The processes of soil erosion and land degradation are more rapid in the case of inappropriate agricultural management, which leads to increased soil loss rates. Moreover, climatic conditions are one of the most important determining factors affecting agriculture, especially in the Mediterranean areas featuring irregular rainfall and high summer temperatures. Conservation agriculture (CA) can make a significant contribution to reducing soil erosion risk on the annual cropland (ACL) of the Mediterranean region in comparison with conventional management (CM). The objective of this study is to provide soil loss rate maps and calculate the values for each altitude and slope class and their combination for the Apulia region in four annual production cycles for the scenarios CM and CA. The present study estimates the significance of the adoption of CA on soil erosion assessment at regional scale based on the Revised Universal Soil Loss Equation (RUSLE) model. The parameters of the RUSLE model were estimated by using remote sensing (RS) data. The erosion probability zones were determined through a Geographic Information System (GIS) and Google Earth Engine (GEE) approach. Digital terrain model (DTM) at 8 m, ACL maps of the Apulia region, and rainfall and soil data were used as an input to identify the most erosion-prone areas. Our results show a 7.5% average decrease of soil loss rate during the first period of adoption of the four-year crop cycle—from 2.3 t ha⁻¹ y⁻¹ with CM to 2.1 t ha⁻¹ y⁻¹ with the CA system. CA reduced soil loss rate compared to CM in all classes, from 10.1% in hill class to 14.1% for hill + low slope class. These results can therefore assist in the implementation of effective soil management systems and conservation practices to reduce soil erosion risk in the Apulia region and in the Mediterranean basin more generally.

The geodatabase on weather-related disasters in agriculture is a part of the cloud storage which hosts the materials of the Observatory for Agricultural meteorology and climatology of the Council for Agricultural Research and Economics (CREA). A specific relational SQL geodatabase has been created by data entry from the official decrees of disaster declaration of the Italian Ministry of Agriculture, food sovereignty and forests within the “National Solidarity Fund for natural disasters in agriculture” (Italian law d.lgs. 102/2004). From this database, managed by CREA for internal research purposes, a dataset has been extracted for the period from 2005 to 2021 and published in the Zenodo repository in text format (.csv file) annotated with discovery and structural metadata. The dataset aims to make available useful data for weather-related risk assessment in agriculture and for agrometeorological analyses of extreme weather events leading to disasters. The following types of weather-related disasters in agriculture are included in the dataset: drought, excess of snow, frost, hail, heat stress, heavy rain leading to flood, persistent rain, tornado, strong wind and sirocco wind. The dataset will be periodically updated.

The present study aimed to chemically and sensorially characterize hop samples, cv Cascade, grown in two different Italian regions (Latium and Tuscany) as well as their derived beers by a multi analytical approach. Significant differences in bitter acid, oil and polyphenol content were observed for hop samples according to their origin. Gas chromatography-olfactometry analysis pointed out floral notes for Tuscany samples, where hops from Latium were characterized by spicy and resinous notes, correlated to the presence of sesquiterpenes. Differences in the molecular fingerprinting were also highlighted by Fourier–Transform Infrared Spectroscopy. The differences found in the hops were reflected in the beers, which were clearly recognized as distinct by a sensory panel. Both beer samples were mainly characterized by six aroma compounds (linalool, geraniol and β-damascenone, citronellol, 2-phenylethyl acetate, and 2-phenylethanol), three of which were potentially responsible for the geographic origin of the hops given their significantly different concentrations.

Knowledge of the flowering dates of black locust trees (Robinia pseudoacacia L.) is crucial information of both economic significance and scientific interest. Black locust is in fact an excellent melliferous plant and can provide information on climate change impacts due to its large distribution throughout the world as planted and naturalized trees. This paper presents the calibration and validation of a phenological model targeted at the simulation of the whole process of black locust flowering (from BBCH 51—inflorescence of flower buds visible—to BBCH 69—end of flowering). The work relies on the phenological observations gathered in the context of IPHEN, the Italian PHEnological Network, with a broad latitudinal distribution of the observational sites (from 37.53° to 46.28° N) and a long time span, from 2010 to 2021. Phenology modeling is based on the Normal Heat Hours approach, which translates air temperature into thermal units based on a plant specific response curve. As meteorological input data, a high resolution (0.045°) gridded dataset was obtained by spatial interpolation of GSOD (NOAA) weather stations.

Agriculture is highly dependent on environmental, climate and weather conditions and on extreme weather events leading to natural disasters. Such events are more and more frequent in Italy, and in the last decades huge public investments were dedicated to risk management policies in agriculture. In order to set an adequate weather-related risk assessment, a robust analysis of the hazard is needed, which requires an agro-meteorological approach to detect the potential impacts of weather extremes on agricultural activities. With the aim of assessing the effectiveness of the current risk management policy in catching the main hazards, specific agro-meteorological indices were applied to highlight occurrence, trends, and spatial patterns of extreme events. The analysis was based on reanalysis datasets and focused on a study area in Southern Italy (Campania region) during the 1981–2021 period. The findings are reported in terms of maps and statistics aggregated at administrative unit level (5 provinces) and show a general intensification of weather extremes in the last decades, both in frequency and intensity of the events. The main indications refer to growth rates of heavy precipitation, potentially leading to flood, locally exceeding 3–4 mm/year, an increasing number of months with severe/extreme droughts, mainly concentrated during the growing season. An upward trend was also observed for days with extreme maximum temperatures, which already exceeded or approached 50% between June and September in the 1981–2021 period in most areas. Maximum temperatures above 35 °C are becoming more frequent and in the inner areas they were reached in 10 days in the 2021 summer quarter. On the other hand, no significant trends were detected for late frosts. In terms of policy implications, the results seem to suggest that some extreme weather events can no longer be considered as exceptional at the present time and in a trend perspective, making them less suitable to be addressed through the risk management tools based almost exclusively on the strategy of transferring risks (insurances and more recent mutual funds) both for farmers and for the allocation of public resources. Therefore, the need is underlined for improving the design of the risk management policies to increase farms’ resilience and adaptation to climate change. Moreover, the study highlights the information potential of agro-meteorological indices in supporting evidence-based decision making in agriculture.