Search Results (1,524)

Astragalus sinicus, a key leguminous green manure widely cultivated in Southern China’s rice-based cropping systems, plays a pivotal role in sustainable agriculture by enhancing soil organic matter sequestration, improving rice yield, and elevating grain quality. The symbiotic nitrogen-fixing association between A. sinicus and its matching rhizobia is fundamental to its agronomic value; however, suboptimal inoculant efficiency and field application methodologies constrain its full potential. To address these limitations, we conducted a multi-phase study involving (1) rhizobial strain screening under controlled greenhouse conditions, (2) an optimized lyophilization protocol evaluating cryoprotectant (trehalose, skimmed milk powder and others), and (3) seed pelleting trails with rhizobial viability and nodulation assessments over different storage periods. Our results demonstrate that Mesorhizobium huakuii CCBAU 33470 exhibits a superior nitrogen-fixing efficacy, significantly enhancing key traits in A. sinicus, including leaf chlorophyll content, tiller number, and aboveground biomass. Lyophilized inoculants prepared with cryoprotectants (20% trehalose or 20% skimmed milk powder) maintained >90% bacterial viability for 60 days and markedly improved nodulation capacity relative to unprotected formulations. The optimized seed pellets sustained high rhizobial loads (5.5 × 10³ cells/seed) with an undiminished viability after 15 days of storage and nodulation ability after 40 days of storage. This integrated approach of rhizobial selection, inoculant formulation, and seed coating overcomes cultivation bottlenecks, boosting symbiotic nitrogen fixation for A. sinicus cultivation. Full article

Polyvinyl chloride (PVC) is commonly employed as mulch in agriculture to boost crop yields. However, its toxicity is often overlooked. Due to its chemical stability, resistance to degradation, and the inadequacy of the recycling system, PVC tends to persist in farm environments, where it can decompose into microplastics (MPs) or nanoplastics (NPs). The radish (Raphanus sativus L.) was chosen as the model plant for this study to evaluate the underlying toxic mechanisms of PVC NPs on seedling growth through the integration of multi-omics approaches with oxidative stress evaluations. The results indicated that, compared with the control group, the shoot lengths in the 5 mg/L and 150 mg/L treatment groups decreased by 33.7% and 18.0%, respectively, and the root lengths decreased by 28.3% and 11.3%, respectively. However, there was no observable effect on seed germination rates. Except for the peroxidase (POD) activity in the 150 mg/L group, all antioxidant enzyme activities and malondialdehyde (MDA) levels were higher in the treated root tips than in the control group. Both transcriptome and metabolomic analysis profiles showed 2075 and 4635 differentially expressed genes (DEGs) in the high- and low-concentration groups, respectively, and 1961 metabolites under each treatment. PVC NPs predominantly influenced seedling growth by interfering with plant hormone signaling pathways and phenylpropanoid production. Notably, the reported toxicity was more evident at lower concentrations. This can be accounted for by the plant’s “growth-defense trade-off” strategy and the manner in which nanoparticles aggregate. By clarifying how PVC NPs coordinately regulate plant stress responses via hormone signaling and phenylpropanoid biosynthesis pathways, this research offers a scientific basis for assessing environmental concerns related to nanoplastics in agricultural systems. Full article

Lotus corniculatus L. is a valuable fodder legume, recognized for its ecological adaptability and high potential for production and fodder quality. In this study, 18 genotypes collected from wild flora were analyzed to highlight genetic variability and facilitate the selection of genotypes with superior potential. The collection area was in the western part of Romania and featured a diverse topography, including parts of the Banat Plain, the Banat Hills, and the Southern and Western Carpathians. The genotypes selected from the wild flora were cultivated and evaluated for morpho-productive and forage quality traits, including pod weight, average number of seeds/pods, green mass production, and protein percentage. PCA highlighted the main components explaining the variability, and K-means clustering allowed for the identification of groups of genotypes with similar performances. ANOVA showed statistically significant differences (p < 0.001) for all traits analyzed. According to the results, genotypes LV-LC-3, LV-LC-4, LV-LC-6, and LV-LC-16 showed high productive potential and were highlighted as the most valuable for advancing in the breeding program. The moderate relationships between traits confirm the importance of integrated selection. The identified genetic variability and selected genotypes support the implementation of effective breeding strategies to obtain high-performance Lotus corniculatus L., adapted to local soil and climate conditions and with a superior forage yield. Full article

Conventional tillage and monocropping are common practices employed for cotton production in the Southern Great Plains (SGP) region, but they can be detrimental to soil health, crop yield, and water resources when improperly managed. Regenerative practices such as cover crops and conservation tillage have been suggested as an alternative. The proposed shift in management practices originates from the need to make agriculture resilient to extreme weather events including intense rainfall and drought. The objective of this study is to test the effects of these regenerative practices in an environment with limited rainfall. Runoff volume, nutrient and sediment concentrations and loadings, and surface soil moisture levels were compared on twelve half-acre (0.2 hectare) cotton plots that employed different cotton seeding rates and variable winter wheat cover crop presence. A winter cover implemented on plots with a high cotton seeding rate significantly reduced runoff when compared to other treatments (p = 0.032). Cover cropped treatments did not show significant effects on nutrient or sediment loadings, although slight reductions were observed in the concentrations and loadings of total Kjeldahl nitrogen, total phosphorus, total solids, and Escherichia coli. The limitations of this study included a short timeframe, mechanical failures, and drought. These factors potentially reduced the statistical differences in several findings. More efficient methods of crop production must continue to be developed for agriculture in the SGP to conserve soil and water resources, improve soil health and crop yields, and enhance resiliency to climate change. Full article

We summarize our present knowledge of the regulation of photostasis and photosynthetic performance versus photoprotection in response to vernalization and conclude that the enhanced photosynthetic performance of winter crops is due to an inherent increase in photosynthetic energy conversion efficiency induced by vernalization which translates into high seed yield in the field as well as under controlled environment conditions. This is consistent with the published data for enhanced photosynthetic performance of the only two extant terrestrial angiosperms, Colobanthus quitensis and Deschampsia antarctica, native to the frigid conditions of terrestrial Antarctica. The Cold Binding factor family of transcription factors (CBFs/DREBs) governs the enhanced photosynthetic performance of winter cereals as well as the Antarctic angiosperms. In contrast to winter crops, spring varieties survive cold environments by stimulating photoprotection at the expense of photosynthetic performance like that observed for green algae and cyanobacteria. Consequently, this minimizes the photosynthetic energy conversion efficiency of spring varieties and limits their seed yield upon cold acclimation. This review provides critical insights into the regulation of photostasis and the balance between photosynthetic performance and photoprotection in plants and how vernalization has enhanced photosynthetic energy conversion, which is essential for understanding plant adaptation to cold environments and optimizing agricultural productivity for improving crop resilience and yield in challenging climates. Full article

This study investigated the impact of nitrogen (N) fertilization on the yield and grain filling (GF) characteristics of two conventional japonica rice varieties with distinct panicle types: Yangchan 3501 (large-panicle: spikelets per panicle $> 150$) and Nangeng 46 (medium-panicle: $100 <$ spikelets per panicle $< 150$). Field experiments were conducted over two growing seasons (2022–2023) with three N application rates (T1: 225 kg ha⁻¹, T2: 270 kg ha⁻¹, T3: 315 kg ha⁻¹). Key measurements included tiller dynamics, panicle composition, GF parameters modeled using the Richards equation, and enzyme activities related to nitrogen metabolism (Fd-GOGAT, NR) and carbohydrate transport (α-amylase, SPS). Results showed that the yield increased with higher N levels for both varieties, with Yangchan 3501 achieving higher yields primarily through increased grains per panicle (15.65% rise under T3 vs. T1), while Nangeng 46 relied on panicle number (8.83% increase under T3 vs. T1). Nitrogen application enhanced Fd-GOGAT and NR activities, prolonging photosynthesis and improving GF rates, particularly in the inferior grains of Yangchan 3501 during middle and late stages. However, a high N reduced seed-setting rates and 1000-grain weight, with larger panicle types exhibiting a greater sensitivity to N-induced changes in branch structure and assimilate allocation. This study highlights that optimizing N management can improve nitrogen-metabolism enzyme activity and GF efficiency, especially in large-panicle rice, while medium-panicle types require higher N inputs to maximize panicle number. These findings provide actionable insights for achieving high yields and efficient nutrient use in conventional rice cultivation. Full article

Vegetable oils are essential for human nutrition and industrial applications. With growing global demand, increasing oil content in oilseed crops has become a top priority. This review synthesizes recent progress in understanding the genetic, environmental, and molecular mechanisms regulating oil content, and presents biotechnological strategies to enhance oil accumulation in major oilseed crops. Oil biosynthesis is governed by intricate genetic–environmental interactions. Environmental factors and agronomic practices significantly impact oil accumulation dynamics. Quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) have identified key loci and candidate genes involved in lipid biosynthesis pathways. Transcription factors and epigenetic regulators further fine-tune oil accumulation. Biotechnological approaches, including marker-assisted selection (MAS) and CRISPR/Cas9-mediated genome editing, have successfully generated high-oil-content variants. Future research should integrate multi-omics data, leverage AI-based predictive breeding, and apply precision genome editing to optimize oil yield while maintaining seed quality. This review provides critical references for the genetic improvement and breeding of high- and ultra-high-oil-content varieties in oilseed crops. Full article

Tomato processing waste (TPW) represents a valuable but underutilized by-product of the food industry with potential for valorization within bioeconomy models. This study investigated the chemical composition, antioxidant profile, and sanitary safety of TPW, analyzing the whole TPW; its fractions (peels and seeds) and oil are obtained from TPW seeds. All samples showed contaminant levels within regulatory limits, confirming their safety for further applications. Various drying methods (air-drying at 70 °C and at 50 °C, lyophilization and vacuum drying) and grinding intensities were evaluated to determine their impact on TPW bioactive compounds retention and organoleptic characteristics. TPW exhibited valuable nutritional properties, particularly high protein and dietary fiber content while TPW oil was characterized with high monounsaturated fatty acid content. Results demonstrated that drying method and particle size significantly influenced the yield of bioactive compound and organoleptic properties, with either lyophilization or vacuum drying and finer milling generally enhancing the recovery of polyphenols, β-carotene, and lycopene and improving color intensity. This research provides the first characterization of the TPW obtained from Croatian indigenous tomato varieties, establishing a scientific foundation for its sustainable valorization and, in broader terms, supporting circular economy objectives and contributing to more resource-efficient food systems. Full article

Functional flours, high in bioactive compounds, have garnered increasing attention, driven by consumer demand for alternative ingredients and the nutritional limitations of wheat flour. This study explores the thermal stability of phenolic compounds in various functional flours using visible, near and shortwave-infrared (Vis–NIR–SWIR) spectroscopy (350–2500 nm), integrated with machine learning (ML) algorithms. Random Forest models were employed to classify samples based on flour type, baking temperature, and phenolic concentration. The full spectral range yielded high classification accuracy (0.98, 0.98, and 0.99, respectively), and an explainability framework revealed the wavelengths most relevant for each class. To address concerns regarding color as a confounding factor, a targeted spectral refinement was implemented by sequentially excluding the visible region. Models trained on the 1000–2500 nm and 1400–2500 nm ranges showed minor reductions in accuracy, suggesting that classification is not solely driven by visible characteristics. Results indicated that legume and wheat flours retain higher total phenolic content (TPC) under mild thermal conditions, whereas grape seed flour (GSF) and olive stone flour (OSF) exhibited notable thermal stability of TPC even at elevated temperatures. These first findings suggest that the proposed non-destructive spectroscopic approach enables rapid classification and quality assessment of functional flours, supporting future applications in precision food formulation and quality control. Full article

To elucidate the photosynthetic physiological mechanisms influencing alfalfa (Medicago sativa L.) yield and quality under varying planting densities, the cultivar ‘Zhongmu No.1’ was used as experimental material. The effects of different row spacing (R1, R2, R3) and seeding rate (S1, S2, S3, S4, S5) combinations on chlorophyll content (ChlM), nitrogen flavonol index (NFI), chlorophyll fluorescence parameters, forage quality, and hay yield were systematically analyzed. Results showed that alfalfa under R1S3 treatment achieved peak values for ChIM, NFI, EE, and hay yield, whereas R1S4 treatment yielded the highest Fv/Fm and CP content. Redundancy analysis further indicated that yield was most strongly associated with ChlM, NFI, Y (II), and qP. Y (II), and qP significantly influenced alfalfa forage quality, exerting negative effects on ADF and NDF, while demonstrating positive effects on CP and EE. In conclusion, narrow row spacing (15 cm) with moderate seeding rates (22.5–30 kg·hm⁻²) optimizes photosynthetic performance while concurrently enhancing both productivity and forage quality in alfalfa cultivated, establishing a theoretical foundation for photosynthetic regulation in high-quality and high-yield alfalfa cultivation. Full article

Durum wheat, the world’s second most cultivated wheat species, is a staple crop, critical for global food security, including in Ethiopia where it serves as a center of diversity. However, climate change and genetic erosion threaten its genetic resources, necessitating genomic studies to support conservation and breeding efforts. This study characterized genome-wide diversity, population structure (STRUCTURE, principal coordinate analysis (PCoA), neighbor-joining trees, analysis of molecular variance (AMOVA)), and selection signatures (F_ST, Hardy–Weinberg deviations) in Ethiopian durum wheat by analyzing 376 genotypes (148 accessions) using an Illumina Infinium 25K single nucleotide polymorphism (SNP) array. A set of 7842 high-quality SNPs enabled the assessments, comparing landraces with cultivars and breeding populations. Results revealed moderate genetic diversity (mean polymorphism information content (PIC) = 0.17; gene diversity = 0.20) and identified 26 loci under selection, associated with key traits like grain yield, stress tolerance, and disease resistance. AMOVA revealed 80.1% variation among accessions, with no significant differentiation by altitude, region, or spike density. Landraces formed distinct clusters, harboring unique alleles, while admixture suggested gene flow via informal seed exchange. The findings highlight Ethiopia’s rich durum wheat diversity, emphasizing landraces as reservoirs of adaptive alleles for breeding. This study provides genomic insights to guide conservation and the development of climate-resilient cultivars, supporting sustainable wheat production globally. Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

Efficient and consistent DNA extraction is crucial for genotyping but often hindered by the limitations of traditional manual processes, which are labour-intensive, error-prone, and costly. We introduce a semi-automated, robotic-assisted DNA extraction (RoboCTAB) tailored for large-scale plant genotyping, leveraging advanced yet affordable liquid-handling robotic systems. The protocol/workflow integrates a CTAB extraction protocol specifically adapted for a robotic liquid-handling system, making it compatible with high-throughput genotyping techniques such as SNP genotyping and sequencing. Various plant parts (leaves, roots, manual seed chip) were explored as the source material for DNA extractions, with the aim of identifying the tissue best suited for collection on a large scale. Young roots (radicle) proved the easiest to harvest at scale, while the harvest of leaves and seed chips were more laborious and error-prone. DNA yield and quality from both leaves and roots (but not seed chips) were similar and sufficient for downstream analysis. Interestingly, root tissue could still be extracted from imbibed seeds, even if the seeds failed to germinate, thus proving useful for DNA extraction. Cost analysis indicates significant savings in labour costs, highlighting the approach’s suitability for large-scale projects. Quality assessments demonstrate that the robotic process yields high-quality DNA, maintaining integrity for downstream applications. This semi-automated DNA extraction system represents a scalable, reliable solution for large-scale genotyping that is accessible to many users who cannot implement highly sophisticated and costly systems as are known to exist in large multinational seed companies. RoboCTAB, a low-cost, optimized method for high-throughput DNA extraction, minimizes the risk of cross-contamination. RoboCTAB is capable of processing up to four 96-well plates (384 samples) simultaneously in a single run, improving cost-efficiency and providing seamless integration with laboratory workflows, potentially setting new standards for efficiency and quality in DNA processing and sequencing at scale. Full article

Traditional seed supply chains face several hidden risks. Certain regulatory departments tend to focus primarily on entity circulation while neglecting the origin and accuracy of data in seed quality supervision, resulting in limited precision and low credibility of traceability information related to quality and safety. Blockchain technology offers a systematic solution to key issues such as data source distortion and insufficient regulatory penetration in the seed supply chain by enabling data rights confirmation, tamper-proof traceability, smart contract execution, and multi-node consensus mechanisms. In this study, we developed a system that integrates blockchain and neural networks to provide seed traceability services. When uploading seed traceability information, the neural network models are employed to verify the authenticity of information provided by humans and save the tags on the blockchain. Various neural network architectures, such as Multilayer Perceptron, Recurrent Neural Network, Fully Convolutional Neural Network, and Long Short-term Memory model architectures, have been tested to determine the authenticity of seed traceability information. Among these, the Long Short-term Memory model architecture demonstrated the highest accuracy, with an accuracy rate of 90.65%. The results demonstrated that neural networks have significant research value and potential to assess the authenticity of information in a blockchain. In the application scenario of seed quality traceability, using blockchain and neural networks to determine the authenticity of seed traceability information provides a new solution for seed traceability. This system empowers farmers by providing trustworthy seed quality information, enabling better purchasing decisions and reducing risks from counterfeit or substandard seeds. Furthermore, this mechanism fosters market circulation of certified high-quality seeds, elevates crop yields, and contributes to the sustainable growth of agricultural systems. Full article

As a unique woody oil crop in China, Camellia oleifera Abel. germplasm resources show significant genetic diversity in Ya’an City. This study measured 60 phenotypic traits (32 quantitative, 28 qualitative) of 302 accessions to analyze phenotypic variation, establish a classification system, and screen high-yield, high-oil germplasms. The phenotypic diversity index for fruit (H’ = 1.36–1.44) was significantly higher than for leaf (H’ = 1.31) and flower (H’ < 1), indicating genetic diversity concentrated in reproductive traits, suggesting potential genetic variability in these traits. Fruit quantitative traits (e.g., single fruit weight CV = 35.37%, fresh seed weight CV = 38.93%) showed high genetic dispersion. Principal component analysis confirmed the fruit factor and economic factor as main phenotypic differentiation drivers. Quantitative traits were classified morphologically, and correlation analysis integrated them into 13 key indicators classified using LSD and range methods. Finally, TOPSIS evaluation selected 10 excellent germplasms like TQ122 and TQ49, with fruit weight, fresh seed yield, and kernel oil content significantly exceeding the population average. This study provides data for C. oleifera DUS test guidelines and proposes a multi-trait breeding strategy, supporting high-yield variety selection and germplasm resource protection. Full article