81 research outputs found
Physiological Adaptation to Water Salinity in Six Wild Halophytes Suitable for Mediterranean Agriculture
No full textOwing to the high interspecific biodiversity, halophytes have been regarded as a tool for understanding salt tolerance mechanisms in plants in view of their adaptation to climate change. The present study addressed the physiological response to salinity of six halophyte species common in the Mediterranean area: Artemisia absinthium, Artemisia vulgaris, Atriplex halimus, Chenopodium album, Salsola komarovii, and Sanguisorba minor. A 161-day pot experiment was conducted, watering the plants with solutions at increasing NaCl concentration (control, 100, 200, 300 and 600 mM). Fresh weight (FW), leaf stomatal conductance (GS), relative water content (RWC) and water potential (WP) were measured. A principal component analysis (PCA) was used to describe the relationships involving the variables that accounted for data variance. A. halimus was shown to be the species most resilient to salinity, being able to maintain FW up to 300 mM, and RWC and WP up to 600 mM; it was followed by C. album. Compared to them, A. vulgaris and S. komarovii showed intermediate performances, achieving the highest FW (A. vulgaris) and GS (S. komarovii) under salinity. Lastly, S. minor and A. absinthium exhibited the most severe effects with a steep drop in GS and RWC. Lower WP values appeared to be associated with best halophyte performances under the highest salinity levels, i.e., 300 and 600 mM NaCl
Agronomic Strategies to Improve N Efficiency Indices in Organic Durum Wheat Grown in Mediterranean Area
No full textOrganic farming systems are often constrained by limited soil nitrogen (N) availability. Here we evaluated the effect of foliar organic N and sulphur (S), and selenium (Se) application on durum wheat, considering N uptake, utilization efficiency (NUtE), grain yield, and protein concentration as target variables. Field trials were conducted in 2018 and 2019 on two old (Cappelli and old Saragolla) and two modern (Marco Aurelio and Nadif) Italian durum wheat varieties. Four organic fertilization strategies were evaluated, i.e., the control (CTR, dry blood meal at sowing), the application of foliar N (CTR + N) and S (CTR + S), and their joint use (CTR + NS). Furthermore, a foliar application of sodium selenate was evaluated. Three factors—variety, fertilization strategies and selenium application—were arranged in a split-split-plot design and tested in two growing seasons. The modern variety Marco Aurelio led to the highest NUtE and grain yield in both seasons. S and N applications had a positive synergic effect, especially under drought conditions, on pre-anthesis N uptake, N translocation, NUtE, and grain yield. Se treatment improved post-anthesis N uptake and NUtE, leading to 17% yield increase in the old variety Cappelli, and to 13% and 14% yield increase in Marco Aurelio and Nadif, mainly attributed to NUtE increase. This study demonstrated that the synergistic effect of foliar applications could improve organic durum wheat yields in Mediterranean environments, especially on modern varieties
Individuation of the best agronomic practices for organic durum wheat cultivation in the Mediterranean environment: a multivariate approach
No full textThe main challenge of organic cereal systems is ensuring high yields and grain quality while maintaining pedo-environmental sustainability. Despite the potential benefits of organic farming systems, a debated limitation is their actual contribution to food security. Durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.], one of the
most important staple food crops, is mainly grown in the Mediterranean environments, where farmers have to face profound inter-annual fluctuations in productions, expecially under organic system, due to prolonged drought and heat spells. With the overarching objective of deriving practical indications to support organic wheat production in
the Mediterranean region, we tested the effect of nitrogen and sulphur-based organic foliar fertilizers on two ancient and two modern durum wheat varieties grown in two seasons (2018–2019) characterized by different weather conditions. Moreover, we evaluated the effect of a foliar application of Selenium at booting on grain yield and quality. Results from the Principal Component analysis revealed that seasonal weather and the varietal choice determined most of the variability of yield and quality traits, while Selenium application markedly affected the performance of organic durum wheat, especially in the milder season. The Cluster Analysis computed on the Principal
Components revealed three groups, representative of (i) the modern variety, Marco Aurelio, grown in the dryest season (average yield, low protein content), (ii) all varieties grown in 2018, with the addition of sodium selenate (high yield, high protein content), and (iii) the ancient variety, Cappelli, grown in both seasons (low yield, average protein
content). This study evidenced that tailored agronomic practices are needed to sustain the organic durum wheat systems in the Mediterranean area. The promising beneficial effect of Selenium would deserve a dedicated research program, where additional experiments should further investigate its impact on organic durum wheat yield and
quality. The multivariate approach permitted us to identify the most effective agronomic practices in relation to different environmental conditions; the outputs from this study are ready to be transferred to organic farmers aiming at improving the performance of durum wheat systems and at providing an effective contribution to food security
Evolutionary trends and phylogenetic association of key morphological traits in the Italian rice varietal landscape
No full textEfficient germplasm exploitation in crop breeding requires comprehensive knowledge of the available genetic diversity. Linking molecular data to phenotypic expression is fundamental for the profitable utilisation of genetic resources. Italian rice germplasm is an invaluable source of genes, being characterised by marked heterogeneity. A phenotypic characterisation is presented in this paper, with a focus on the evolutionary trends, and on the comparison with available molecular studies. A panel of 351 Italian rice varieties was analysed using seven key morphological traits, employing univariate and multivariate analyses. Considerable variability was found, with clear morphological trends towards reduced plant height, earliness, and spindle-shaped caryopses. Previous findings indicating that genetic diversity was maintained throughout time could not be confirmed, as small phenotypic variability was found in the most recent rice varieties. Consistency with phylogenetic data from previous studies was partial: one phylogenetic subgroup was phenotypically well distinct, while the others had overlapping characteristics and encompassed a wide range of phenotypic variation. Our study provides a quantitative ready-to-use set of information to support new breeding programs, as well as the basis to develop variety-specific calibrations of eco-physiological models, to identify promising traits in light of climate change conditions and alternative management scenarios
Multi metric evaluation of leaf wetness models for large-area application of plant disease models
No full textLeaf wetness (LW) is one of the most important input variables of disease simulation models because of its fundamental role in the development of the infection process of many fungal pathogens. The low reliability of LW sensors and/or their rare use in standard weather stations has led to an increasing demand for reliable models that are able to estimate LW from other meteorological variables. When working on large databases in which data are interpolated in grids starting from weather stations, LW estimation is often penalized by the lack of hourly inputs (e.g., air relative humidity and air temperature), leading researchers to generate such variables from the daily values of the available weather data.
Although it is possible to find several papers about models for the estimation of LW, the behavior and reliability of these models were never assessed by running them with inputs at different time resolutions aiming at large-area applications. Furthermore, only a limited number of papers have assessed the suitability of different LW models when used to provide inputs to simulate the development of the infection process of fungal pathogens. In this paper, six LW models were compared using data collected at 12 sites across the U.S. and Italy between 2002 and 2008 using an integrated, multi metric and fuzzy-based expert system developed ad hoc. The models were evaluated for their capability to estimate LW and for their impact on the simulation of the infection process for three pathogens through the use of a potential infection model. This study indicated that some empirical LW models performed better than physically based LW models. The classification and regression tree (CART) model performed better than the other models in most of the conditions tested. Finally, the estimate of LW using hourly inputs from daily data led to a decline of the LW models performances, which should still be considered acceptable. However, this estimate may require further work in data collection and model evaluation for applications at finer spatial resolutions aimed at decision support systems
Promoting sustainable tomato irrigation strategies in Mediterranean conditions via simulation modelling
No full textAn agro-physiological dataset on industrial tomatoes from nine years of field experiments conducted with alternative water-saving strategies in Mediterranean environments
No full textThe availability of field experimental data plays a piv- otal role in advancing agricultural research, particularly in the Mediterranean, where farmers face significant chal- lenges due to water scarcity and changing climatic condi- tions. We present a multi-year homogenized dataset of agro- physiological traits collected on industrial tomatoes and fo- cused on the effect of deficit irrigation (DI). The dataset has been compiled over nine years and comprises 100 experi- mental plots, where 32 DI strategies have been tested. Vi- sual observations on tomato phenology and qualitative and quantitative production data have been collected in field and laboratory surveys, complemented with detailed information on pedo-climatic conditions and irrigation scheduling (tim- ing and volume). Researchers can find in this dataset a rich source for calibrating and evaluating agro-physiological mod- els and a reference basis to study the relationships between DI strategies, weather variability, and the performance of tomato growing systems. Agronomists from the public and private sectors can gain domain knowledge to support local farmers with the best DI strategies to achieve high yields while optimizing water use. Moreover, this dataset serves as ground truth for digital decision support systems, which need real-world data to enhance their accuracy in guiding farmers on efficient water use. This data source is intended to become a crucial asset for researchers, agronomists, and decision-makers in the Mediterranean as it bridges the gap between research and practice in an area where farmers are already striving with water scarcity for industrial tomato cultivation
A model for simulating the height of rice plants
No full textA reliable approach for modelling rice plant height would allow the simulation of processes with a significant impact on yields, e.g., lodging, floodwater effect on leaves temperature, crop-weeds competition for radiation interception. In this paper we present a new model for the simulation of rice plant height based on the integral of the percentage of biomass partitioned to stems. The model was compared with four alternative approaches using data collected during eight experiments carried out in Russia, Japan and US between 1991 and 2000, proving to be the most accurate in reproducing plant height during the whole crop cycle. RRMSE ranged between 8.02% and 20.87%, modelling efficiency was always close to one and the absolute value of coefficient of residual mass never exceeded 0.16. It resulted also the most robust and the less complex (according to the Akaike's Information Criterion) among those compared. The model presents a lower level of empiricism with respect to the other approaches found in the literature, deriving plant height from the allocation of biomass to stems, which are the plant organs most involved in determining canopy height. This model represents a suitable base for further developments aiming at including the effect of management practices (e.g., fluctuating water depth) and environmental factors (e.g., crop-weeds competition for radiation interception). Moreover, the low input requirements favour its inclusion in operational cropping systems models
Identifying the most promising agronomic adaptation strategies for the tomato growing systems in Southern Italy via simulation modeling
No full textThe main cultivation area of the Italian processing tomato is the Southern Capitanata plain. Here, the hardest agronomic challenge is the optimization of the irrigation water use, which is often inefficiently performed by farmers, who tend to over-irrigate. This could become unsustainable in the next years, given the negative impacts of climatic changes on groundwater availability and heat stress intensification. The aim of the study was to identify the most promising agronomic strategies to optimize tomato yield and water use in Capitanata, through a modeling study relying on an extensive dataset for model calibration and evaluation (22 data sets in 2005–2018). The TOMGRO simulation model was adapted to open-field growing conditions and was coupled with a soil model to reproduce the impact of water stress on yield and fruit quality. The new model, TomGro_field, was applied on the tomato cultivation area in Capitanata at 5×5 km spatial resolution using an ensemble of future climatic scenarios, resulting from the combination of four General Circulation Models, two extreme Representative Concentration Pathways and five 10-years time frames (2030–2070). Our results showed an overall negative impact of climate change on tomato yields (average decrease=5–10%), which could be reversed by i) the implementation of deficit irrigation strategies based on the restitution of 60–70% of the crop evapotranspiration, ii) the adoption of varieties with longer cycle and iii) the anticipation of 1–2 weeks in transplanting dates. The corresponding irrigation amounts applied are around 360 mm, thus reinforcing that a rational water management could be realized. Our study provides agronomic indications to tomato growers and lays the basis for a bio-economic analysis to support policy makers in charge of promoting the sustainability of the tomato growing systems
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