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Open AccessArticle

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

1
Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-INAGEA), 28040 Madrid, Spain
2
CEIGRAM, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(18), 3881; https://doi.org/10.3390/s19183881
Received: 30 June 2019 / Revised: 5 September 2019 / Accepted: 6 September 2019 / Published: 9 September 2019
(This article belongs to the Special Issue Proximal Sensing for Nitrogen Management)
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. View Full-Text
Keywords: chlorophyll; polyphenol; nutrient deficiency; fertilization; precision agriculture chlorophyll; polyphenol; nutrient deficiency; fertilization; precision agriculture
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MDPI and ACS Style

Gabriel, J.L.; Quemada, M.; Alonso-Ayuso, M.; Lizaso, J.I.; Martín-Lammerding, D. Predicting N Status in Maize with Clip Sensors: Choosing Sensor, Leaf Sampling Point, and Timing. Sensors 2019, 19, 3881.

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