Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry

Canopy reflectance sensors are a viable technology to optimize the fertilization management of crops. In this research, canopy reflectance was measured through a passive sensor to evaluate the effects of either crop features (N fertilization, soil mulching, appearance of red fruits, and cultivars) o...

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Main Authors: Giorgio Gianquinto, Francesco Orsini, Giuseppina Pennisi, Stefano Bona
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/21/4730
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author Giorgio Gianquinto
Francesco Orsini
Giuseppina Pennisi
Stefano Bona
author_facet Giorgio Gianquinto
Francesco Orsini
Giuseppina Pennisi
Stefano Bona
author_sort Giorgio Gianquinto
collection DOAJ
description Canopy reflectance sensors are a viable technology to optimize the fertilization management of crops. In this research, canopy reflectance was measured through a passive sensor to evaluate the effects of either crop features (N fertilization, soil mulching, appearance of red fruits, and cultivars) or sampling methods (sampling size, sensor position, and hour of sampling) on the reliability of vegetation indices (VIs). Sixteen VIs were derived, including seven simple wavelength reflectance ratios (NIR/R460, NIR/R510, NIR/R560, NIR/R610, NIR/R660, NIR/R710, NIR/R760), seven normalized indices (NDVI, G-NDVI, MCARISAVI, OSAVI, TSAVI, TCARI), and two combined indices (TCARI/OSAVI; MCARI/OSAVI). NIR/560 and G-NDVI (Normalized Difference Vegetation Index on Greenness) were the most reliable in discriminating among fertilization rates, with results unaffected by the appearance of maturing fruits, and the most stable in response to different cultivars. Black mulching film did not affect NIR/560 and G-NDVI behavior at the beginning of the growing season, when the crop is more responsive to N management. Due to a moderate variability of NIR/560 and G-NDVI, a small sample size (5−10 observations) is sufficient to obtain reliable measurements. Performing the measurements at 11:00 and 14:00 and maintaining a greater distance (1.8 m) between plants and instrument enhanced measurement consistency. Accordingly, NIR/560 and G-NDVI resulted in the most reliable VIs.
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spelling doaj.art-592e05d87a7741e2a5dc822626e1aeb92022-12-22T03:58:34ZengMDPI AGSensors1424-82202019-10-011921473010.3390/s19214730s19214730Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral RadiometryGiorgio Gianquinto0Francesco Orsini1Giuseppina Pennisi2Stefano Bona3Department of Agricultural and Food Sciences (DISTAL), University of Bologna, Viale Fanin, 44, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), University of Bologna, Viale Fanin, 44, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), University of Bologna, Viale Fanin, 44, 40127 Bologna, ItalyDepartment of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università, 16, 35020 Legnaro (PD), ItalyCanopy reflectance sensors are a viable technology to optimize the fertilization management of crops. In this research, canopy reflectance was measured through a passive sensor to evaluate the effects of either crop features (N fertilization, soil mulching, appearance of red fruits, and cultivars) or sampling methods (sampling size, sensor position, and hour of sampling) on the reliability of vegetation indices (VIs). Sixteen VIs were derived, including seven simple wavelength reflectance ratios (NIR/R460, NIR/R510, NIR/R560, NIR/R610, NIR/R660, NIR/R710, NIR/R760), seven normalized indices (NDVI, G-NDVI, MCARISAVI, OSAVI, TSAVI, TCARI), and two combined indices (TCARI/OSAVI; MCARI/OSAVI). NIR/560 and G-NDVI (Normalized Difference Vegetation Index on Greenness) were the most reliable in discriminating among fertilization rates, with results unaffected by the appearance of maturing fruits, and the most stable in response to different cultivars. Black mulching film did not affect NIR/560 and G-NDVI behavior at the beginning of the growing season, when the crop is more responsive to N management. Due to a moderate variability of NIR/560 and G-NDVI, a small sample size (5−10 observations) is sufficient to obtain reliable measurements. Performing the measurements at 11:00 and 14:00 and maintaining a greater distance (1.8 m) between plants and instrument enhanced measurement consistency. Accordingly, NIR/560 and G-NDVI resulted in the most reliable VIs.https://www.mdpi.com/1424-8220/19/21/4730passive sensorsampling methodologybootstrap analysisvegetation indicesgreen ratio of vegetation indexnir/560 or gvi (green vegetation index)green normalized difference vegetation indexnormalized difference vegetation index on greenness (g-ndvi)soil mulchingsolanum lycopersicum l
spellingShingle Giorgio Gianquinto
Francesco Orsini
Giuseppina Pennisi
Stefano Bona
Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
Sensors
passive sensor
sampling methodology
bootstrap analysis
vegetation indices
green ratio of vegetation index
nir/560 or gvi (green vegetation index)
green normalized difference vegetation index
normalized difference vegetation index on greenness (g-ndvi)
soil mulching
solanum lycopersicum l
title Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
title_full Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
title_fullStr Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
title_full_unstemmed Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
title_short Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry
title_sort sources of variation in assessing canopy reflectance of processing tomato by means of multispectral radiometry
topic passive sensor
sampling methodology
bootstrap analysis
vegetation indices
green ratio of vegetation index
nir/560 or gvi (green vegetation index)
green normalized difference vegetation index
normalized difference vegetation index on greenness (g-ndvi)
soil mulching
solanum lycopersicum l
url https://www.mdpi.com/1424-8220/19/21/4730
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AT giuseppinapennisi sourcesofvariationinassessingcanopyreflectanceofprocessingtomatobymeansofmultispectralradiometry
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