Search Results (2,679)

Drought stress is one of the most critical abiotic stresses restricting global crop production, and sorghum plays an important role in arid and semi-arid areas due to its inherent drought tolerance compared to many other cereals. However, significant variation in drought tolerance exists among different sorghum genotypes, which provides an opportunity to dissect the underlying mechanisms. In this study, a drought-tolerant sorghum line (LNR-6) and a drought-sensitive line (LR-2381) were used for comparative analysis. Plants were grown under two water regimes: well-watered conditions (CK, soil water content maintained at 40%) and drought stress (soil water content reduced to 24%). Integrated transcriptomic and non-targeted metabolomic analyses were conducted to investigate the physiological and molecular mechanisms underlying sorghum drought tolerance. Phenotypic analysis showed that drought stress significantly reduced plant height and chlorophyll content in the drought-sensitive genotype, whereas the drought-tolerant genotype showed only minor changes. Transcriptome analysis identified several enriched functional categories of differentially expressed genes between the two genotypes under drought stress. Among them, genes associated with limonene and pinene degradation, photosynthesis, and photosynthesis-antenna proteins were significantly enriched and may be involved in drought-response regulation. Metabolomic analysis revealed significant accumulation of flavonoids and phenylpropanoids under drought conditions. KEGG pathway enrichment further indicated that flavone and flavonol biosynthesis, flavonoid biosynthesis, and phenylpropanoid biosynthesis were the most significantly enriched metabolic pathways. Overall, these findings enhance our understanding of the coordinated transcriptional and metabolic responses underlying drought tolerance in sorghum. Full article

Olive tree (Olea europaea L.) is a major Mediterranean crop, valued for both fruit yield and high-quality oil, yet extreme summer stress, including high temperature, intense irradiance, and water limitation, can substantially reduce productivity and affect oil composition. The objective of the present study was to evaluate the mitigating efficacy of foliar applications of glycine betaine (GB), kaolin (K), and calcium carbonate (CC) under rainfed conditions across three Greek sites on “Koroneiki” (in two sites) and “Lianolia Kerkyras” (in one site) cultivars. Treatments were applied during the summer, and effects on fruit yield, oil content per fruit, oil yield per tree, and key oil quality parameters—including total phenols, flavonoids, antioxidant capacity, and fatty acid composition—were assessed. GB significantly enhanced fruit yield and oil production for “Koroneiki” at the site with the harshest environmental conditions (24.37 Kg fruits per tree and 4.69 Kg of oil per tree compared to 19.16 Kg fruits per tree and 3.48 Kg of oil per tree in control). In contrast, K proved most effective at the other two sites for both cultivars (43% and 52.8% increase in fruit yield and oil mass per tree in “Koroneiki” respectively and 30% as well as 34% increase in yield and oil mass per tree in “Lianolia Kerkyras”, respectively. CC exhibited limited impact on both productivity and quality. Under all treatments, the oils produced could be classified as extra virgin olive oils, with the products exhibiting minor effects on the functional properties of the oils. These findings indicate that the efficacy of stress-alleviating foliar treatments is strongly influenced by both environmental conditions and cultivar. Overall, K was the most effective treatment, followed by GB. Tailored application of these treatments represents a sustainable approach to maintaining olive productivity and preserving oil quality in the context of climate change. Full article

Leaf water content (LWC) is a key physiological indicator for assessing crop water status. However, its spectral response may vary under different irrigation practices, which limits the general applicability of existing models. This study aims to develop irrigation-specific LWC estimation models for spring wheat based on UAV multispectral imagery. Field experiments were conducted during two growing seasons (2023–2024) under three irrigation methods, with five water treatments and three replicates, resulting in a total of 45 experimental plots. Multispectral data and in situ measurements were collected at key growth stages. Irrigation-dependent sensitive vegetation indices were identified through correlation analysis, and machine learning models, including Random Forest (RF), Multiple Linear Regression (MLR), and Backpropagation Neural Network (BPNN), were constructed and evaluated using a five-fold cross-validation framework. The results showed that spectral sensitivity to LWC varied significantly across irrigation methods, with different dominant indicators under FD, ND, and MD. Model performance also exhibited irrigation-dependent differences. Among the three models, RF showed the most stable performance, achieving mean R² values of 0.70, 0.74, and 0.62 and corresponding RMSE values of 0.04, 0.06, and 0.08 under FD, ND, and MD, respectively. In contrast, MLR showed lower predictive accuracy, while BPNN exhibited limited robustness under the current dataset, particularly under ND. These findings highlight the importance of irrigation-specific modeling strategies for improving LWC estimation reliability. Full article

The transition from starch-dominated to protein-enriched gluten-free systems represents a critical step in improving the functional and nutritional quality of composite flours. This study investigated the effects of progressive substitution of Amaranthus caudatus (amaranth) with Lupinus mutabilis (Andean lupin) on the physicochemical, rheological, and antioxidant properties of gluten-free flour blends. A multimodal dataset comprising 33 variables across six measurement domains (proximal composition, hydration properties, thermomechanical behavior, pasting profiles, particle size, and antioxidant activity) was analyzed using an integrated framework combining univariate inference (FDR-adjusted p-values), PCA, Multiple Factor Analysis (MFA), and sparse Partial Least Squares Discriminant Analysis (sPLS-DA). Results revealed that increasing lupin content (10–40%) significantly increased protein and fiber levels while decreasing starch content, leading to higher water absorption capacity and reduced peak viscosity and setback. Multivariate models showed that the protein/fiber–starch trade-off was the principal axis of compositional differentiation (PC1, ~41% variance), while PC2 captured rheological and antioxidant variability, with formulations containing higher proportions of amaranth exhibiting greater antioxidant activity. The sPLS-DA model achieved 72% separation accuracy with moisture, protein, water absorption, and torque parameters as top discriminants. These findings provide an evidence-based framework for gluten-free flour optimization using Andean crops and highlight how statistical modeling can inform targeted formulation decisions. The approach is transferable to other compositional transitions in food systems, underscoring the utility of multivariate analytics in applied food research. The multivariate framework further suggests that intermediate substitution levels may offer an optimal balance between nutritional enrichment and rheological functionality. Full article

Wheat productivity and grain quality are strongly influenced by nutrient management and soil moisture availability. Nitrogen (N) and potassium (K) regulate biomass production, physiological stability and grain protein development. However, their efficiency varies under water-limited conditions. This study aimed to evaluate how soil moisture modulates nitrogen–potassium efficiency, nutrient partitioning, physiological responses and grain quality development in wheat. The current experiment was planned to assess the impact of varying but combined levels of N and K fertilizers on wheat crop growth and yield components as well as nutrient uptake and grain quality under different irrigation levels (i.e., normal irrigation Field Capacity (FC) 100%, partial water deficit FC75%, moderate water deficit FC50%, severe water deficit FC25%). The results of the study showed that increasing N-K supply enhanced biomass, chlorophyll contents, nutrient accumulation and grain quality under full irrigation, with N2K2 showing the highest growth, yield and quality traits. Under moderate deficit, N2K1 maintained a relatively stable yield and physiological performance, whereas severe moisture limitation markedly reduced nutrient uptake, grain development and fertilizer efficiency despite a higher NK application. Progressive reductions in irrigation also altered nutrient distribution among leaves, straw and grain, indicating moisture-regulated remobilization during grain filling. Maximum increments in values for plant height (27%), total biomass (108%), grain yield (183%), grain NPK content (38%, 6.3%, 26%), grain protein (38%) and wet gluten (38%) were noted in the N2K2 treatment at FC100%, but these parameters showed up to 80% reduction under the same treatment of N-K at FC25%. It is concluded that wheat response to N–K fertilization was moisture dependent and fertilizer rate alone did not ensure productivity under severe water deficit. Therefore, integrating nutrient supply with irrigation management is essential to sustain productivity and grain quality. Full article

Opuntia ficus-indica (L.) Mill., also named Cactus pear, is a crop widespread in many countries with Mediterranean and subtropical climates, where it represents a valuable source of food. However, in southern Europe, this fruit market is limited to a few months, from summer to autumn. The possibility to extend the ripening period of fruit is represented by the special pruning of the first bloom flush and consequent new development of late flowers and fruits. Extending the cultivation period would allow farmers to maximize the crop’s potential, thereby extending the Cactus pear market season throughout much of the year. In this study, conducted in southern Sardinia (Italy), progressive pruning was applied with the aim of evaluating the fruit characteristics in relation to this type of cultivation, also considering the weather conditions during the experimental period. Morphological traits and physicochemical compositions of fruit picked in four harvests during two sampling seasons from August 2022 to March 2023, and from August 2023 to March 2024 were compared. According to principal component analysis (PCA), most of the observed characters showed significant differences among harvest periods but also between the two seasons of cultivation (year of cultivation: r = 0.722 on PC1), suggesting that the meteorological trend strongly modulated fruit traits. Some fruit qualities were partially lost during the winter months, such as juice acidity and total soluble solids (TSS). October was the month with the highest TSS levels (13.5 ± 0.25), followed by August, January and March. On the other hand, juiciness and fresh weight remained unchanged or even improved in fruit harvested out-of-season. As observed in the redundancy analysis (RDA) a contribution of 54% due to weather variability emerged. In Particular, TSS levels, pH and juice dry matter were associated with high temperatures, solar radiation, and wind intensity. Wind speed was also moderately linked with betalain content. Moreover, high relative humidity was associated with lower pH values, higher water content, and higher fruit fresh weight. A significant difference was found between the two years in betalains content (80.0 ± 3.7 µg·mL⁻¹ in 2022–2023 and 28.2 ± 2.5 µg·mL⁻¹ in 2023–2024). The breakdown in the 2023–2024 season was likely due to the strong heat wave of July 2023 (up to 47 °C), which caused their partial degradation. In light of seasonal variability, this work provides some useful insights for future management of Cactus pear, also considering the possibility of usefully extending the period of cultivation and harvesting. Full article

Shoot tip cryopreservation is essential for the long-term conservation of plant genetic resources. It provides the only reliable method for establishing a long-term, readily available gene pool of clonally propagated crops and elite in vitro clones used in the pharmaceutical, food, and cosmetic industries. Still, its success is often limited by the inherent sensitivity of many species to the osmotic and chemical stresses imposed by concentrated cryoprotectant (vitrification) solutions and severe dehydration. The optimization of modern cryopreservation protocols primarily focuses on modifying shoot tip preculture, cryoprotectant treatments, or regrowth conditions, while frequently overlooking donor plant preconditioning or relegating it to a secondary role. However, the physiological state of in vitro plants from which apical or axillary shoot tips are extracted may hold the key to successful post-cryopreservation recovery, especially in cryo-sensitive taxa. This review revisits the critical role of donor plant vigor and induced stress tolerance in the cryopreservation of clonal crops by systematically evaluating preconditioning strategies, including cold acclimation, sucrose pretreatment, and the use of growth regulators and signaling molecules such as abscisic, jasmonic, and salicylic acids, involved in stress signaling and tolerance development. The beneficial physiological changes induced by donor plant pretreatment, such as reduced freezable water content and the accumulation of protective compounds, are discussed in the context of contemporary cryopreservation methods. The effects of culture conditions, including the roles of ammonium and nitrates, light quality, culture density and aeration, medium strength, culture age, and subculture duration, are also considered. We analyze how different treatments of in vitro donor plants improve shoot tip tolerance to osmotic and/or chemical toxicity imposed by specific cryopreservation methods to support a material-centered selection of a cryopreservation procedure. Future directions and potential approaches for integrating target donor plant preconditioning into modern cryopreservation protocols for shoot tips, particularly in stress-sensitive species, are discussed. Full article

Rice is a globally important food crop, and its production is often affected by extreme climates such as drought and high temperatures. This study investigated how drought applied at different growth stages affects cadmium (Cd) uptake and accumulation in rice, as well as the underlying mechanisms. The results showed that drought treatments generally increased soil organic matter and alkali-hydrolyzed nitrogen content but decreased pH and available phosphorus content. The available Cd content in soil under the grain-filling stage drought treatment was lower than that under other treatments. Speciation analysis showed that under grain-filling stage drought, exchangeable Cd decreased by 3.04%, and residual Cd increased by 2.67%. Furthermore, drought treatments significantly enhanced soil urease and sucrase activities. Rice plant height and yield were significantly affected by the timing of drought, with the grain-filling stage drought treatment yielding the highest, while full growth stage and tillering stage drought treatments resulted in significantly lower yields. Cd content in various organs followed the order: root > stem > leaf > brown rice, with the brown rice Cd content being the lowest under grain-filling stage drought. In conclusion, drought treatment during the grain-filling stage had the least effect on Cd content in various rice tissues while maintaining a relatively high yield, providing a theoretical basis for water management in Cd-contaminated paddy fields. Full article

Dryland farming systems in South Dakota face rainfall variability and rising water demand, which can reduce crop productivity and threaten long-term soil health. We combined field experiments across three dryland sites in South Dakota (Roscoe, Selby, Fort Pierre) with continuous soil moisture monitoring (0–15, 15–30, 30–45 cm) and HYDRUS-1D modeling to evaluate cover crops and soil amendments (biochar, manure) on water retention. During the active cover crop growth period, plots with cover crops consistently exhibited lower soil water content than plots without cover crops, likely due to increased transpiration. Plots with no cover crop (NCC) retained more water than cover crop (CC) plots (Roscoe: 26.27% vs. 24.16% at 0–15 cm). During the primary crop growing season, biochar consistently increased soil moisture (θ) compared with manure and unamended plots. Following a 43-day dry spell (1 July–13 August 2024), soil moisture declined by approximately 0.096 m³ m⁻³ in the biochar plots, compared with 0.125 m³ m⁻³ under manure and 0.216 m³ m⁻³ in the unamended control, exhibiting differences in water retention capacity among treatments. HYDRUS inverse modeling reproduced observed soil moisture dynamics (R² ~ 0.91) and demonstrated higher water content under biochar. Scenario analysis using representative wet (2008) and dry (2012) years showed the cover crop + biochar combination maintained the highest average water content. Results support integrating biochar with cover cropping to buffer drought and improve soil water availability in dryland farming. Full article

Climate change exacerbates water scarcity in semi-arid and arid regions, particularly across the Mediterranean Basin, posing severe challenges to food security and freshwater availability. Non-conventional water resources, such as desalinated seawater, are increasingly considered for supplementing irrigation; however, their exclusive use can induce osmotic stress, nutrient imbalances, and soil alkalinity, thereby limiting crop performance. This study evaluated the agronomic, and physiological impacts of blending freshwater (FW) and desalinated seawater (DSW) for two zucchini (Cucurbita pepo L.) cultivars, Radia and Kayssar, under greenhouse conditions. Five irrigation regimes were tested: T1 (FW^100%), T2 (FW^75%-DSW^25%), T3 (FW^50%-DSW^50%), T4 (FW^25%-DSW^75%), and T5 (DSW^100%). Moderate blending, particularly T2 and T3, optimized vegetative growth, biomass accumulation, and reproductive performance, maximum yields were obtained under T3, reaching 6.65 kg/plant for Radia and 5.49 kg/plant for Kayssar, while fruit quality, including caliber and soluble solids content (°Brix), was also highest under this regime. These findings support the suggestion that implementing such combined/blended irrigation regimes can enhance vegetative growth, yield, and fruit quality in the face of increasing water scarcity and energy constraints. Full article

Increasing domestic sewage production associated with urban population growth poses environmental challenges. Biosolids from wastewater treatment can recycle nutrients in agriculture, while plant growth-promoting rhizobacteria (PGPR) enhance nutrient availability and plant performance. This study evaluated the effects of the combined application of sewage sludge–derived biosolid and Bacillus aryabhattai on sunflower growth, biomass production, physiological traits, and nutrient status during the early growth stage under greenhouse conditions. We hypothesized that this combined treatment would enhance plant performance compared with biosolid application alone. Four treatments were established: control (T1), 5 g of biosolid alone (T2), 5 g biosolid + 3.2 mL B. aryabhattai (T3), and 5 g biosolid + 6.4 mL B. aryabhattai (T4). The formulation contains B. aryabhattai strain CMAA 1363 (1 × 10⁸ CFU mL⁻¹) as the active microbial component, together with humic substances and other formulation agents (thickener, preservative, and water). The Plants were grown for 44 days. The data were analyzed using one-way ANOVA followed by mean comparison among treatments. Shoot dry mass was significantly higher in T4 compared with the T1 and T2 (p < 0.001), while no significant difference was observed between T3 and T4 (p > 0.05). Biosolid application increased the photosynthetic rate, and its combination with B. aryabhattai further enhanced photosynthetic performance, with significant difference detected between bacterial doses only at the end of growth period. Substomatal CO₂ concentration was lower in inoculated treatments, indicating greater CO₂ assimilation efficiency. Total chlorophyll increased with the addition of sludge and further increased by inoculation with 6.4 mL. Leaf N, Mn, and Zn contents were highest in T4. Overall, the combined application of biosolid and B. aryabhattai improved photosynthetic efficiency and biomass accumulation, highlighting the potential of integrating biosolids and beneficial rhizobacteria as a sustainable approach for nutrient recycling and improved crop productivity in agricultural systems. Full article

Food insecurity occurs due to the impact of climate change and intense global conditions. Thus, understanding crop farming plans and monitoring crop yields have become major tasks for decision makers. Previous work has applied remote sensing techniques and empirical methods to predict the yields and analyse the relationships between spectral indices and historical crop yield data. However, a limitation of these studies is that they do not extract the values of spectral indices by crop types when the testing area is regional with multiple farmlands and requires a crop classification process. This can cause inaccurate results when investigating the correlations between the yield and the spectral indices. This research develops a yield prediction framework with historical crop maps by means of unsupervised classification with zero ground truth using Sentinel-2 imagery to retrieve the values of spectral indices of winter barley. The extracted spectral indices and the meteorological and historical yield data in North Norfolk, UK, are implemented in 1D Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and CNN–LSTM for winter barley yield predictions. LSTM has outstanding performance overall and the best result approaches a Root Mean Square Error (RMSE) of 0.406 kg/hectare, a Mean Square Error (MSE) of 0.165 kg/hectare and a Mean Absolute Error (MAE) of 10.495 kg/hectare. The EVI in April, May and June is the most important feature in the LSTM model and shows strong positive correlation with the yield of winter barley. The developed framework with unsupervised crop classification and LSTM can be applied to multiple crop types and in different regions using opensource datasets, historical yields, spectral indices and meteorological data. Correlations between these datasets indicate that higher EVI and maximum and minimum temperature and sun hours at the germination and seedling growth stages increase the yields of winter barley, but excess Water Content (WC) in plants with a higher Normalised Difference Moisture Index (NDMI) from April to June leads to a decline in the yields of winter barley. Full article

In the USA, agriculture is the largest consumer of freshwater resources, and precision irrigation (PI) can conserve water significantly while maintaining crop yield. Current approaches to soil volumetric water content (VWC) mapping for PI rely on installing a costly soil moisture sensor within each of 4–5 management zones per field. Although this strategy provides temporally dense data, it is spatially sparse. Alternatively, spatially dense remotely sensed data require calibration with in situ soil moisture measurements, which are expensive and labor intensive to obtain. Previous research indicates that soil VWC zones must be regularly reassessed, a process that is impractical without low-cost soil VWC sensors. In anticipation of deploying dense networks of inexpensive soil moisture sensors for PI in large turfgrass fields, we investigate the mapping errors and optimal sampling density required for accurate soil VWC mapping using random forests (RFs) and z-score calibration in two turfgrass sports fields in Utah. Dense sampling of soil VWC was undertaken at 101 and 103 points in each field with a theta probe. These data were systematically sub-sampled to quantify errors in z-score soil moisture maps generated with varying sample sizes. A jack-knife procedure was employed to determine the optimum number of sensors required to produce accurate RF-based soil moisture maps. The RF approach also allows identification of the most influential covariates for soil VWC prediction. For RFs, 21–79 samples were needed to characterize changing spatial patterns in fields with mean absolute errors (MAEs) of 1.39–9.71%, but for most dates only 25–40 samples were needed. The z-score calibration produced MAEs of 1.38–10.44% with as few as 10–15 samples, but the spatial patterns remain static and only the magnitude of values changes. Therefore, using RFs with 40–60 sensors was recommended to allow for accurate mapping despite dropped signals and broken sensors. Full article

The apple tree (Malus domestica Borkh.) is one of the most economically important fruit crops worldwide, and its productivity is increasingly affected by water deficit. Understanding genotype-specific physiological responses to water deficit is important for improving water deficit resilience in apple. This study evaluated the effects of water deficit (14 days) and subsequent rehydration (7 days) on eight apple genotypes (‘Galaval’, ‘Idared’, ‘Rubinstep’, ‘B11’, ‘HL 308’, ‘HL 2010’, ‘HL 2350’, and ‘HL 827’) grown under semi-controlled container conditions. Physiological parameters, including pigment content, gas exchange, chlorophyll fluorescence, water use efficiency, and leaf water status, were assessed. Water deficit affected all measured parameters, with responses differing among genotypes. In most cases, water deficit was associated with reduced gas exchange and chlorophyll fluorescence, as well as changes in pigment content and leaf water status. However, the magnitude and direction of these responses varied depending on genotype. Some genotypes (e.g., ‘HL 2350’ and ‘B11’) showed more stable physiological performance under water deficit conditions, while others (e.g., ‘Idared’ and ‘Rubinstep’) exhibited more pronounced changes. Rehydration resulted in partial recovery of physiological parameters, although values generally did not reach control levels within the experimental period. The results indicate substantial genotypic variability in physiological responses to short-term water deficit under controlled conditions. These findings provide useful information for further research on water deficit responses in apple; however, additional studies under field conditions and including growth and yield parameters are required to assess the agronomic relevance of the observed differences. Full article

A systematic elucidation of soil ammonia (NH₃) volatilization (SAV) and the underlying drivers is imperative for evaluating NH₃ pollution mitigation strategies and advancing sustainable agricultural practices. Currently, no scientific consensus has been established on the effects of maize–soybean intercropping on SAV across varying nitrogen (N) application rates. A consecutive field experiment was conducted over a 2-year period from 2024 to 2025 with a split-plot design. The experiment comprised three cropping systems (maize monocropping (MM), soybean monocropping (MS), and maize–soybean intercropping (IMS)) and three N application rates (no N application (NN), 20% reduced N application (20%RN), and conventional N application (ConN)). The results demonstrated that N application markedly increased SAV. Accumulative SAV was 4.94–6.01 kg ha⁻¹ under NN treatment, whereas it was 8.21–27.89 kg ha⁻¹ under ConN treatment, 7.25–21.52 kg ha⁻¹ under 20%RN treatment. Under ConN treatment, the accumulative SAV in IMS was 21.34 kg·ha⁻¹ and 27.89 kg·ha⁻¹ in 2024 and 2025, respectively, which were significantly higher than those in MM by 16.80% and 13.33%. Under 20% RN treatment, the accumulative SAV in IMS was 15.46 kg·ha⁻¹ and 19.24 kg·ha⁻¹ in 2024 and 2025, respectively, which were lower than those in MM by 3.07% and 10.59%. SAV was positively correlated with soil ammonium N concentration. Moreover, within an appropriate range, SAV increased in response to rising soil water content and temperature. Collectively, maize–soybean intercropping integrated with a 20% nitrogen reduction mitigated environmental risks associated with reactive nitrogen losses. This system constitutes a stable yield, resource-efficient, and ecologically sustainable cropping practice. Full article