Herbicide resistance is a major weed control issue that threatens the sustainability of rice cropping systems. Its epidemiology at large scale is largely unknown. Several rice weed species have evolved resistant populations in Italy, including multiple resistant ones. The study objectives were to analyze the impact in Italian rice fields of major agronomic factors on the epidemiology of herbicide resistance and to generate a large-scale resistance risk map. The Italian Herbicide Resistance Working Group database was used to generate herbicide resistance maps. The distribution of resistant weed populations resulted as not homogeneous in the area studied, with two pockets where resistance had not been detected. To verify the situation, random sampling was done in the pockets where resistance had never been reported. Based on data from 230 Italian municipalities, three different statistics, stepwise discriminant analysis, stepwise logistic regression, and neural network, were used to correlate resistance distribution in the main Italian rice growing area with seeding type, rotation rate, and soil texture. Through the integration of complaint monitoring, mapping, and neural network analyses, we prove that a high risk of resistance evolution is associated with traditional rice cropping systems with intense monoculture rates and where water-seeding is widespread. This is the first study that determines the degree of association between herbicide resistance and a few important predictors at large scale. It also demonstrates that resistance is present in areas where it had never been reported through extensive complaint monitoring. However, these resistant populations cause medium-low density infestations, likely not alarming rice farmers. This highlights the importance of integrated agronomic techniques at cropping system level to prevent the diffusion and impact of herbicide resistance or limit it to an acceptable level. The identification of concise, yet informative, agronomic predictors of herbicide resistance diffusion can significantly facilitate effective management and improve sustainability.

<p>Barley is a widespread crop in the Mediterranean area and in temperate climates. Barley impact in the food chain is very important for its value as food and feed. The societal demand is for more productive varieties, which can be able to cope with the current and future climate scenarios. Change in climate is expected to result in more adverse conditions for the barley growth and alter land suitability in its growing regions, such as the Mediterranean basin. In this context, laboratory and modelling activities for the so-called “in silico ideotyping” can be effectively carried out to design new germplasms and to define optimal field management practices. As a first step to reach this objective, we collate the available scientific research about the identification of optimal phenotypic traits for the adaptation to harsh environments. In the framework of the GENDIBAR project (Utilization of local genetic diversity for studying barley adaptation to harsh environments and for pre-breeding; PRIMA European Funding Programme), a bibliometric analysis was carried out in the SCOPUS database with the aim to find published papers about barley adaptation in relation to changing climate. The initial query was (barley AND climate AND adaptation); it contained few keywords and resulted in less than 200 publications. By adding (barley AND ideotyping OR barley AND phenotyping), the search reached 450 records. The most comprehensive search was achieved by adding another OR condition (Barley AND future climate OR climate change) that yielded more than 1000 results. Although these records seemed relevant, a deeper analysis showed that less than 5% of these studies are of real interest and moreover the manual screening of the abstracts of all records will require around a month of work. The second query represents a compromise between the simplest query (barley AND climate AND adaptation) and the last query made by three conditions bonded together. This literature search approach highlighted the results of manipulative experiments and modelling studies for deriving phenotyping and agronomic traits to address in-silico ideotyping design. However, the search outcome suggests that there is a gap of knowledge about the barley phenotypic traits needed to cope with climate change in the semi-arid and arid regions of the Mediterranean basin. This approach is expected to further provide useful information for the development of land suitability models, as well as for barley breeding.</p>

<p>Conservation agriculture (CA) involves complex and interactive processes that ultimately determine soil C storage, making it difficult to identify clear patterns, particularly, when the results originate from many experimental studies. To solve these problems, we used the ARMOSA process-based crop model to simulate the contribution of different CA components (minimum soil disturbance, permanent soil cover with crop residues and/or cover crops, and diversification of plant species) to soil organic carbon (SOC) sequestration at 0-30 cm soil depth and to compare it with SOC evolution under conventional agricultural practices. We simulated SOC changes in two sites located in Central Asia (Almalybak, Kazakhstan) and Southern Europe (Lombriasco, Italy), which have contrasting soils, organic carbon contents, climates, crops and management intensity.  Simulations were carried out for the current (1998-2017) and future climatic scenarios (period 2020-2040, scenario Representative Concentration Pathway 6.0).</p><p>Five cropping systems were simulated: conventional systems under ploughing at 25-30 cm with monoculture and  residues removed (Conv–R) or residues retained (Conv+R); no-tillage (NT) with residue retained and crop monocultures; CA and CA with a cover crop, Italian ryegrass (CA+CC). In Conv–R, Conv+R and NT, the simulated monocultures were spring barley in Almalybak and maize in Lombriasco. In CA and CA+CC, crop rotations were winter wheat - winter wheat - spring barley - chickpea in Almalybak; maize - winter wheat - soybean in Lombriasco, together with Italian ryegrass in the +CC options.</p><p>In Lombriasco, conventional systems led to SOC decline of 170-350 kg ha<sup>-1</sup> yr<sup>-1</sup>, whereas, NT and CA prevented the decline and kept it on the slightly positive level under both climate scenarios. A low rate of SOC increase most likely stems from, in addition to climates, the low silt-clay fraction (34%), and thus, more vulnerable to mineralization and decay.</p><p>In Almalybak, SOC loss in conventional systems was 480-560 kg ha<sup>-1</sup> yr<sup>-1</sup> under current climate, and NT prevented the loss only under current climate, but not under the future climate scenario. In contrast, CA allowed for the annual C sequestration of 300 kg ha<sup>-1</sup> and up to 620 kg ha<sup>-1</sup> with cover crops. Under the future climate scenario, the model predicted somewhat less C sequestration under CA, probably, due to the reduction of residue biomass. Particularly, in Southern Kazakhstan, CA has the largest potential for C sequestration under both climate scenarios, twice exceeding the objectives of the “4 per 1000” initiative. This initiative claims that an annual growth rate of 0.4% in the soil carbon stocks, or 4‰ per year, in the first 30-40 cm of soil, would significantly reduce the CO<sub>2</sub> concentration in the atmosphere related to human activities.</p>