Search Results (4,678)

Spodoptera littoralis (Boisd.) (Lepidoptera: Noctuidae) is a major insect pest that severely affects various crops. Our study provides new insights by combining field efficacy trials with enzymatic analysis to evaluate the effects of emamectin benzoate mixtures with other insecticides (lufenuron, cypermethrin, chlorpyrifos, and spinosad) against S. littoralis. The aim of our work was to investigate the effectiveness of five insecticides, i.e., emamectin benzoate, lufenuron, cypermethrin, chlorpyrifos, and spinosad, for controlling this pest under field conditions during two consecutive seasons (2023–2024). Each insecticide was applied individually at the recommended rate, while some were mixed with emamectin benzoate at half its recommended rate. The results indicated that emamectin benzoate was the most effective insecticide, followed by lufenuron. The joint action of emamectin benzoate (LC₂₅) and its mixtures with other insecticides (chlorpyrifos, spinosad, cypermethrin, and lufenuron) at various concentrations (LC₅₀) against second- and fourth-instar S. littoralis larvae was evaluated. Results showed additive effects with chlorpyrifos, lufenuron, and cypermethrin, while potentiation occurred with cypermethrin (LC₅₀) and chlorpyrifos (LC₅₀). Antagonistic effects were observed in the combination of emamectin benzoate with spinosad (LC₂₅ and LC₅₀). This study concluded that applying insecticides individually is more cost-effective for managing cotton leafworm infestations in cotton crops. Additionally, enzyme activity analysis showed significant changes in alpha-esterase, beta-esterase, carboxylesterase, acetylcholinesterase, and glutathione S-transferase levels in larvae treated with different insecticide combinations. Full article

Remote sensing is a widely used tool for crop monitoring to improve water management. Rice, a crop traditionally grown under flooded conditions, requires farmers to understand the relationship between crop reflectance, water depth and final yield. This study focused on seven commercial rice fields in 2022 and six in 2023, analyzing the correlations between water depth and Sentinel-2 reflectance over two growing seasons in Valencia, Spain. During the tillering stage across both seasons, water depth showed positive correlations with visible bands and negative correlations with NIR and SWIR bands. There were no correlations with the indices NDVI, GNDVI, NDRE and NDWI. The NIR band showed significant correlations across both seasons, with R² values of 0.69 and 0.71, respectively. In addition, the calculation of NIR anomalies for each field proved to be a good indicator of final yield anomalies. In 2022, anomalies above 10% corresponded to yield deviations above 500 kg·ha⁻¹, while in 2023, anomalies above 15% were associated with yield deviations above 1000 kg·ha⁻¹. The response of final yield to water level was positive up to average values of 9 cm. The use of the NIR band during the rice crop tillering stage can support farmers in improving irrigation management. Full article

The growth potential of Crinum bulbispermum was evaluated on gold mine tailings. The primary objectives were to model the species’ climatic niche in relation to gold mining regions, assess its germination success on tailings, and compare seedling survival and growth on tailings versus other soil types. Species distribution modelling identified the South African Grassland Biome on the Highveld (1000+ m above sea level), where the majority of gold mines are located, as highly suitable for the species. Pot trials demonstrated above 85% germination success across all soil treatments, including gold mine tailings, indicating its potential for restoration through direct seeding. An initial seedling establishment rate of 100% further demonstrated the species’ resilience to mine tailings, which are often seasonally dry, nutrient-poor, and may contain potentially toxic metals. However, while C. bulbispermum was able to germinate and establish in mine tailings, long-term growth potential (over 12 months) was constrained by low organic carbon content (0.11%) and high salinity (194.50 mS/m). These findings underscore the critical role of soil chemistry and organic matter in supporting long-term plant establishment and growth on gold tailings. Building on previous research, this study confirms the ability of this thick-rooted geophyte to tolerate chemically extreme soil conditions. Crinum bulbispermum shows promise for phytostabilization and as a potential medicinal plant crop on tailings. However, future research on microbial community interactions and soil amendment strategies is essential to ensure its long-term sustainability. Full article

Chickpea is a highly weed-prone crop with limited herbicide options and high labor demands, raising the following question: Can fall-planted legume–cereal cover crops (CCs) improve soil properties while reducing herbicide use and manual weeding pressure? To explore this, we evaluated the effect of fall-planted winter rye (WR) alone in 2021 and mixed with hairy vetch (HV) in 2022 and 2023 at Randolph farm in Petersburg, Virginia. The objectives were two-fold: (a) to examine the effect of CCs on soil properties using monthly growth dynamics and biomass harvested from fifteen 0.25 m²-quadrants and (b) to evaluate the efficiency of five termination methods: (1) green manure (GM); (2) GM plus pre-emergence herbicide (GMH); (3) burn (BOH); (4) crimp mulch (CRM); and (5) mow-mulch (MW) in suppressing weeds in chickpea fields. Weed distribution, particularly nutsedge, was patchy and dominant on the eastern side. Growth dynamics followed an exponential growth rate in fall 2022 (R² ≥ 0.994, p < 0.0002) and a three-parameter sigmoidal curve in 2023 (R² ≥ 0.972, p < 0.0047). Biomass averaged 55.8 and 96.9 t/ha for 2022 and 2023, respectively. GMH consistently outperformed GM in weed suppression, though GM was not significantly different from no-till systems by the season’s end. Kabuli-type chickpeas under GMH had significantly higher yields than desi types. Pooled data fitted well to a three-parametric logistic curve, predicting half-time to 50% weed coverage at 35 (MM), 38 (CRM), 40 (BOH), 46 (GM), and 53 (GMH) days. Relapses of CCs were consistent in no-till systems, especially BOH and MW. Although soil properties improved, CCs alone did not significantly suppress weed. Full article

This study, conducted in Southern Italy in 2023, investigated the effects of a dynamic agrivoltaics (AV) system on microclimate, water consumption, plant growth, and essential oil yield in six medicinal species: lavender (Lavandula angustifolia L. ‘Royal purple’), lemmon thyme (Thymus citriodorus (Pers.) Schreb. ar. ‘Aureus’), common thyme (Thymus vulgaris L.), rosemary (Salvia rosmarinus Spenn. ‘Severn seas’), mint (Mentha spicata L. ‘Moroccan’), and sage (Salvia officinalis L. subsp. Officinalis). Due to the rotating solar panels, two distinct ground zones were identified: a consistently shaded area under the panels (UP), and a partially shaded area between the panels (BP). These were compared to an adjacent full-sun control area (T). Microclimate parameters, including solar radiation, air and leaf infrared temperature, and soil temperature, were recorded throughout the cultivation season. Reference evapotranspiration (ET_O) was calculated using Turc’s method, and crop evapotranspiration (ET_C) was estimated with species-specific crop coefficients (K_C). Results showed significantly lower microclimatic values in the UP plot compared to both BP and especially T, resulting in ET_C reductions of 81.1% in UP and 13.1% in BP relative to T, an advantage in water-scarce environments. Growth and yield responses varied among species and treatment plots. Except for mint, all species showed a significant reduction in fresh biomass (40.1% to 48.8%) under the high shading of UP compared to T. However, no biomass reductions were observed in BP. Notably, essential oil yields were higher in both UP and BP plots (0.60–2.63%) compared to the T plot (0.51–1.90%). These findings demonstrate that dynamic AV systems can enhance water use efficiency and essential oil yield, offering promising opportunities for sustainable, high-quality medicinal crop production in arid and semi-arid regions. Full article

Soil microbial communities are crucial for ecosystem services, soil fertility, and the resilience of agroecosystems. This study investigated how long-term (31 years) agronomic practices—tillage, NPK fertilization, and cropping system—along with measured environmental variables influence the microbial biomass and its community composition in Chernozem soil under corn cultivation. The polyfactorial field experiment included three tillage treatments ((moldboard (MT), ripped (RT), strip (ST)), two fertilization regimes (NPK (N: 160; P: 26; K: 74 kg/ha), and unfertilized control) and two cropping systems (corn monoculture and corn–wheat biculture). The soil samples (0–30 cm) were collected in June and September 2023. Microbial biomass and community structure were quantified using phospholipid fatty acid (PLFA) analysis, which allowed the estimation of total microbial biomass and community composition (arbuscular mycorrhizal (AM) fungi, fungi, Gram-negative (GN) and Gram-positive (GP) bacteria, actinomycetes). Our results showed that microbial biomass increased from June to September, rising by 270% in unfertilized plots and by 135% in NPK-fertilized plots, due to higher soil moisture. Reduced tillage, especially ST, promoted significantly higher microbial biomass, with biomass reaching 290% and 182% of that in MT plots in June and September, respectively. MT had a higher ratio of bacteria-to-fungi compared to RT and ST, indicating a greater sensitivity of fungi to disturbance. NPK fertilization lowered soil pH by about one unit (to 4.1–4.8) and reduced microbial biomass—by 2% in June and 48% in September—compared to the control, with the particular suppression of AM fungi. The cropping system had a smaller overall effect on microbial biomass. Full article

Induced mutation plays an integral part in plant breeding as it introduces new variability among the population. A study was conducted in cowpeas [Vigna unguiculata (L.) Walp] to assess the yield divergence, heritability, genetic advance, and correlation among the M5 Tswana cowpea mutants. The experiment utilized seven genotypes under rainfed and supplementary irrigation during the 2022/23 and 2023/24 cropping seasons. The mutant lines demonstrated significant variations in days to 50% emergence (DE) and days to 50% flowering (DF). Tswana emerged earlier (5–7 days) and flowered in 21–54 days across the two seasons, compared to some of the mutant lines. The yield and yield components varied among some mutant lines and the control. Most importantly, mutants outperformed the Tswana control for some of these traits, indicating potential for genetic improvement. An analysis of genetic parameters revealed minimal environmental influences on some of the observed traits (GH, PN, GY), while others showed little environmental impact. Variation in heritability (H²) and genetic advance (GA%) between the two seasons limited the contribution of genotypic effects in the expression of the studied traits. Correlation analysis revealed strong and significant positive associations between DE and GH, as well as between DF and PW. Most traits, except DF and PW, were positively correlated with grain yield (GY), although the correlations were not significantly different. Cluster analysis grouped the genotypes into four distinct clusters. Principal component analysis (PCA) revealed the superiority of mutant lines (Tswana-300Gy-214, Tswana-400Gy mutant lines, and Tswana-500Gy-31) in their association with improved GY, pod weight (PW), 100-seed weight (100-SW), and seed number per pod (SN/P). Interestingly, the Tswana control formed a separate cluster and diverged from the mutants in PCA, suggesting that induced mutagenesis effectively targeted genes controlling the traits considered in this study. Full article

In the past three decades, localized research has highlighted shifts in rainfall patterns and temperature trends in central Ethiopia, a region vital for agriculture and economic activities and heavily dependent on climate conditions to sustain livelihoods and ensure food security. However, comprehensive analyses of long-term climate data remain limited for this area. Understanding local climate trends is essential for enhancing agricultural resilience in the study area, a region heavily dependent on rainfall for crop production. This study analyzes historical rainfall and temperature patterns over the past 30 years and projects future climate conditions using downscaled CMIP6 models under SSP4.5 and SSP8.5 scenarios. Results indicate spatial variability in rainfall trends, with certain areas showing increasing rainfall while others experience declines. Temperature has shown a consistent upward trend across all seasons, with more pronounced warming during the short rainy season (Belg). Climate projections suggest continued warming and moderate increases in annual rainfall, particularly under SSP8.5 by the end of the 21st century. It is concluded that both temperature and rainfall are projected to increase in magnitude by 2080, with higher Sen’s slope values compared to earlier periods, indicating a continued upward trend. These findings highlight potential breaks in agricultural calendars, such as shifts in rainfall onset and cessation, shortened or extended growing seasons, and increased risk of temperature-induced stress. This study highlights the need for localized adaptation strategies to safeguard agriculture production and enhance resilience in the face of future climate variability. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

Discovering, analyzing, and finding a key to understanding the physiological and biochemical responses that Vitis vinifera L. undertakes against drought stress is of fundamental importance for this profitable crop. Today’s considerable climatic fluctuations force researchers and farmers to focus on this issue with solutions inclined to respect the ecosystem. In this academic work, we focused on describing the drought stress consequences on several parameters of secondary metabolites on Vitis vinifera leaves (quercetins, kaempferol, resveratrol, proline, and xanthophylls) and on some ecophysiological characteristics (e.g., water potential, stomatal conductance, and leaf temperature) to compare the answers that diverse agronomic management techniques (i.e., irrigation with and without zeolite, pure zeolite and no application) could instaurate in the metabolic pathway of this important crop with the aim to find convincing and thought-provoking responses to use this captivating and versatile mineral, the zeolite known as the “magic rock”. Stressed grapevines reached 56.80 mmol/m²s gs at veraison and a more negative stem Ψ (+10.63%) compared to plants with zeolite. Resveratrol, in the hottest season, fluctuated from 0.18–0.19 mg/g in zeolite treatments to 0.37 mg/g in stressed vines. Quercetins were inclined to accumulate in response to drought stress too. In fact, we recorded a peak of quercetin (3-O-glucoside + 3-O-glucuronide) of 11.20 mg/g at veraison in stressed plants. It is interesting to note how the pool of metabolites was often unchanged for plants treated with zeolite and for plants treated with water only, thus elevating this mineral to a “stress reliever”. Full article

Enhancing the nutritional content of crops is crucial for safeguarding human health and mitigating global hunger. A viable method for attaining this goal is the planned implementation of various agronomic practices, including tillage and nutrient provision. A field experiment was executed at the Hungarian University of Agriculture and Life Sciences in Gödöllő in the 2023 and 2024 growing seasons. The study aimed to assess the effects of foliar nutrient supply and soil tillage methods on the grain nutritional composition and mineral content of winter barley. Employing a split-plot design with three replications, the experiment included four nutrient treatments (control, bio-cereal, bio-algae, and MgSMnZn blend) and two soil tillage types (i.e., plowing and cultivator). The results indicated that while protein content was not influenced by the main effects of nutrients and tillage, the levels of β-glucan, starch, crude ash, and moisture content were significantly (p < 0.05) affected by the nutrient treatments and by growing year, treated as a random factor. Notably, bio-algae and bio-cereal nutrients, combined with cultivator tillage, enhanced β-glucan content. All applied nutrient treatments increased the level of starch compared to the control. With regard to grain mineral content, the iron and zinc content responded to the nutrient supply, tillage, and growing year. However, applying a multiple-nutrient composition-based treatment did not increase iron and zinc levels, suggesting that individual applications may be more effective for increasing the content of these minerals in grains. Cultivator tillage improved iron and zinc levels. Moreover, manganese (Mn) and copper (Cu) were predominantly affected by nutrient availability and by growing seasons as a random factor. Therefore, to improve grain quality, this study emphasizes the significance of proper nutrient and tillage methods by focusing on the intricate relationships between agronomic techniques and environmental factors that shape barley’s nutritional profile. Full article

Timely and accurate monitoring of crop nitrogen (N) status is essential for precision agriculture. UAV-based hyperspectral remote sensing offers high-resolution data for estimating plant nitrogen concentration (PNC), but its cost and complexity limit large-scale application. This study compares the performance of UAV hyperspectral data (S185 sensor) with simulated multispectral data from DJI Phantom 4 Multispectral (P4M), PlanetScope (PS), and Sentinel-2A (S2) in estimating winter wheat PNC. Spectral data were collected across six growth stages over two seasons and resampled to match the spectral characteristics of the three multispectral sensors. Three variable selection strategies (one-dimensional (1D) spectral reflectance, optimized two-dimensional (2D), and three-dimensional (3D) spectral indices) were combined with Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), and Partial Least Squares Regression (PLSR) to build PNC prediction models. Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. Among models, SVM and RFR showed consistent effectiveness across strategies. These findings highlight the potential of low-cost multispectral platforms for practical crop N monitoring. Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms. Full article

Potato (Solanum tuberosum L.) crop yields may be reduced by nitrogen deficiency stress tolerance. An evaluation of 144 tetraploid potato genotypes was carried out during two consecutive seasons (2019 and 2020), with the objective of characterizing their variability in key physiological and agronomic parameters. Physiological parameters included chlorophyll content and fluorescence, stomatal conductance, NDVI, leaf area, and perimeter, while agronomic characteristics such as yield, tuber fresh weight, tuber number, starch content, dry matter, and reducing sugars were evaluated. To genotype the population, the GGP V3 Potato array was used, generating 18,259 high-quality SNP markers. Marker–trait association analysis was conducted using the GWASpoly package in R, applying Q + K linear mixed models to enhance precision. This methodology enabled the identification of 18 SNP markers that exhibited statistically significant associations with the traits analyzed in both trials and periods, relating them to genes whose functional implication has already been described. Genetic loci associated with chlorophyll content and tuber number were detected across non-stress and stress treatments, while markers linked to leaf area and leaf perimeter were identified specifically under nitrogen deficiency stress. The genomic distribution of these markers revealed that genetic markers or single-nucleotide polymorphisms (SNPs) correlated with phenotypic traits under non-stress conditions were predominantly located on chromosome 11, whereas SNPs linked to stress responses were mainly identified on chromosomes 2 and 3. These findings contribute to understanding the genetic mechanisms underlying potato tolerance to nitrogen deficiency stress, offering valuable insights for the development of future marker-assisted selection programs aimed at improving nitrogen use efficiency and stress resilience in potato breeding. Full article

Climate warming poses significant challenges for the sustainable management of natural water resources, making efficient planning and usage essential. This study evaluates the water requirements, irrigation demand, and rainfall deficits for two key vegetable crops, carrot and white cabbage, under projected climate scenarios RCP 4.5 and RCP 8.5 for the period 2031–2100. The analysis was conducted for Kraków and Rzeszów Counties in southern Poland using projected monthly temperature and precipitation data from the Klimada 2.0 portal. Potential evapotranspiration (ETp) during the growing season (May–October) was estimated using Treder’s empirical model and the crop coefficient method adapted for Polish conditions. The reference period for comparison was 1951–2020. The results reveal a significant upward trend in water demand for both crops, with the highest increases under the RCP 8.5 scenario–seasonal ETp values reaching up to 517 mm for cabbage and 497 mm for carrot. Rainfall deficits are projected to intensify, especially during July and August, with greater shortages in Rzeszów County compared to Kraków County. Irrigation demand varies depending on soil type and drought severity, becoming critical in medium and very dry years. These findings underscore the necessity of adapting irrigation strategies and water resource management to ensure sustainable vegetable production under changing climate conditions. The data provide valuable guidance for farmers, advisors, and policymakers in planning effective irrigation infrastructure and optimizing water-use efficiency in southern Poland. Full article

Drosophila suzukii is an invasive pest of many fruit crops worldwide. Employing the Sterile Insect Technique (SIT) could mitigate D. suzukii population growth and crop damage. This study evaluated the efficacy of SIT on commercial fruit, by (1) validating the quality of irradiated sterile males (male mating competitiveness, courtship, and flight performance) in the laboratory, and (2) assessing population suppression and fruit damage reduction in commercial raspberry fields. Treatment with SIT was compared to the grower’s standard chemical insecticide program throughout the season. The principal metrics of efficacy were trap counts of wild adult female D. suzukii in crops and larvae per fruit during harvesting. These metrics together with monitoring of border areas allowed targeting of high-pressure areas with higher releases of sterile males, to maximise efficacy for a given release number. The sterile male D. suzukii were as competitive as their fertile non-irradiated counterparts in laboratory mating competitiveness and flight performance studies while fertility egg-to-pupae recovery was reduced by 99%. In commercial raspberry crops, season-long releases of sterile males significantly suppressed the wild D. suzukii population, compared to the grower standard control strategy; with up to 89% reduction in wild female D. suzukii and 80% decrease in numbers of larvae per harvested fruit. Additionally, relative fruit waste (i.e., percentage of harvested fruits rejected for sale) at harvest was reduced for early, mid and late harvest crops, by up to 58% compared to the grower standard control. SIT has the potential to provide an effective and sustainable strategy for managing D. suzukii in raspberries, increasing marketable yield by reducing adult populations, fruit damage and waste fruit. SIT could therefore serve as a valuable tool for integrated pest management practices in berry production systems. Full article