Search Results (181)

Thai eggplant (Solanum melongena L. cv. Chao Phraya), a widely cultivated vegetable with increasing global demand, is highly susceptible to salinity stress, which can severely impair seed germination and early seedling development. This study investigated the effects of sodium nitroprusside (SNP), a nitric oxide (NO) donor, on seed germination and seedling growth under salt stress conditions. Seeds were pre-treated with SNP at concentrations of 0, 0.05, 0.1, and 0.2 mM for 24 h and subsequently germinated under saline conditions with NaCl solutions (0, 100, and 200 mM). SNP pre-treatment, particularly at 0.05 and 0.1 mM, significantly improved germination percentage and germination rate in seeds exposed to 200 mM NaCl compared to untreated controls. Increased NaCl concentrations induced oxidative stress in seedlings, as evidenced by elevated hydrogen peroxide (H₂O₂) accumulation, which in turn caused lipid peroxidation, reflected by higher malondialdehyde (MDA) levels. Salt stress significantly increased ascorbate peroxidase (APX) activity, whereas catalase (CAT) activity showed no significant change across treatments. Correlation analysis revealed that APX activity was positively correlated with oxidative stress markers (H₂O₂) and delayed germination (T₅₀/MGT), whereas CAT activity showed no significant correlation with these parameters. In contrast, elevated APX activity was strongly and negatively correlated with overall seedling growth and vigor (SVI/GI), indicating that the underlying stress condition had a detrimental effect on plant performance. Overall, SNP pre-treatment, particularly at 0.05 and 0.1 mM, significantly enhanced salt tolerance by promoting germination (increasing GP and reducing T₅₀/MGT) and improving seedling growth (SL and RL). This protective effect is associated with improved redox regulation and partial mitigation of oxidative damage, as reflected by changes in H₂O₂, MDA, and APX; however, excessive SNP concentrations may exert phytotoxic effects, highlighting the importance of optimal dosing. Full article

Morningglories (Ipomoea lacunosa, I. hederacea, and I. purpurea) are persistent, problematic weeds in summer row crops throughout warm-temperate regions. Their vining growth habit and enduring seedbanks lead to recurring infestations and harvest interferences. This review synthesizes current knowledge on the seed ecology of these species to clarify how dormancy, germination, and emergence processes contribute to their persistence. Published anatomical and ecological studies were examined to summarize dormancy mechanisms, environmental signals regulating dormancy release, germination requirements, and seasonal emergence patterns. Morningglories exhibit a dormancy system dominated by physical dormancy, occasionally combined with a transient physiological component. Dormancy release is promoted by warm and fluctuating temperatures, hydration–dehydration cycles, and long-term seed-coat weathering. Once permeable, seeds germinate across broad temperature ranges, vary in sensitivity to water potential, and show limited dependence on light. Field studies indicate extended emergence windows from late spring through midsummer, especially in no-till systems where surface seeds experience strong thermal and moisture fluctuations. Despite substantial progress, significant gaps remain concerning maternal environmental effects, population-level variation, seedbank persistence under modern management, and the absence of mechanistic emergence models. An improved understanding of these processes will support the development of more predictive and ecologically informed management strategies. Full article

Low-temperature plasma treatments were applied to barley seeds using a dielectric barrier-stabilized corona discharge operated in ambient air enriched with oxygen or nitrogen to quantify surface chemical modifications and seed wettability. X-ray photoelectron spectroscopy showed that oxygen-enriched plasma produced the strongest oxidation, increasing surface oxygen from 9 ± 5 at% (control) to 24 ± 5 at%, while reducing carbon from 88 ± 5 at% to 76 ± 5 at%. Nitrogen-enriched plasma induced more moderate changes (O: 13 ± 5 at%, C: 85 ± 5 at%) but resulted in clear nitrogen incorporation, with an enhanced N 1s amine/amide component at ~400.8 eV. The hydroxyl O 1s contribution increased from 70% (control) to 82% (oxygen) and 90% (nitrogen), indicating substantial surface hydroxylation. SEM-EDX showed only minor micrometer-scale composition changes and no detectable morphological damage. Raman and ATR-FTIR spectra confirmed that polysaccharide, protein, and lipid structures remained intact, with intensity variations reflecting increased hydrophilicity. Water imbibition kinetics fitted with the Peleg model demonstrated faster initial hydration after plasma exposure, with 1/k₁ increasing from 20.25 ± 1.90 h⁻¹ (control) to 36.70 ± 6.56 h⁻¹ (oxygen) and 38.87 ± 7.57 h⁻¹ (nitrogen), while 1/k₂ remained nearly unchanged. Full article

Soil salinity poses a major threat to agriculture by severely limiting how well plants grow and produce crops. It strongly inhibits seed germination, a critical stage for plant life. Thus, it is critical to understand the complex ways salinity affects seed germination at the physiological, biochemical, and molecular levels to develop effective salt stress mitigation strategies. This review synthesizes the underlying mechanisms of how salinity inhibits seed germination, the observed impacts of this inhibition, and potential mitigation strategies. The review revealed that high salt concentrations reduce seed germination percentage and increase germination time through multiple mechanisms. They create osmotic stress that reduces water uptake, cause ion toxicity that disrupts critical metabolic activities, and induce oxidative stress. Furthermore, salinity can modify endogenous hormonal profiles, specifically by decreasing germination stimulants like gibberellic acids while increasing inhibitors like abscisic acid. The review finally explored the strategies to mitigate salinity’s adverse effects on seed germination. They include seed priming, a technique involving partial hydration of seeds in an eliciting solution, a promising biotechnological tool to overcome salinity problems during seed germination. Other approaches are the use of organic amendments and the breeding of salt-tolerant varieties. Future research should combine conventional and advanced molecular technologies to develop salt-tolerant cultivars to ensure food security in salt-affected agricultural lands. Full article

Chickpea seed quality is highly susceptible to mechanical damage during handling and to rapid deterioration under postharvest storage. Atmospheric pressure Non-Thermal Plasma (NTP) has shown positive effects on seed quality in several species, but its long-term impact on chickpea remains poorly understood. This study evaluated the effect of NTP on the physiological germination process and postharvest deterioration of Cicer arietinum L. (Fabaceae) ’Felipe UNC-INTA’ seeds. Seeds were treated for three minutes with dielectric barrier discharge using O₂ and N₂ as carrier gases. Results showed that NTP optimized the triphasic germination response in embryo, especially in phases II and III, where radicle protrusion occurred earlier in treated (27 and 30 h) than in control (33 h) seeds, accompanied with a partition ratio < 1, indicating the roots’ preferential assimilate allocation. Fungal incidence decreased notably, e.g., Aspergillus decreased from 31% (control) to 11% (N₂) and 10% (O₂). O₂-treated seeds exhibited higher germination (94%) than the control (90%) and an 11% reduction in individual electrical conductivity, indicating enhanced membrane integrity. After six months of storage, both treatments delayed aging, maintaining higher vigor than untreated seeds. Overall, NTP emerges as a promising postharvest technology to enhance and preserve seed vigor and viability in C. arietinum. Full article

Soybeans are widely used in agro-industrial sectors, and global demand for this crop continues to rise. After harvest, however, soybean seeds often lack the appropriate moisture content for storage, making drying a common practice under changing climate conditions. Because temperature is a critical factor during drying, this study aimed to evaluate the effect of air-drying temperature on physiological responses and cytogenetic conformation of soybean seeds. The experiment was conducted under a completely randomized design with four replications for each temperature. Seeds with 23 percent moisture content were dried in a convective dryer equipped with airflow and temperature control at 40 °C, 50 °C, 60 °C, and 70 °C until reaching 13 percent. Samples for physiological and cytological analyses were collected before and after drying. The results indicated that drying temperature influenced seed performance and vigor. Moreover, nuclear alterations were identified as an important component of the genotoxicity caused by high drying temperatures. Overall, air temperatures above 50 °C induced physiological and cytogenotoxic effects, underscoring the need for careful monitoring during seed drying. Full article

Agricultural research has accelerated in recent years, but farmers often lack the time and resources to conduct on-farm experiments, as most of their efforts are devoted to crop production. Seed classification provides essential insights for seed quality control, impurity detection, and yield estimation. Early identification of seed types is critical to reduce costs, minimize risks of poor field emergence, and support efficient crop management. Traditional classification methods rely heavily on manual feature extraction and expert input, which limits scalability and accuracy when dealing with highly similar seed types. To address this challenge, we propose an automated end-to-end deep learning framework for complex multiclass Brassica seed classification. Our framework integrates preprocessing, feature learning, and classification into a unified pipeline, eliminating the need for handcrafted features. Using a newly collected dataset of ten Brassica seed classes characterized by high texture similarity, we develop and evaluate a convolutional neural network optimized through architectural design and hyperparameter tuning. Experimental results demonstrate that the proposed framework achieves a classification accuracy of 93%, outperforming several state-of-the-art pretrained models. These findings highlight the potential of automated end-to-end deep learning models to enhance precision agriculture, providing robust and scalable solutions for seed quality monitoring and agricultural productivity. Full article

Sprouts are gaining popularity among consumers worldwide due to their high nutritional properties. A comparative evaluation of novel and environmentally friendly pre-sowing seed treatment techniques was conducted to enhance wheat sprout production. Pulsed electromagnetic field (PEMF), cold atmospheric plasma (CAP), and high-pressure processing (HP) at 200 and 600 MPa were applied on durum wheat seeds for 3 and 10 min. The above techniques, along with ozonation (OZ), were also applied for 3 and 10 min for the “activation” of water that was used for immersion of the wheat seeds. Seed germination percentage, root and shoot length, and seedling dry weight were the measurements for the comparative evaluation of 21 treatments of seeds growing in Petri dishes. The results indicated that CAP, PEMF, and OZ treatments had positive effects on wheat sprout production, while prolonged exposure to HP processing appeared to stress the seeds. Overall, the multiple comparisons of four processing technologies, applied by two methods and at two exposure times, could be a benchmark study for further understanding the response of seeds in pre-sowing techniques. Full article

Bambara groundnut is an underutilized legume with significant potential for enhancing nutrition and food security. However, limited knowledge of its seed systems hinders the development of targeted interventions. This study assessed the Bambara groundnut seed systems and seed quality in Ghana. A semi-structured questionnaire was used to examine seed production, conditioning, and saving practices, while 150 farmer-saved seed samples were evaluated for quality. The findings revealed that the seed system is predominantly informal, with 99% of farmers relying on their own saved seeds, which showed poor germination and emergence. About 54.4% sourced seeds from local markets, and 60.7% recycled seeds for five years or more. Seeds were stored unshelled in polypropylene bags in Tolon and shelled in the Kintampo South and Talensi Districts. Seed selection was primarily based on size (in Tolon) and visible absence of disease symptoms (in Kintampo South and Talensi). An incidence (7.6%) of seed-borne pathogens was recorded, with Aspergillus flavus (38.8%) and A. niger (16.6%) being most prevalent. Other pathogens included Macrophomina phaseolina (11.5%), Rhizopus spp. (6.5%), Curvularia lunata (5.3%), and A. fumigatus (1.9%). This study highlights the need to support community-based seed systems to improve farmers’ access to quality Bambara groundnut seed. Full article

Soybean seed production in low-altitude subtropical environments in Paraguay is constrained by the antagonism between achieving high grain yields and high physiological seed quality, a relationship governed by the Genotype x Environment x Management (GxExM) interaction. This study aimed to elucidate this trade-off by evaluating three sowing dates (early, normal, late) across genotypes from three relative maturity groups over four growing seasons. Our results demonstrate that sowing date is the primary factor modulating this antagonism. Early and normal sowings maximized yield (up to 62.8% higher than late sowing) by synchronizing the reproductive period with maximum solar radiation but exposed the maturation phase to severe thermal and water stress. This consistently resulted in a high incidence of green seeds (>95% higher than late sowing) and a drastic reduction in seed vigor, with longevity potential reduced by up to 63.6%. In contrast, late sowing functioned as a stress-escape strategy, shifting maturation to milder autumn conditions and consistently producing seeds of high vigor, viability, and greater longevity. Critically, during a season of extreme drought and heat, the late sowing not only preserved quality but also produced the highest grain yield, highlighting its decisive role in risk mitigation. Thus, sowing date is a key management tool for targeted production in these environments. Full article

Stinging nettle (Urtica dioica L.) is a multipurpose perennial plant with growing interest as a source of nutrients for both human and animal consumption. Despite its recognized nutritional potential, limited research has addressed how agronomic practices influence its nutritional quality. The aim of the present study was to assess the effects of plant density and fertilization on the micro- and macronutrient content of nettle plants and seeds. A three-year field experiment (2021–2024) was conducted under Mediterranean conditions using a split-plot design with two plant densities (12 and 16 plants m⁻²) and three nitrogen fertilization regimes [control (0 kg N ha⁻¹), urea (200 kg N ha⁻¹), and urea with urease inhibitor (200 kg N ha⁻¹)]. Results showed that nitrogen fertilization significantly affected macronutrient composition, increasing crude protein and crude carbohydrates (by up to 6% and 4% respectively) while reducing crude fat and fiber contents by up to 10% in nettle plants. However, fertilization negatively influenced the concentrations of Mg, Zn, K, and Mn in seeds and reduced their content by up to 16%, 4%, 9%, and 5% respectively. On the contrary, Fe and Cr increased under nitrogen application. Plant density had a minor effect on nutritional content, mainly improving protein accumulation in lower densities. Overall, U. dioica demonstrated a stable nutritional profile and high mineral content, therefore supporting its potential as a sustainable dual-purpose crop for food and feed systems. The findings of the present study indicate that proper crop management can significantly improve the nutrient content of nettle plants and seeds. Full article

Drought is a major abiotic stress that compromises seed germination, seedling establishment, and subsequent crop productivity, thereby threatening agricultural sustainability and food security. Developing effective seed-based strategies is therefore essential to enhance drought resilience. In this study, we investigated the efficacy of green-synthesized silver nanoparticles (AgNPs), produced using Azadirachta indica (neem) flower extract as a seed priming agent, to improve drought tolerance and early growth in wheat (Triticum aestivum). Seeds were primed with AgNPs (25–100 mg L⁻¹), PEG 6000 (−0.6, −0.8, and −1.0 MPa), and their combination (AgNPs + PEG 6000). AgNP priming enhanced germination by 72%, 86%, and 100% at 25, 50, and 75 mg L⁻¹, respectively, compared with the control, with 75 mg L⁻¹ identified as the optimal concentration. This treatment increased total chlorophyll and carotenoid contents by 14% and 6%, and elevated phenolic and flavonoid accumulation by 58% and 97%, respectively. Antioxidant enzyme activities were also substantially increased—catalase (CAT) by 44%, superoxide dismutase (SOD) by 23%, peroxidase (POX) by 11%, and glutathione reductase (GR) by 58%. Under drought stress, AgNP priming at 75 mg L⁻¹ improved germination by up to 80%, indicating enhanced drought tolerance. Elevated protein and antioxidant enzyme levels, along with reduced malondialdehyde (MDA), proline, and total soluble sugar levels, further confirmed mitigation of oxidative stress. Collectively, these results demonstrate that neem-mediated green-synthesized AgNPs could serve as an effective seed-priming agent, promoting wheat seedling establishment and enhancing drought resilience under water-deficit conditions. Full article

Efficient and climate-resilient Sorghum bicolor L. cultivation is increasingly important under Central European conditions. This study evaluated two hybrids across two locations in 2023–2024 with row spacings of 25, 45, and 75 cm and four sowing densities of 210,000–300,000 seed ha⁻¹. Row spacing, year, and genotype exerted a strong and consistent effect on grain yield and quality, with multiple instances reaching high statistical significance (p < 0.001). In contrast, seed rate had no significant main effect, influencing results only via site- and season-specific interactions. At a 45 cm row spacing, sorghum exhibited the highest grain yield (8.59 t ha⁻¹), the lowest seed moisture content (13.59%), and the greatest protein yield (1.094 t ha⁻¹). The 25 cm spacing with higher density produced with 0.46 t ha⁻¹ higher yields than 75 cm and the highest protein content (13.35%), but 0.48 t ha⁻¹ lower yield than the 45 cm treatment. The 75 cm spacing generally gave 12.29% lower yield and 6.72% lower quality despite higher tillering. TKW was highest at 45 cm row spacing (31.12 g), 23.3% greater than at 75 cm (25.25 g). The 45 cm row spacing provided the most stable yield, superior quality, and balanced agronomic performance, representing the most practical configuration for sustainable sorghum production under Central European conditions. Full article

Given the reduced resilience of the Amazon rainforest due to deforestation, identifying high-quality genetic markers for the propagation of native species is crucial for forest regeneration. This study investigated metabolic dynamics during Brazil nut (Bertholletia excelsa) germination to identify biochemical markers for selecting superior genotypes. We analyzed primary reserves (carbohydrates, lipids, proteins) and minerals in two genotypes, 606 and Santa Fé, in seven germination stages. Our results revealed distinct metabolic patterns. Genotype 606 showed 101.73% greater efficiency in the transient accumulation of starch, 34.86% higher degradation of lipids, and 34.86% higher transitory synthesis of soluble proteins. Conversely, Santa Fé was 16.8% more efficient in amino acid synthesis and 795.33% in boron compartmentalization, though less so in sucrose (2.17%) and in lipid synthesis (24.84%). Overall, early germination stages involved starch, sucrose degradation and mineral consumption. During post-germinative stages, protein and lipid degradation likely fueled gluconeogenic pathways and supported carbohydrate synthesis and seedling growth. This work increases the knowledge on Brazil nut germination physiology and identifies metabolic markers that differentiate genotypes. These findings are fundamental for our understanding of primary metabolism turnover in B. excelsa and provide a basis to support forest restoration and genetic improvement programs. In addition, we hope to contribute to the selection of superior high-performance genotypes, which are essential for recovering degraded areas and enhancing productive plantations in the Amazon region. Full article

Cover crop mixes play an important role in enhancing soil health, nutrient turnover, and ecosystem resilience; yet, maintaining even seed dispersion and planting uniformity is difficult due to significant variances in seed physical and aerodynamic properties. These discrepancies produce non-uniform seeding and species separation in drill hoppers, which has an impact on stand establishment and biomass stability. The thousand-grain weight is an important measure for determining cover crop seed quality and yield since it represents the weight of 1000 seeds in grams. Accurate seed counting is thus a key factor in calculating thousand-grain weight. Accurate mixed-seed identification is also helpful in breeding, phenotypic assessment, and the detection of moldy or damaged grains. However, in real-world conditions, the overlap and thickness of adhesion of mixed seeds make precise counting difficult, necessitating current research into powerful seed detection. This study addresses these issues by integrating deep learning-based computer vision algorithms for multi-seed detection and counting in cover crop mixes. The Canon LP-E6N R6 5D Mark IV camera was used to capture high-resolution photos of flax, hairy vetch, red clover, radish, and rye seeds. The dataset was annotated, augmented, and preprocessed on RoboFlow, split into train, validation, and test splits. Two top models, YOLOv5 and YOLOv7, were tested for multi-seed detection accuracy. The results showed that YOLOv7 outperformed YOLOv5 with 98.5% accuracy, 98.7% recall, and a mean Average Precision (mAP 0–95) of 76.0%. The results show that deep learning-based models can accurately recognize and count mixed seeds using automated methods, which has practical applications in seed drill calibration, thousand-grain weight estimation, and fair cover crop establishment. Full article