Istituto Sperimentale Agronomico

In recent years, there has been an intensification of weather variability worldwide as a result of climate change. Some regions have been affected by drought, while others have experienced more intense rainfall. The incidence and severity of mouldy grain and mycotoxin contamination during the growing and harvesting seasons have increased as a result of these weather conditions. Addi-tionally, torrential rains and wet conditions may cause delays in grain drying, leading to mold growth in the field. In July 2023, a wheat field in Lecco (Lombardy, Italy) was affected by torren-tial rains that led to the development of the Claviceps fungi. In the field, dark sclerotia were identi-fied on some ears. Wheat ears, kernels and sclerotia were collected and analyzed by LC-MS/MS at IZSLER, Food Chemical Department, in Bologna. The wheat ears, kernels and sclerotia were ana-lyzed for 12 ergot alkaloids (EAs) according to (EU) Regulation 2023/915 (er-gocornine/ergocorninine; ergocristine/ergocristinine; ergocryptine/ergocryptinine; ergome-trine/ergometrinine; ergosine/ergosinine; ergotamine/ergotaminine), after QuEChERS (Z-Sep/C18) purification. The analyzed sclerotia showed significant differences in total alkaloids content that varies between 0.01-0.5% (w/w), according to the results of 2017 EFSA scientific report. EAs de-tected in sclerotia were up to 4951 mg/kg, in wheat ears up to 33 mg/kg, and in kernels were 1 mg/kg. Additional mycotoxins including ochratoxin A, deoxynivalenol, zearalenone, fumonisins, T2-HT2 toxins, and aflatoxins were investigated in wheat kernels, after purification with immu-noaffinity columns (IAC). The analysis revealed the presence of deoxynivalenol in wheat kernels at a concentration of 2251 µg/kg. It is expected that climate change will increase the frequency of extreme weather events. In order to mitigate the potential risks associated with mycotox-in-producing fungi and to ensure the protection of human health, it is suggested to implement of-ficial controls in the field.

This study investigates the major land use change processes over the 1990–2008 period in Abruzzo region (Central Italy) in relation to the characteristics of the soils and with particular regard to their capability for agricultural purposes, in order to highlight their implications on agricultural productivity. The relative changes in the agricultural incomes and land values were also estimated. To this end, we proposed an inventory approach as a flexible and feasible way for monitoring land use changes at multiple scales. As main outcomes, the shrinkage of agricultural lands and their internal changes (intensification vs. extensification processes) were highlighted. The shrinkage of agricultural lands was strictly related to: (a) reforestation process in mountain areas and less productive lands after land abandonment; and (b) urbanization on plains and more productive lands. Although the intensification process was demonstrated to have a positive effect on the overall regional agricultural incomes, especially on high quality soils, this was not adequate to compensate the economic loss due to the other land use changes, especially in marginal areas and low-to-medium quality soils. Finally, the paper discusses the geographical pattern of land use change processes across the region, including their interrelations and combined effects, and ultimately offers recommendations to decision-makers addressing future sustainable development objectives from local to global scale.

Pot marigold ( Calendula officinalis L.) is the second most commonly-sold medicinal herb in Colombia. The study was performed in Tunja, Colombia, in which chlorophyll and carotenoid content were evaluated in pot marigold grown under low and high light conditions (35% and 100% of full daylight). Chlorophyll fluorescence parameters and electron transport rate were also evaluated. Compared to full sun plants, shaded plants had a higher ratio of chlorophyll a to chlorophyll b, and a lower ratio of carotenoids to chlorophyll. Values for maximum fluorescence ( Fm ), variable fluorescence ( Fv ), and maximum quantum efficiency of photosystem II (the ratio Fv/Fm ) increased in shaded plants, while electron transport rate was reduced. These results suggest that pot marigold plants are very sensitive to low-light conditions.

Soil map is one of the basic tools in any agricultural development planning and generating a digital one is even more effective and more productive for natural resources evaluation. Moreover, remote sensing and GIS have added to soil classification different concept and enforcement. The study aim was to produce digital soil maps for the study area following different classification systems (ST and WRB) and to define the spatial distribution and characteristics all the soil classes in the study area, which will be indispensable for future development planning. This work has been done as a part of the 29^th Course Professional Master in IAO institution, Florence, Italy. The study area was Kilte Awulaelo district in Tigray region, Ethiopia, Which is characterized by different topographies and geomorphologies with different agro ecological conditions. Eleven main soil groups and sixty soil types were identified in the study area. The main soil groups are: Leptosols, Vertisols, Fluvisols, Stagnosols, Kastanozems, Phaeozems, Calcisols, Luvisols, Arenosols, Cambisols and Regosols. Regosols and Cambisols are the dominant soils in the study area which is characteristic soils of rainfed agriculture and land affected by erosion. Using spatial distribution map of each soil group was very helpful to connect soil characteristics with soil forming factors. Lastly, GIS and remote sensing were very effective tools in this study and gave higher value for the final study results.<br />

Four 1 km global land cover products are currently available to the scientific community: the University of Maryland (UMD) global land cover product, the International Geosphere–Biosphere Programme Data and Information System Cover (IGBP‐DISCover), the MODerate resolution Imaging Spectrometer (MODIS) global land cover product and Global Land Cover 2000 (GLC2000). Because of differences in data sources, temporal scales, classification systems and methodologies, it is important to compare and validate these global maps before using them for a variety of studies at regional to global scales. This study aimed to perform the validation and comparison of the four global land cover datasets, and to examine the suitability and accuracy of different coarse spatial resolution datasets in mapping and monitoring cropland across China. To meet this objective, we compared the four global land cover products with the National Land Cover Dataset 2000 (NLCD‐2000) at three scales to evaluate the accuracy of estimates of aggregated cropland areas in China. This was followed by a spatial comparison to assess the accuracies of the four products in estimating the spatial distribution of cropland across China. A comparative analysis showed that there are varying levels of apparent discrepancies in estimating the cropland of China between these four global land cover datasets, and that both area totals and spatial (dis)agreement between them vary from region to region. Among these, the MODIS dataset has the best fit in depicting China's croplands. The coarse spatial resolution and the per pixel classification approach, as well as landscape heterogeneity, are the main reasons for the large discrepancies between the global land cover datasets tested and the reference data.

Arable crops in hilly terrain may experience additional abiotic stress over crops growing in the plain, which affects crop establishment and productivity. We aim to predict risks and sustainability of crops in hilly terrain for current and future climates. In the STAMINA project we include a proper micrometeorological model (MM) to simulate the effects of terrain on atmospheric variables and their impact on crop growth. A generic crop growth model (CGM) is connected to the MM model, simulating growth and development of an arable crop. The model system estimates the distributed components of the soil water and energy balance with reference to standard weather variables, crop and topographic characteristics. Finally, specific risk indicators, e.g. crop water stress index (CWSI) and thermal stress index (TSI), are calculated to characterize yield reduction and to test mitigation options. The model was successfully calibrated for cereals and sugar beet. Here, we give an overview of this new model and present some results for a 5-year simulation scenario for northern Europe, in which we quantified the effects of terrain (slope and aspect) on meteorological variables and crop yields. The effect of topography on productivity was considerable: south-facing aspects were beneficial for winter wheat in wet years (+2.3 t DM ha−1), similar effects were seen for sugar beet.

Abstract Soil moisture and temperature, sowing depth and penetration resistance affect the time and percentage of seedling emergence, which are crucial for the simulation of drought‐limited crop production. The aim of this research was to measure the effect of soil water potential on germination and emergence, shoot and root elongation rates (SER and RER) of two different seed/crop types. Sugar beet and durum wheat seeds were sown into two soils (clay and loam), submitted to five matric potentials (−0.01, −0.1, −0.2, −0.4 and −0.8 MPa) and incubated at constant temperature (25°C) and humidity. Cumulative count analysis was used to estimate parameters of the distribution of germination or emergence times for each box of beet or wheat seeds and to derive estimates for base potentials (ψb), hydrothermal times (H) and numbers of viable units. In a second experiment, NaCl solution was used to mimic the soil matric potentials to estimate potential RER and SER. Germination of sugar beet was slightly more sensitive to matric potential than durum wheat (ψb of −1.13 and −1.23 MPa, respectively). H(g) was longer for sugar beet than for durum wheat (67 vs 47 MPa °Cd). For emergence ψb was similar for both seed types and soils but hydrothermal times (H(e)) were 40 MPa °Cd higher for sugar beet than for wheat. Emergence was about 20 MPa °Cd earlier in loam than in clay. SER measured in soils were similar for both crops and for durum wheat it agreed with those determined in NaCl solution. RER and SER fell with decreasing osmotic potential to approximately 20% of their maximum values (1.03 mm h−1 and 0.57 mm h−1, respectively). Seedling viability decreased with decreasing matric potential and more in clay than in loam soil and more for sugar beet than durum wheat. Seed and soil aggregate size are discussed with respect to the effects of water diffusion and soil–seed contact on germination and emergence modelling.

The objective of this work is to investigate the synergistic use of leaf area index (LAI) retrieved by ENVISAT ASAR data and crop growth models, such as CERES-Wheat, to improve the accuracy of wheat yield predictions. The estimate reliability of CERES-Wheat strongly depends on the accuracy of its numerous inputs, which are not always available or accurate. As a consequence, the model would largely benefit from using updated information on the wheat status, provided by remote sensing at field scale. This work shows that the assimilation of ENVISAT ASAR AP data into the model lead to significant improvements in the wheat dry biomass and the grain yield model predictions.