Search Results (5,278)

Sorghum is a climate-resilient crop; however, recurrent drought and shorter rainy seasons limit its productivity. Sorghum grain yield (GY), biomass production (AGB), and harvest index (HI) are influenced by the genetic composition and plasticity of the maturity period. Limited studies have examined the effect of the maturity period on these traits. This study evaluated 106 diverse sorghum genotypes to determine the effect of maturity period on these traits to identify contrasting genotypes for breeding and production. Field trials were conducted during the 2023/24 and 2024/25 seasons using a 10 × 11 alpha lattice design. During season I, late-maturing genotypes produced GY and AGB values 28.8% and 51.2% higher than early-maturing genotypes and 34.9% and 54.4% higher than medium-maturing genotypes, respectively, but recorded 19.24% and 12.28% lower HIs than the early- and medium-maturing genotypes, respectively. In season II, late-maturing genotypes had a 10.43% and 34.49% lower GY and HI, respectively, yet a 92.69% higher AGB than early-maturing genotypes. Compared with medium-maturing types, late-maturing genotypes had a 2.32% and 24.1% lower GY and HI, respectively, but a 52.96% higher AGB. The findings demonstrated that the effect of maturity period on sorghum GY, AGB, and HI is strongly influenced by the genetic potential for crop maturation and environmental conditions. Genotypes AS232, AS603, and AS580 combined early maturity and higher GY, AGB, and HI values, making them promising candidates for cultivation and breeding in drought-prone agroecologies. Full article

Agricultural carbon emissions, a key part of terrestrial carbon emissions, affect global carbon accounting, with historical data scarcity adding to calculation difficulty. Exploring agricultural planting structure evolution can supplement historical data and improve accounting accuracy. Based on local chronicles and statistics, this study reconstructs Northeast China’s planting structure of six major crops during the 1950s–1980s via threshold classification and transfer matrix methods. Results show high-carbon crops (corn in particular) expanded notably, while low-carbon crops (especially sorghum) declined. Planting patterns varied regionally, with the most complex structural changes occurring in the 1960s–1970s. Agricultural carbon emissions fluctuated in phases; the planting scale effect dominated emission growth, the intensity effect inhibited it, and the structural effect played a heterogeneous auxiliary role. This study provides a historical basis for low-carbon agricultural planning and differentiated carbon reduction policies. Full article

Agricultural seeds are sold as commodities yet seed quality can be non-uniform. Despite the extensive literature showing that plasma treatments of seeds provides advantages for many crops, lettuce studies, particularly in indoor farming systems, are limited. This study provides a systematic investigation of the impacts of non-thermal plasma treatments with various feed gases (N₂, O₂, dry air, and wet air) on the germination and growth characteristics of four lettuce cultivars (Red Oakleaf (RO), Black Simpson (BS), Valley Heart Romaine (VHR), and Paris Romaine (PR)) under controlled cultivation conditions in an agrivoltaic agrotunnel. Although the germination time was not conclusively affected by the treatments, the results show a complex interaction between germination rate and yield across the different cultivars and plasma treatments. Except for PR seeds (77.8% vs. 65.8% control), wet air plasma treatments increased germination rates by 18.7–100% over controls for all other cultivars. In yield analysis, wet air treatment had the strongest effect, especially for VHR (51.7 vs. 42.5 g/pot). Treatments did not notably affect RO. For BS, N₂ treatment gave the highest increase (54.2 vs. 48.1 g/pot), while PR responded best to O₂ treatment (58.4 vs. 51.8 g/pot). The energy consumption of plasma treatments was negligible for all treatments, while labor costs for small batches of seeds accounted for the largest share of secondary operating costs (839, 622, and 659 h/year, respectively for BS, VHR, and PR). Despite additional expenses, including labor, O&M, and degradation costs, the reduced seed requirements from higher germination rates and higher yield increased net profit by 12.0% compared to untreated cultivation in the most impacted (Valley Heart Romaine) lettuce. There is an opportunity for further cost optimization of the non-thermal plasma treatment for each type of lettuce seed. Full article

Convolutional Neural Networks have shown promising effectiveness in identifying different types of cancer from radiographs. However, the opaque nature of CNNs makes it difficult to fully understand the way they operate, limiting their assessment to empirical evaluation. Here we study the soundness of the standard practices by which CNNs are evaluated for the purpose of cancer pathology. Thirteen highly used cancer benchmark datasets were analyzed, using four common CNN architectures and different types of cancer, such as melanoma, carcinoma, colorectal cancer, and lung cancer. We compared the accuracy of each model with that of datasets made of cropped segments from the background of the original images that do not contain clinically relevant content. Because the rendered datasets contain no clinical information, the null hypothesis is that the CNNs should provide mere chance-based accuracy when classifying these datasets. The results show that the CNN models provided high accuracy when using the cropped segments, sometimes as high as 93%, even though they lacked biomedical information. These results show that some CNN architectures are more sensitive to bias than others. The analysis shows that the common practices of machine learning evaluation might lead to unreliable results when applied to cancer pathology. These biases are very difficult to identify, and might mislead researchers as they use available benchmark datasets to test the efficacy of CNN methods. Full article

Straw compost products are considered an excellent organic amendment for acidic soils, yet their effectiveness and microbial associations remain poorly understood. This study employed a pot experiment to evaluate the effects of straw compost products from six crops (corn, soybean, wheat, rice, peanut, and canola) on corn growth and nutrient uptake, soil physicochemical properties, and microbial community in an acidic red soil and examined how microbial community changes relate to plant performance. The results showed that straw compost products significantly enhanced corn growth and contents of nitrogen, phosphorus, and potassium in the aboveground tissues, except for wheat and canola straw. Compost products also improved availability of soil nutrients to varying degrees and affected the bacterial community structures in bulk and rhizosphere soils. There were significant differences in the improvement effects among straw types, with leguminous crops being better than cereal crops. Corn growth was closely correlated with increased soil organic carbon. The influence of the rhizosphere on bacterial communities was stronger than that of straw compost type. The dominant phyla Actinobacteriota and Patescibacteria were key bacterial groups positively associated with corn nutrient uptake in the rhizosphere. Compared to the bulk network, the rhizosphere microbial co-occurrence network exhibited higher modularity and a greater proportion of positive edges, suggesting a more cooperative interaction pattern. The influence of compost products might be associated with distinct nitrogen and phosphorus transformation pathways. Overall, this study clarifies the differential effects of straw compost products on acidic soil improvement and reveals strong associations between rhizosphere microorganisms and crop nutrient uptake. Full article

Following the transfer of farmland, new agricultural entities exhibit clearer profit-oriented goals and heightened sensitivity to changes in profitability. Changes in farmland transfer prices significantly affect producers’ crop selection, input choices, technology adoption, farming methods, and intensity. This study establishes a motivation–behavior–outcome analytical framework by integrating producer behavior theory with the mechanism of farmland health formation, suggesting that rising transfer prices may prompt producers to exhibit five types of positive or negative behaviors. The SBM-DEA model is employed to measure the grain green total factor productivity of farmland across 102 counties in China’s Henan Province from 2017 to 2022, reflecting the healthy utilization of farmland. Results from the two-way fixed-effects and threshold effect models reveal an inverted U-shaped relationship, indicating initially positive and later negative impacts of increasing transfer prices on farmland health utilization. GTWR model findings highlight that economic disparities and the pace of price increases dictate the intensity of producers’ positive and negative motivations, while the economic capacity for absorbing shocks and the natural endowment capacity for absorbing shocks influence the likelihood and magnitude of these effects. Government regulation should, therefore, focus on regulating producer interests. Full article

Land is the fundamental basis for maintaining agricultural production and ensuring food security. The task of managing and sustainably utilizing land resources has always been a priority for every country in the world. The study used GIS-MEC technology to integrate data from seven types of single-factor maps to construct a soil quality map with 47 land units (including eight land units with an area >100 ha, 29 land units with an area from 10 to 100 ha, and 10 land units with an area <10 ha). In addition, by combining soil quality maps and the nutritional needs of different crops, an assessment of land suitability for six major crops was conducted, and three key crops were selected for focused development: rice, vegetables, and flowers. The application of GIS in soil quality management is in line with the current trends of digital transformation and integrated data management in Vietnam and around the world. However, this method has several limitations that need to be considered when applying it, such as dependence on expert expertise, high demands on input data and verification of output results, and limitations in analyzing trends and analyzing social, non-linear factors. Full article

Integrated Pest Management (IPM) is a well-established framework for agricultural crop protection. IPM has typically been represented as a pyramid of practices, beginning at the base with agronomic and cultural approaches and gravitating upwards towards chemical plant protection products. However, this representation is an insufficient description of IPM adoption at the farm level as it cannot incorporate the many challenges faced by farmers and growers. This paper presents an alternative approach to contextualize horticultural IPM based on a sample of commercial vegetable and fruit growers from the Republic of Ireland (N = 45), based on an existing model. This model incorporates the management, business, and sustainability aspects influencing IPM adoption. Utilization of the model on data collected from growers through a series of semi-structured interviews contributed to a. a comprehensive exploration of the type of IPM tools being used and b. contextualized analysis of the data with the intention of capturing grower perspectives. The findings highlight a crop and production system effect on the type of IPM tools used by the growers and suggest influence from a range of internal and external motivating and limiting factors. Excerpts from the grower interviews underline the complexity of IPM and draw attention to the lack of grower-centricity captured by IPM paradigms heretofore. Full article

Large-scale agricultural remote sensing monitoring is challenged by pronounced spatial heterogeneity arising from fragmented terrain, complex climatic backgrounds, and diverse cropping structures. However, existing agricultural zoning schemes generally lack an integrated consideration of remote sensing imaging mechanisms and key variable conditions such as atmospheric interference and crop phenology, limiting their direct utility in guiding region-specific sensor selection and classification algorithm calibration. To address this limitation, this study integrates multi-source earth observation data and agricultural statistical information to construct an Agricultural Remote-sensing Classification Difficulty Index (ARCDI) from multiple dimensions, including image availability, cropping structure, cropland fragmentation, and topographic environment. On this basis, a graph theory-based spatially constrained Skater clustering algorithm is introduced to establish a two-tier “cropland–major cereal crops” zoning framework oriented toward remote sensing applications. The results indicate that the proposed framework delineates five distinct first-tier cropland classification difficulty zones across China. This zoning scheme effectively quantifies the regional heterogeneities in monitoring challenges. Building upon this first-tier zoning, the framework is further refined into 50 second-tier major cereal crop classification difficulty zones, including 13 winter wheat zones, 21 maize zones, and 16 rice zones. Statistical tests and spatial analyses demonstrate that the proposed zoning scheme significantly outperforms conventional clustering approaches in balancing within-zone homogeneity and spatial continuity. This advantage is quantitatively reflected by consistently lower residual spatial autocorrelation (residual Moran’s I ≈ 0.10–0.11) and an approximately 20% reduction in within-zone variance compared with other spatially constrained methods. Extensive field-sample validation provides preliminary evidence of an inverse relationship between crop-type classification difficulty and accuracy. These results confirm the framework’s reliability in identifying regional difficulty and its decision-support value for selecting remote sensing strategies. Overall, this study systematically elucidates the spatial differentiation patterns of remote sensing classification difficulty for cropland and major cereal crops across China. The proposed framework provides robust scientific support for data selection, algorithm optimization, and differentiated strategy formulation in national-scale agricultural monitoring, thereby facilitating the operationalization of regional agricultural remote sensing applications. Full article

Large-scale forest pest management has traditionally relied on aerial spraying; however, increasing regulatory restrictions and environmental concerns have limited its application in many regions. Unmanned Aerial Spraying System (UASS) platforms for aerial spraying have developed intensively in the last decade for pesticide application in agricultural crops but remain scarcely explored within the forestry sector. This study evaluates the feasibility of UASS-based spraying platforms for forest pest control. We tested a multi-rotor agricultural UASS in two different forest conditions: broadleaf and conifer stands. Both biological and synthetic insecticides were sprayed against two contrasting forest pests, Lymantria dispar and Adelges laricis. Defoliation and infestation intensity were used to assess treatment efficacy post-application. Results indicated differences in operational productivity between forest stand types, with higher treatment efficacy observed for L. dispar. Despite the correct dosage delivered by the UASS, the target organism showed a limited biological response in the conifer pest. In conclusion the use of UASSs in forest ecosystems is conditioned by forest-specific factors; however, these technologies show potential to be aligned with interventions targeting early-stage pest outbreaks. Full article

In recent years, microplastics (MPs) pollution in agricultural soils has increased markedly, largely due to the improper management of plastic mulch films used to improve crop growing conditions. In this context, the present study evaluated the use of biochar (BC) as a soil amendment for mulch-derived MPs-contaminated soils in a radish (Raphanus sativus L.) crop under greenhouse conditions. A pot experiment was established in soils contaminated with MPs (0.5% w/w) and amended with four BC rates (w/w): 0% (Control), 1% (BC1), 3% (BC3), and 5% (BC5). Soil physicochemical indicators were assessed, together with germination, leaf, and radish bulb growth parameters. The experiment was conducted under greenhouse conditions until the radishes reached commercial maturity. Most of the soil’s physicochemical indicators, such as hydrogen potential (pH), electrical conductivity (EC), water holding capacity (WHC), total organic carbon (TOC), organic matter (OM), total nitrogen (TN), ammonium (N–NH₄⁺) and nitrates (N–NO₃⁻), showed significant differences between treatments (p < 0.05), with the exception of the carbon-nitrogen ratio (C/N), which did not vary significantly (p ≥ 0.05). No significant differences were observed among treatments (p ≥ 0.05) for germination indicators. For leaf traits, dry biomass was significantly lower in BC1 than in the other treatments (p < 0.05). For radish bulb traits, fresh weight was significantly higher in BC3 (p < 0.05) compared with the other treatments. Similarly, total plant fresh weight showed significant differences among treatments, with BC3 exhibiting the highest value (p < 0.05). Overall, the BC3 treatment provided the greatest improvement in radish development in MPs-contaminated soil. However, further research involving different types of MPs, BCs, or other crop species is needed to more comprehensively assess the impact of BC on agricultural soils contaminated with MPs. Full article

Sugarcane (Saccharum spp.) is a globally vital sugar crop, yet its productivity faces severe challenges from infestation by Chilo sacchariphagus. To decipher the plant’s molecular and metabolic defense mechanisms, this study applied an integrated transcriptomic and metabolomic analysis to three field-grown sugarcane cultivars (Zhongtang 4, 5, and 6) under natural borer stress. The transcriptomic analysis identified a total of 34,004 differentially expressed genes (DEGs), of which 18,674 were up-regulated, and 15,330 were down-regulated. The three cultivars exhibited distinct transcriptional regulatory patterns: Z4 and Z5 showed a global suppression-type response and a strong activation-type response, respectively, and Z6 presented a balanced-type response. A functional enrichment analysis revealed that the DEGs were significantly involved in metabolic processes, stress response, plant hormone signal transduction, phenylpropanoid biosynthesis, and plant-pathogen interaction pathways. Metabolomic analysis detected 963 differentially accumulated metabolites (DAMs), primarily including flavonoids, phenolic acids, amino acids and their derivatives, and lipids. These metabolites were significantly enriched in pathways such as amino acid metabolism, biosynthesis of secondary metabolites, and glutathione metabolism. Integrated multi-omics analysis further revealed strong synergistic regulatory relationships between gene expression and metabolite accumulation, particularly in defense-related secondary metabolic pathways, such as phenylpropanoid and flavonoid biosynthesis. Several key regulatory hubs were identified, including novel transcripts and D-xylulose-5-phosphate. Sugarcane employs a genetic background-dependent, multi-layered transcriptional reprogramming and metabolic restructuring to cope with borer stress. Cultivars Z4 and Z6 tend to activate and accumulate defensive compounds, while Z5 exhibits a different pattern of metabolic resource allocation. This research provides a systematic elucidation of the molecular mechanisms underlying insect resistance in sugarcane and offers important candidate genes and metabolites for breeding resistant varieties. Full article

Background: LATERAL ORGAN BOUNDARIES DOMAIN (LBD/AS2) transcription factors integrate developmental and hormonal signals during organogenesis. As a high-value fruit tree crop, blueberries’ rooting ability underpins their vegetative propagation and field performance, yet a genome-wide view of the LBD repertoire and its roles in blueberry has been lacking. Results: We cataloged 153 non-redundant LBD genes (VcLBD) by homology search against the GDV RefTrans V1 genome and domain validation, substantially exceeding counts reported for other fruit crops. Phylogeny resolved the family into the canonical Class I/II and seven subclades, with extensive lineage-specific expansion supported by synteny: 72.31% of loci arose from whole-genome/segmental and tandem duplication. Gene structures were highly heterogeneous (2–24 exons) but conserved within clades; motif profiling (MEME/InterPro) recovered the signature LOB cysteine block, GAS module and a leucine-zipper-like motif with clade-specific combinations. Promoter scanning identified 38 cis-element types, including hormone- (auxin, cytokinin, GA, JA/MeJA, ABA, SA), stress- and meristem-associated motifs, indicating broad regulatory inputs. Public transcriptomes revealed pronounced tissue–stage specificity with a root-centered bias; qRT-PCR across eight organs/stages validated four archetypal expression programs (higher expression in roots, flowers, fruits in stage 1, or mature fruit, respectively), including floral/early-fruit enrichment (e.g., VcLBD39/40) and ripening-associated induction. Hormone assays demonstrated differential responsiveness: IAA up-regulated VcLBD6/16b/33c/40e/41, whereas 6-BA suppressed VcLBD16b/33c/39a/39c/40e and induced VcLBD41/46h; ACC and MeJA produced gene-specific induction or repression. During adventitious rooting (0/4/7/10 DAC), 30 VcLBDs were differentially expressed, forming three temporal patterns. VcLBD16b reaches its peak expression during the early stages of adventitious root development and exhibits a strong response to auxin. VcLBD11 shows dynamic changes synchronized with cytokinin activity, while VcLBD33/40 is associated with primordia growth and vascular-related processes. Conclusions: We identified and characterized 153 VcLBD genes, profiled their transcripts across multiple blueberry tissues, defined stages of adventitious root development, and evaluated hormone responsiveness for representative members. Together, these results establish a foundation for dissecting VcLBD regulatory mechanisms and functions, particularly in organ growth and adventitious rooting. Full article

Drought and salt stresses severely impair plant growth and development worldwide. DEHYDRATION-RESPONSIVE ELEMENT BINDING proteins (DREBs), as a subfamily of the AP2/ERF transcription factor superfamily, play critical regulatory roles in plant biological processes including growth and development, as well as the adaptive response to various abiotic stresses. Based on the transcriptome data analysis of Medicago truncatula under saline-alkali stress previously conducted in our laboratory, a gene responsive to saline-alkali stress, Medtr3g110205, was identified, and its homologous gene in Arabidopsis thaliana, AtERF41 (AT5G11590), was obtained via BLAST (version BLAST+ 2.17.0.). The mutant erf41 was used to explore its biological functions in response to drought and salt stresses. The results showed that under salt and drought stress conditions, the seed germination rate, and growth status of the erf41 mutant were all better than those of the wild type. Further determination of physiological and biochemical indicators revealed that the leaf contents of superoxide dismutase (SOD) and proline (Pro) in the leaves of the mutant plants were significantly higher than those in the wild type, while the malondialdehyde (MDA) content was significantly decreased. In conclusion, the AtERF41 gene negatively regulates salt and drought tolerance in Arabidopsis thaliana, providing a potential target for the genetic improvement of crop stress tolerance. This study not only deepens our understanding of the role of DREB transcription factors in plant stress response but also provides a theoretical basis for improving crop stress tolerance using genetic engineering technology in the future. Full article

Silage additives formulated with lactic acid bacteria (LAB) are commonly applied to enhance fermentation efficiency and aerobic stability. However, comparative evaluations across different forage species are still scarce. This in vitro experiment assessed the influence of eleven commercial silage inoculants containing various combinations of homo- and heterofermentative LAB on fermentation dynamics, nutrient conservation, and aerobic stability of medium-wilted alfalfa (Medicago sativa L.), perennial ryegrass (Lolium perenne L.), and red clover/perennial ryegrass silages. Experimental silages were prepared in 3 L laboratory silos and stored for 90 days. All inoculated treatments exhibited significantly lower pH values at both 3 and 90 days of ensiling compared with the untreated control (p < 0.05). LAB application increased the concentration of total fermentation acids and lactic acid in all forage types, although responses varied depending on inoculant composition. Inoculants containing Lentilactobacilllus buchneri produced the greatest acetic acid concentrations and resulted in a marked enhancement of aerobic stability. Compared with the control, silage inoculation significantly decreased dry matter losses by 35–64% and ammonia-N proportion by 20–37%, leading to an additional dry matter recovery of 1.29–2.87%. Control silages showed the lowest aerobic stability (97.2 h), while inoculated silages ranged from 126.0 to 200.4 h, with the extent of improvement differing among forage species and LAB formulations. In conclusion, commercial silage inoculants incorporating diverse LAB strains effectively improve fermentation quality, limit nutrient degradation, and enhance aerobic stability of legume and grass silages under controlled experimental conditions. Full article