Modeling approaches have emerged to address uncertainties arising from N₂O emissions variability, representing a powerful methodology to investigate the two emitting processes (i.e., nitrification and denitrification) and to represent the interconnected dynamics among soil, atmosphere, and crops. This work offers an extensive overview of the widely used models simulating N₂O under different cropping systems and management practices. We selected process-based models, prioritizing those with well-documented algorithms found in recently published scientific articles or having published source codes. We reviewed and compared the algorithms employed to simulate N₂O emissions, adopting a unified symbol system. The selected models (APSIM, ARMOSA, CERES-EGC, CROPSYST, CoupModel, DAYCENT, DNDC, DSSAT, EPIC, SPACSYS, and STICS) were categorized by the approaches used to model nitrification and denitrification processes, discriminating between implicit or explicit consideration of the microbial pool and according to the formalization of the main environmental drivers of these processes (soil nitrogen concentration, temperature, moisture, and acidity). Models’ setting and performance assessments were also discussed. From the appraisal of these approaches, it emerged that soil chemical–physical properties and weather conditions are the main drivers of N cycling and the consequent gaseous emissions.

Arable soils significantly contribute to atmosphere pollution through N₂O emissions due to the massive use of N-based fertilizers and soil managements. N₂O formation in the soil occurs mainly through nitrification and denitrification processes, which are influenced by soil moisture, temperature, oxygen concentration, pH, and the amount of available organic carbon and nitrogen. This review synthetically presents the mechanisms of N₂O formation and emission in arable land and some of the current strategies to improve crop nutrient use efficiency. Biological nitrification inhibitor-based agronomic strategies are also presented as future prospects for the sustainable management of crops, which is missing in most of the reviews.

Cover crops are grown in order to provide agro-ecological services and must be terminated before planting the subsequent cash crop. Winterkill termination (by frost damage) depends on the interaction between crop frost hardiness, temperatures and the development stage reached at the time of sub-zero temperature exposure. Remotely sensing intensity, timing and spatial variation of cover crop frost damage can be useful for modeling and planning purposes. Therefore, in this study Sentinel-2 vegetation indices were employed in order to detect frost damage in four white mustard (Sinapis alba L.) fields located in Northern Italy. We estimated the starting date of frost events by means of vegetation indices (EVI, NDRE, NDVI, MMSR, and CCCI); we quantified and mapped frost damage at the sub-field level, using ground-based frost damage measurements carried out during the 2021/2022 season. As to frost damage quantification, MMSR outperformed the other VIs followed by CCCI and EVI (R² > 0.55). The adopted procedure to detect starting dates of frost events was successful in most cases, with a one-day and a four-day delay in the two best cases (NDRE). Finally, maps of frost damage were consistent with its observed spatial variation. We demonstrated that it is possible to employ vegetation indices in order to detect cover crop frost damage and thus assessing cover crop winterkill termination efficiency in the field. Further research is needed, involving additional field monitoring of white mustard in more diverse conditions, and extension of the calibration, as well as validation.

Cover crops provide agro-ecological services like erosion control, improvement of soil quality, reduction of nitrate leaching and weed control. Before planting the subsequent cash crop, cover crops need to be terminated with herbicides, mechanically or with the help of frost (winterkill). Winterkill termination is expected to increase its relevance in the next years, especially for organic farming due to limitations in the use of herbicides and for conservation agriculture cropping systems. Termination by frost depends on complex interactions between genotype, development stage and weather conditions. To understand these interactions for management purposes, crop frost damage models, whose review is the purpose of this article, can be very useful. A literature search led to the collection of eight frost damage models, mainly dedicated to winter wheat. Three of these models are described in detail because they appear suited to adaptation to cover crops. Indeed, they explicitly simulate frost tolerance acquisition and loss as influenced by development stage using a crop frost tolerance temperature, whose rate of variation depends on the processes of hardening and dehardening. This tolerance temperature is compared daily with environmental temperature to calculate frost damage to the vegetative organs. The three models, when applied to winter wheat in Canada, Norway and France, have shown good agreement between measured and simulated crop frost tolerance temperature (when declared, the root mean squared error was 2.4°C). To compare the behaviour of these models, we applied them in two locations with different climatic conditions (temperate climate: Sant’Angelo Lodigiano, Italy, and continental climate: Saskaatoon, Canada) with respect to frost tolerance acquisition. This comparison revealed that the three models provide different simulated dates for the frost damage event in the continental site, while they are more similar in the temperate site. In conclusion, we have shown that the reviewed models are potentially suitable for simulating cover crop frost damage. Highlights - Frost termination is very important for cover crops and needs to be simulated with crop models. - Lacking a cover crop frost damage model, we review eight models simulating damage of cash crops, namely cereals. - Three of these models are also applicable to cover crops and are described in more detail. - The simulated crop frost tolerance temperature decreases and increases with hardening and dehardening, respectively. - This tolerance temperature is compared with environmental temperature to calculate frost damage to the crop.