Integrating NDVI and agronomic data to optimize the variable-rate nitrogen fertilization

Abstract The success of Variable Rate Application (VRA) techniques is closely linked to the algorithm used to calculate the different fertilizer rates. In this study, we proposed an algorithm based on the integration between some estimated agronomic inputs and crop radiometric data acquired by using a multispectral sensor. Generally, VRA algorithms are evaluated by comparing the yields, but they can often be affected by factors acting in the final phase of the crop cycle and not dependent on the fertilization treatments. Therefore, we decided to compare our algorithm (ALG) versus the traditional application of fertilizer (TRD) by evaluating the crop growth 1.5 months after the fertilization time. The algorithm was tested on a sorghum crop under organic farming, managed with or without manure. The saving of N obtained with ALG was equal to 14 and 5 kg ha − 1 (-14 and − 10% for the non-manure and fertilized treatments, respectively). The NDVI values acquired after fertilization showed a remarkable reduction of relative standard deviation for ALG system (from 22 to 9% and from 34 to 14% for manured and not manured, respectively), which was not found for TRD system (from 16 to 17% and from 29 to 18% for manured and not manured, respectively). The above ground biomass produced was statistically equivalent for the two systems in the manured plots and significant higher for ALG in not-manured plots (+ 0.74 t ha − 1 of dm, equal to + 23%). Finally, the indices calculated to evaluate the Nitrogen Use Efficiency (NUE) were consistently better in the ALG theses.

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Publication Details

Journal
Precision Agriculture
Published
2024-09-09
DOI
https://doi.org/10.1007/s11119-024-10185-2
Citations
11
Primary Topic
Crop Yield and Soil Fertility
Type
article
Field-Weighted Citation Impact
6.24

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article

Integrating NDVI and agronomic data to optimize the variable-rate nitrogen fertilization

Nicola Silvestri, Nicola Grossi, Massimiliano Ruggeri, Leonardo Ercolini
11 citations
Precision Agriculture
Crop Yield and Soil Fertility
6.24
article

Integrating NDVI and agronomic data to optimize the variable-rate nitrogen fertilization

Nicola Silvestri, Nicola Grossi, Massimiliano Ruggeri, Leonardo Ercolini
article en
11 citations

Abstract

Abstract The success of Variable Rate Application (VRA) techniques is closely linked to the algorithm used to calculate the different fertilizer rates. In this study, we proposed an algorithm based on the integration between some estimated agronomic inputs and crop radiometric data acquired by using a multispectral sensor. Generally, VRA algorithms are evaluated by comparing the yields, but they can often be affected by factors acting in the final phase of the crop cycle and not dependent on the fertilization treatments. Therefore, we decided to compare our algorithm (ALG) versus the traditional application of fertilizer (TRD) by evaluating the crop growth 1.5 months after the fertilization time. The algorithm was tested on a sorghum crop under organic farming, managed with or without manure. The saving of N obtained with ALG was equal to 14 and 5 kg ha − 1 (-14 and − 10% for the non-manure and fertilized treatments, respectively). The NDVI values acquired after fertilization showed a remarkable reduction of relative standard deviation for ALG system (from 22 to 9% and from 34 to 14% for manured and not manured, respectively), which was not found for TRD system (from 16 to 17% and from 29 to 18% for manured and not manured, respectively). The above ground biomass produced was statistically equivalent for the two systems in the manured plots and significant higher for ALG in not-manured plots (+ 0.74 t ha − 1 of dm, equal to + 23%). Finally, the indices calculated to evaluate the Nitrogen Use Efficiency (NUE) were consistently better in the ALG theses.

Precision AgricultureVol. 25(5)
University of Pisa (IT), National Research Council (IT)
European Commission, Università di Pisa
Openalex Percentile: Top 3%
Crop Yield and Soil Fertility
6.24
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Integrating NDVI and agronomic data to optimize the variable-rate nitrogen fertilization — Nicola Silvestri, Nicola Grossi, et al. · Precision Agriculture (2024) | TGRS Research Map | TGRS