2002Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Precision farming through variable fertilizer application by automated detailed tracking of in-season crop properties

M. Reyniers, Els Vrindts, Koenraad Dumont, Josse De Baerdemaeker

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Abstract

What is lacking in precision farming at present, are more comprehensive and non-destructive methods for obtaining the data needed to prescribe variable treatments. A farmer needs to be informed in order to be efficient, and that includes having the knowledge and information products to forge a viable strategy for farming operations. Current remote sensing (satellite images) sources are too coarse in multispectral spatial resolution and too infrequent in time to allow detailed tracking of phenological stages during the growing season. In this research very detailed and automated on-the-go optical monitoring of the crop is used for detecting and managing zones with different crop yield potential on a seasonal scale. In particular, reflectance properties are used to identify and evaluate optical indicators of the nutritional status of the crop. These indicators should allow site-specific in-seasonal correction of N-application to come to optimal crop yield all over the field. Based on these indicators, site-specific fertilization is done with a variable fertilizer equipped with DGPS. At the end of the season, the crop was harvested with a combine harvester, equipped with precision farming sensors to map final crop yield. In this way final results could be evaluated and analyzed.

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What this paper is about

What is lacking in precision farming at present, are more comprehensive and non-destructive methods for obtaining the data needed to prescribe variable treatments. A farmer needs to be informed in order to be efficient, and that includes having the knowledge and information products to forge a viable strategy for farming operations. Current remote sensing (satellite images) sources are too coarse in multispectral spatial resolution and too infrequent in time to allow detailed tracking of phenological stages during the growing season. In this research very detailed and automated on-the-go optical monitoring of the crop is used for detecting and managing zones with different crop yield potential on a seasonal scale. In particular, reflectance properties are used to identify and evaluate optical indicators of the nutritional status of the crop. These indicators should allow site-specific in-seasonal correction of N-application to come to optimal crop yield all over the field. Based on these indicators, site-specific fertilization is done with a variable fertilizer equipped with DGPS. At the end of the season, the crop was harvested with a combine harvester, equipped with precision farming sensors to map final crop yield. In this way final results could be evaluated and analyzed.

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Available abstract

What is lacking in precision farming at present, are more comprehensive and non-destructive methods for obtaining the data needed to prescribe variable treatments. A farmer needs to be informed in order to be efficient, and that includes having the knowledge and information products to forge a viable strategy for farming operations. Current remote sensing (satellite images) sources are too coarse in multispectral spatial resolution and too infrequent in time to allow detailed tracking of phenological stages during the growing season. In this research very detailed and automated on-the-go optical monitoring of the crop is used for detecting and managing zones with different crop yield potential on a seasonal scale. In particular, reflectance properties are used to identify and evaluate optical indicators of the nutritional status of the crop. These indicators should allow site-specific in-seasonal correction of N-application to come to optimal crop yield all over the field. Based on these indicators, site-specific fertilization is done with a variable fertilizer equipped with DGPS. At the end of the season, the crop was harvested with a combine harvester, equipped with precision farming sensors to map final crop yield. In this way final results could be evaluated and analyzed.

Key concepts: Precision agriculture, Agricultural engineering, Multispectral image, Agriculture, Environmental science, Crop, Growing season, Remote sensing

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