become a challenging task of precision viticulture. This work evaluates the Vis‐NIR reflectance spectra and the sensitivity of the derived‐spectral indices to detect nitrogen deficiency in grapevines. Material and methods ‐ Well N‐fertilized vs. unfertilized vines were compared over two seasons (2016 and 2017) on Vitis vinifera L. cv. Barbera potted vines. For each treatment, 24 leaves from eight representative vines were tagged in order to collect, at different phenological stages, contact Vis‐NIR spectra and perform physiological measurements. The performance of several spectral vegetation indices sensitive to different biophysical (i.e. chlorophyll and carotenoids content, leaf area index) and physiological parameters (light use efficiency) was measured by means of a sensitivity (signal to noise ratio) analysis. Leaf greenness index was monitored with a handheld chlorophyll meter SPAD 502 whilst single‐leaf gas exchanges were assessed by using a handheld analyzer. Multispectral analysis was associated to a rigorous ground‐truthing as it concerns shoot growth, yield, fruit composition and pruning weight. Results – In both years the differential fertilization increased leaf N concentration of N+ vines at veraison. Vine performance varied according to plant vigor and nutritional status. N+ increased canopy growth, vine productivity, and bunch compactness whilst N0 enhanced the proportion of shot berries and reduced titratable acidity and malate in juice. N deficiency resulted in lower SPAD readings and assimilation rates as compared to well N‐fertilized vines. N0 vs N+ contact Vis‐NIR spectra differed in Green and Red‐edge regions with faster responses on basal leaves. Data were associated to a different sensitivity of Vis‐NIR spectral indices specially when based on the Red‐edge bands showing higher efficiency in detecting leaf N concentration since early stages of canopy growth.
Keywords: Mineral nutrition, Visual symptoms, Leaf age, Assimilation, Yield components, Phenotyping.