Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin

Abstract

Uncertainty in weather conditions for the forthcoming growing season influences farmers' decisions, based on their experience of the past climate, regarding the reduction of agricultural risk. Early within-season predictions of grain yield can represent a great opportunity for farmers to improve their management decisions and potentially increase yield and reduce potential risk. This study assessed 3 methods of within-season predictions of durum wheat yield at 10 sites across the Mediterranean Basin. To assess the value of within-season predictions, the model SiriusQuality2 was used to calculate wheat yields over a 9 yr period. Initially, the model was run with observed daily weather to obtain the reference yields. Then, yield predictions were calculated at a monthly time step, starting from 6 mo before harvest, by feeding the model with observed weather from the beginning of the growing season until a specific date and then with synthetic weather constructed using the 3 methods, historical, analogue or empirical, until the end of the growing season. The results showed that it is possible to predict durum wheat yield over the Mediterranean Basin with an accuracy of normalized root means squared error of < 20%, from 5 to 6 mo earlier for the historical and empirical methods and 3 mo earlier for the analogue method. Overall, the historical method performed better than the others. Nonetheless, the analogue and empirical methods provided better estimations for low-yielding and high-yielding years, thus indicating great potential to provide more accurate predictions for years that deviate from average conditions.

Contribution of Wild Relatives to Durum Wheat (Triticum turgidum subsp. durum) Yield Stability across Contrasted Environments

“…The crossover interaction due to year effects was more pronounced in the other locations; these effects were mainly associated with the total and distribution of rainfall and temperature for rainfed trials. These findings confirm previously reported effects of weather conditions on the GEI in durum wheat in the Mediterranean basin [3,74,75]. Annoceur was characterized by low heritability during both seasons, and it was among the locations where low genetic gain for durum wheat was achieved [76].…”

Performance of the MARS-crop yield forecasting system for the European Union: Assessing accuracy, in-season, and year-to-year improvements from 1993 to 2015

“…In the MCYFS, the statistical methods used have inherent flaws, for instance when it comes to unprecedented conditions or yield levels that are out of the usual range of expectations. In recent years an increasing amount of publications have appeared on crop forecasting using a variety of novel methods and approaches ( Becker-Reshef et al, 2010 ; Ceglar et al, 2016 ; Iizumi et al, 2013 ; Ferisse et al, 2015 ; Schauberger et al, 2017 ; Sharif et al, 2017 ) including probabilistic approaches (e.g. Ben-Ari et al, 2016 ), random forest (e.g.…”

Potential impacts of projected warming scenarios on winter wheat in the UK

“…The current climate patterns are causing gradual warming of Earth, with the last 5 years (2015–2019) being among the world's warmest while 9 out of 10 warmest years that have been recorded since 2005 (NOAA 2020). The impacts of increased temperature on crop development, yield and quality has been well documented (Porter and Gawith, 1999; Semenov, 2008; Ferrise et al ., 2014; Semenov and Stratonovitch, 2014; Trnka et al ., 2014; Asseng et al ., 2015, 2019). In a study where statistical and process-based models were compared, it has been found that global wheat production will fall by 4–6% per °C of air temperature increase (Liu et al ., 2016).…”