Future climate will reshape inter-row grass mowing in vineyards: A modelling approach for optimized agronomic management

Climate change exerts mounting pressure on major agroecosystems, jeopardizing both their productivity and long-term sustainability. Vineyards, as multi-layer cropping systems, require effective inter-row management to improve grape production and sustain the provision of ecosystem services. Crop models predict the dynamics of the distinct vegetation layers in the system and support the optimization of inter-row practices. In this study, the original UNIFI.GrapeML vine growth model was integrated with a new module to simulate the daily inter-row grass growth in conjunction with the development of the main crop. The model was calibrated and validated in two vineyards located in the Piedmont region. The results showed satisfactory performance simulating grass growth (r = 0.79, RMSE = 31.3 g d.m. m -2 ) and fractional transpirable soil water (r = 0.93, RMSE = 0.17), for grassed and tilled inter-rows. Moreover, the UNIFI.GrapeML showed satisfactory performance in simulating vine phenology (r = 0.69, RMSE = 6.7 days, on average among all phenological phases), pruned shoot weight (r = 0.74, RMSE = 39.0 g d.m. m -2 ) and yield (r = 0.55, RMSE = 66.1 g d.m. m -2 ), in both vineyards. Once validated, the integrated model was applied to assess grass growth in SSP1 2.6, SSP2 4.5 and SSP5 8.5. Under future climates, the model demonstrated that the onset of grass growth occurred earlier, and the frequency of required cuts between March and November increased from a minimum of +4.2% in SSP2 4.5 to a maximum of +5.7% in SSP1 2.6 compared to the present. Furthermore, simulated grass growth trends revealed different redistribution of operating costs and CO 2 emissions for mowing throughout the season. This study demonstrates that UNIFI.GrapeML could guide inter-row management within vineyards under future climates, optimizing production and mitigating the environmental impact of viticulture. • Optimizing inter-row agronomic management is fundamental to improve vineyard sustainability • UNIFI.GrapeML model simulates grass growth under different inter-row managements • A general increase in inter-row mowings was simulated for future climates • The grass mowing varies seasonally with fluctuations in costs and CO 2 emissions

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Publication Details

Journal
Italian Journal of Agronomy
Published
2025-10-23
DOI
https://doi.org/10.1016/j.ijagro.2025.100059
Primary Topic
Horticultural and Viticultural Research
Type
article
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article

Future climate will reshape inter-row grass mowing in vineyards: A modelling approach for optimized agronomic management

Lorenzo Brilli, Giorgio Capello, Marko Simeunović, Nicolina Staglianó et al.
Italian Journal of Agronomy
Horticultural and Viticultural Research
article

Future climate will reshape inter-row grass mowing in vineyards: A modelling approach for optimized agronomic management

Lorenzo Brilli, Giorgio Capello, Marko Simeunović, Nicolina Staglianó, Elisa Paravidino, Luisa Leolini, Marco Bindi, Kruna Ratković, Simone Bussotti, Marco Moriondo, Camilla Dibari, Giovanni Argenti, Riccardo Rossi, Sergi Costafreda-Aumedes, Gloria Padovan, Marcella Biddoccu, Michele Moretta, Anna Rita Balingit, M. Coli
article en

Abstract

Climate change exerts mounting pressure on major agroecosystems, jeopardizing both their productivity and long-term sustainability. Vineyards, as multi-layer cropping systems, require effective inter-row management to improve grape production and sustain the provision of ecosystem services. Crop models predict the dynamics of the distinct vegetation layers in the system and support the optimization of inter-row practices. In this study, the original UNIFI.GrapeML vine growth model was integrated with a new module to simulate the daily inter-row grass growth in conjunction with the development of the main crop. The model was calibrated and validated in two vineyards located in the Piedmont region. The results showed satisfactory performance simulating grass growth (r = 0.79, RMSE = 31.3 g d.m. m -2 ) and fractional transpirable soil water (r = 0.93, RMSE = 0.17), for grassed and tilled inter-rows. Moreover, the UNIFI.GrapeML showed satisfactory performance in simulating vine phenology (r = 0.69, RMSE = 6.7 days, on average among all phenological phases), pruned shoot weight (r = 0.74, RMSE = 39.0 g d.m. m -2 ) and yield (r = 0.55, RMSE = 66.1 g d.m. m -2 ), in both vineyards. Once validated, the integrated model was applied to assess grass growth in SSP1 2.6, SSP2 4.5 and SSP5 8.5. Under future climates, the model demonstrated that the onset of grass growth occurred earlier, and the frequency of required cuts between March and November increased from a minimum of +4.2% in SSP2 4.5 to a maximum of +5.7% in SSP1 2.6 compared to the present. Furthermore, simulated grass growth trends revealed different redistribution of operating costs and CO 2 emissions for mowing throughout the season. This study demonstrates that UNIFI.GrapeML could guide inter-row management within vineyards under future climates, optimizing production and mitigating the environmental impact of viticulture. • Optimizing inter-row agronomic management is fundamental to improve vineyard sustainability • UNIFI.GrapeML model simulates grass growth under different inter-row managements • A general increase in inter-row mowings was simulated for future climates • The grass mowing varies seasonally with fluctuations in costs and CO 2 emissions

Italian Journal of AgronomyVol. 20(4)
University of Donja Gorica (ME), Institute for Sustainable Plant Protection (IT), Centro di Ricerca per l’Orticoltura (IT), Institute of Biosciences and Bioresources (IT), Ambiente Italia (Italy) (IT), University of Florence (IT)
Openalex Percentile: Top 78%
Horticultural and Viticultural Research
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