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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766790/ https://www.ncbi.nlm.nih.gov/pubmed/31505810 http://dx.doi.org/10.3390/s19183881 |
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author | Gabriel, Jose Luis Quemada, Miguel Alonso-Ayuso, María Lizaso, Jon I. Martín-Lammerding, Diana |
author_facet | Gabriel, Jose Luis Quemada, Miguel Alonso-Ayuso, María Lizaso, Jon I. Martín-Lammerding, Diana |
author_sort | Gabriel, Jose Luis |
collection | PubMed |
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(®) and Dualex(®)) 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. |
format | Online Article Text |
id | pubmed-6766790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67667902019-10-02 Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing Gabriel, Jose Luis Quemada, Miguel Alonso-Ayuso, María Lizaso, Jon I. Martín-Lammerding, Diana Sensors (Basel) Article 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(®) and Dualex(®)) 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. MDPI 2019-09-09 /pmc/articles/PMC6766790/ /pubmed/31505810 http://dx.doi.org/10.3390/s19183881 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gabriel, Jose Luis Quemada, Miguel Alonso-Ayuso, María Lizaso, Jon I. Martín-Lammerding, Diana Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766790/ https://www.ncbi.nlm.nih.gov/pubmed/31505810 http://dx.doi.org/10.3390/s19183881 |
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