Open AccessCriteria for Selecting Optimal Nitrogen Fertilizer Rates for Precision Agriculture
Author(s) -
Bruno Basso,
Davide Cammarano,
Peter Grace,
Giovanni Cafiero,
Luigi Sartori,
Michele Pisante,
Giuseppe Landi,
S. de Franchi,
Francesco Basso
Publication year - 2009
Publication title -
italian journal of agronomy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 24
eISSN - 2039-6805
pISSN - 1125-4718
DOI - 10.4081/ija.2009.4.147
Subject(s) - precision agriculture , yield (engineering) , fertilizer , environmental science , crop simulation model , agriculture , stability (learning theory) , variable (mathematics) , agricultural engineering , sustainability , soil science , ground truth , crop , mathematics , agronomy , ecology , computer science , biology , materials science , engineering , mathematical analysis , machine learning , metallurgy
Yield rates vary spatially and maps produced by the yield monitor systems are evidence of the degree of withinfield variability. The magnitude of this variability is a good indication of the suitability of implementing a spatially variable management plan. Crop simulation models have the potential to integrate the effects of temporal and multiple stress interaction on crop growth under different environmental and management conditions. The strength of these models is their ability to account for stress by simulating the temporal interaction of stress on plant growth each day during the season. The objective of paper is to present a procedure that allows for the selection of optimal nitrogen fertilizer rates to be applied spatially on previously identified management zones through crop simulation modelling. The integration of yield maps, remote sensing imagery, ground truth measurements, electrical resistivity imaging allowed for the identifications of three distinct management zones based on their ability to produce yield and their stability over time (Basso et al., 2009). After validating the model, we simulated 7 N rates from 0 to 180 kg N/ha with a 30 kg N/ha increment. The model results illustrate the different N responses for each of the zone. The analysis allowed us to identify the optimal N rate for each of the zone based on agronomic, economic and environmental sustainability of N management