Optimizing precision irrigation of a vineyard to improve water use efficiency and profitability by using a decision-oriented vine water consumption model
While the agronomic and economic benefits of regulated deficit irrigation (RDI) strategies have long been established in red wine grape varieties, spatial variability in water requirements across a vineyard limits their practical application. This study aims to evaluate the performance of an integrated methodology—based on a vine water consumption model and remote sensing data—to optimize the precision irrigation (PI) of a 100-ha commercial vineyard during two consecutive growing seasons. In addition, a cost-benefit analysis (CBA) was conducted of the tested strategy. Using an NDVI generated map, a vineyard with 52 irrigation sectors and the varieties Tempranillo, Cabernet and Syrah was classified in three categories (Low, Medium and High). The proposed methodology allowed viticulturists to adopt a precise RDI strategy, and, despite differences in water requirement between irrigation sectors, pre-defined stem water potential thresholds were not exceeded. In both years, the difference between maximum and minimum water applied in the different irrigation sectors varied by as much as 25.6%. Annual transpiration simulations showed ranges of 240.1–340.8 mm for 2016 and 298.6–366.9 mm for 2017. According to the CBA, total savings of 7090.00 € (2016) and 9960.00 € (2017) were obtained in the 100-ha vineyard with the PI strategy compared to not PI. After factoring in PI technology and labor costs of 5090 €, the net benefit was 20.0 € ha−1 in 2016 and 48.7 € ha−1 in 2017. The water consumption model adopted here to optimize PI is shown to enhance vineyard profitability, water use efficiency and yield.
631 - Agricultura. Agronomia. Maquinària agrícola. Sòls. Edafologia agrícola
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Bellvert, J., M. Mata, X. Vallverdú, C. Paris, and J. Marsal. 2020. "Optimizing Precision Irrigation Of A Vineyard To Improve Water Use Efficiency And Profitability By Using A Decision-Oriented Vine Water Consumption Model". Precision Agriculture. doi:10.1007/s11119-020-09718-2.
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