Sunn hemp (Crotalaria juncea L.) is a fast growing, drought tolerant legume crop with potential as a biomass feedstock for advanced biofuels in Southern Europe, grown in either a single or double crop system. This study presents a new simulation model, SunnGro, which reproduces sunn hemp productivity, while providing a detailed description of leaf/branch size heterogeneity and its evolution during the vegetative season. The model was calibrated and validated using 20 field datasets collected from 2016 to 2018 in Greece, Spain, and Italy under non-limiting soil water conditions. High correlation between the simulated and measured values of branch number (R2 = 0.80), leaf number (R2 = 0.92), and biomass accumulation (0.67 < R2 < 0.82) demonstrated good model predictivity across sites, seasons, alternative sowing densities, dates, and harvest times. An uncertainty analysis was carried out under varying seasonal air temperatures and sowing times in five European locations to explore the capability of the model to identify the best agronomic practices for maximizing sunn hemp yield. Therefore, the current version of SunnGro is an effective tool for scenario analyses under varying management practices and changing climatic conditions.

Parenti A., Cappelli G., Zegada-Lizarazu W., Martin Sastre C., Christou M., Monti A., et al. (2021). SunnGro: A new crop model for the simulation of sunn hemp (Crotalaria juncea L.) grown under alternative management practices. BIOMASS & BIOENERGY, 146(March 2021), 1-16 [10.1016/j.biombioe.2021.105975].

SunnGro: A new crop model for the simulation of sunn hemp (Crotalaria juncea L.) grown under alternative management practices

Parenti A.
;
Cappelli G.;Zegada-Lizarazu W.;Monti A.;
2021

Abstract

Sunn hemp (Crotalaria juncea L.) is a fast growing, drought tolerant legume crop with potential as a biomass feedstock for advanced biofuels in Southern Europe, grown in either a single or double crop system. This study presents a new simulation model, SunnGro, which reproduces sunn hemp productivity, while providing a detailed description of leaf/branch size heterogeneity and its evolution during the vegetative season. The model was calibrated and validated using 20 field datasets collected from 2016 to 2018 in Greece, Spain, and Italy under non-limiting soil water conditions. High correlation between the simulated and measured values of branch number (R2 = 0.80), leaf number (R2 = 0.92), and biomass accumulation (0.67 < R2 < 0.82) demonstrated good model predictivity across sites, seasons, alternative sowing densities, dates, and harvest times. An uncertainty analysis was carried out under varying seasonal air temperatures and sowing times in five European locations to explore the capability of the model to identify the best agronomic practices for maximizing sunn hemp yield. Therefore, the current version of SunnGro is an effective tool for scenario analyses under varying management practices and changing climatic conditions.
2021
Parenti A., Cappelli G., Zegada-Lizarazu W., Martin Sastre C., Christou M., Monti A., et al. (2021). SunnGro: A new crop model for the simulation of sunn hemp (Crotalaria juncea L.) grown under alternative management practices. BIOMASS & BIOENERGY, 146(March 2021), 1-16 [10.1016/j.biombioe.2021.105975].
Parenti A.; Cappelli G.; Zegada-Lizarazu W.; Martin Sastre C.; Christou M.; Monti A.; Ginaldi F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/855058
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