Using air thermal time to predict the time course of seedling emergence of Avena sterilis subsp. sterilis (sterile oat) under Mediterranean climate

Avena sterilis subsp. sterilis (sterile oat) is a troublesome grass weed of winter cereals both in its native range encompassing the Mediterranean up to South Asia, and in regions of America, Northern Europe and Australia where it is introduced. A better understanding of seedling emergence patterns of this weed in cereal fields can help control at early growth stages benefiting efficacy under a changing climate. With this aim, the objective of this research was to develop and validate a field emergence model for this weed based on cumulative air thermal time (CTT, ℃ day). Experiments for model setting and evaluation were carried out in experimental and commercial fields in southern Spain. Two alternative models, Gompertz and Weibull, were compared for their ability to represent emergence time course. The Weibull model provided the best fit to the data. Evaluation through independent experiments showed good model performance in predicting seedling emergence. According to the developed model, the onset of emergence takes place at 130 CTT, and 50% and 90% emergence is achieved at 448 and 632 CTT, respectively. Results indicate that this model could be useful for growers as a tool for decision-making in A. sterilis control

Wheat Yield Gap Assessment in Using the Comparative Performance Analysis (CPA)

One of the crucial issues in developing nations is diminishing the yield gaps. Therefore, accurate yield gap estimation has many real-world uses for increasing crop production. Utilizing comparative performance analysis (CPA) techniques, the yield gap of wheat fields was evaluated in this study. In Varamin, Tehran Province, Iran, data on 104 wheat fields were collected between 2018 and 2020 and every aspect of wheat field management has been documented. The CPA model determines the yield gap’s contributing factors and potential yield. The results of data analysis revealed that the production ranged from 2600 to 7600 kg ha−1. The CPA method predicted a potential yield of 9316 kg ha−1 and found a yield gap of 3748 kg ha−1; this amount was 40.23% of the potential yield. Leaf chlorophyll (29%), irrigation at stem extension (9%), LAI (7.7%), soil salinity (8.2%), field area (16.3%), phosphorus consumption (6%), nitrogen utilized at the stage of tillering (16%), and HI (7.8%) all contributed to the yield gap in the CPA. It has been said that the computed yield in CPA is a potential yield that can be reached. CPA is a cheap and straightforward tool that could identify yield gaps and their causes in a district without the need for costly experiments. Therefore, developing nations with significant efficiency and yield gaps can use these techniques effectively