Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing

Nitrogen (N) losses from agricultural systems increase air and water pollution, and these losses are highly correlated with the excessive fertilization. An adjusted N fertilization is then a key factor in increasing the N fertilizer efficiency, and leaf clip sensors can help to improve it. This stud...

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Main Authors: Jose Luis Gabriel, Miguel Quemada, María Alonso-Ayuso, Jon I. Lizaso, Diana Martín-Lammerding
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/18/3881
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spelling doaj-5380c2392404409399c4c364acdf63dc2020-11-25T02:01:01ZengMDPI AGSensors1424-82202019-09-011918388110.3390/s19183881s19183881Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and TimingJose Luis Gabriel0Miguel Quemada1María Alonso-Ayuso2Jon I. Lizaso3Diana Martín-Lammerding4Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-INAGEA), 28040 Madrid, SpainCEIGRAM, Universidad Politécnica de Madrid, 28040 Madrid, SpainCEIGRAM, Universidad Politécnica de Madrid, 28040 Madrid, SpainCEIGRAM, Universidad Politécnica de Madrid, 28040 Madrid, SpainInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-INAGEA), 28040 Madrid, SpainNitrogen (N) losses from agricultural systems increase air and water pollution, and these losses are highly correlated with the excessive fertilization. An adjusted N fertilization is then a key factor in increasing the N fertilizer efficiency, and leaf clip sensors can help to improve it. This study (combining five different field experiments in Central Spain) tried to identify the ability of the clip sensors in maize N status identification and yield prediction, comparing two different devices (SPAD-502<sup>&#174;</sup> and Dualex<sup>&#174;</sup>) and identifying the best protocol for maize leaf sampling. As a result, the study demonstrated that different leaf clip chlorophyll sensors presented similar results, although some differences appeared at larger N concentrations. Complementary polyphenol information (as flavonol) can improve the maize N deficiency prediction. Moreover, valuable information for a proper sampling protocol was obtained with this study. It proved that the sampling position (in the leaf and in the plant) and sampling time were crucial for a better estimation of the maize N status. Proper fertilization recommendations could be achieved based on clip chlorophyll sensor measurements.https://www.mdpi.com/1424-8220/19/18/3881chlorophyllpolyphenolnutrient deficiencyfertilizationprecision agriculture
collection DOAJ
language English
format Article
sources DOAJ
author Jose Luis Gabriel
Miguel Quemada
María Alonso-Ayuso
Jon I. Lizaso
Diana Martín-Lammerding
spellingShingle Jose Luis Gabriel
Miguel Quemada
María Alonso-Ayuso
Jon I. Lizaso
Diana Martín-Lammerding
Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
Sensors
chlorophyll
polyphenol
nutrient deficiency
fertilization
precision agriculture
author_facet Jose Luis Gabriel
Miguel Quemada
María Alonso-Ayuso
Jon I. Lizaso
Diana Martín-Lammerding
author_sort Jose Luis Gabriel
title Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
title_short Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
title_full Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
title_fullStr Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
title_full_unstemmed Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing
title_sort predicting n status in maize with clip sensors: choosing sensor, leaf sampling point, and timing
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-09-01
description Nitrogen (N) losses from agricultural systems increase air and water pollution, and these losses are highly correlated with the excessive fertilization. An adjusted N fertilization is then a key factor in increasing the N fertilizer efficiency, and leaf clip sensors can help to improve it. This study (combining five different field experiments in Central Spain) tried to identify the ability of the clip sensors in maize N status identification and yield prediction, comparing two different devices (SPAD-502<sup>&#174;</sup> and Dualex<sup>&#174;</sup>) and identifying the best protocol for maize leaf sampling. As a result, the study demonstrated that different leaf clip chlorophyll sensors presented similar results, although some differences appeared at larger N concentrations. Complementary polyphenol information (as flavonol) can improve the maize N deficiency prediction. Moreover, valuable information for a proper sampling protocol was obtained with this study. It proved that the sampling position (in the leaf and in the plant) and sampling time were crucial for a better estimation of the maize N status. Proper fertilization recommendations could be achieved based on clip chlorophyll sensor measurements.
topic chlorophyll
polyphenol
nutrient deficiency
fertilization
precision agriculture
url https://www.mdpi.com/1424-8220/19/18/3881
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