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Ratoon rice, the cultivation of a second crop from the stubble after the main harvest, is recognized as an eco-friendly and resource-saving method for rice production. Here, a field experiment was carried out in the Yangtze River region to investigate the impact of varying stubble heights on the grain quality of ratoon rice, as well as to compare the grain quality between the main and ratoon season. This study, which focused on 12 commonly cultivated rice varieties, conducted a comprehensive analysis assessing milling characteristics, appearance, and cooking quality. The results show that ratoon rice crops exhibited a higher milled rice rate and head rice rate compared to the main rice crops. Conversely, chalky rice percentage, chalkiness degree, and amylose content were lower in ratoon rice crops. Principal component analysis grouped eight relevant quality indicators of rice quality which were concentrated into three categories, with amylose content identified as the key indicator of rice quality for distinguishing between different stubble heights. Random forest results reveal a robust and significant correlation between appearance quality index and amylose content. Subordinate function analysis indicated that a stubble height of 30 cm resulted in optimal rice quality, with Lingliangyou 211 exhibiting the highest quality and Xiangzao Xian 32 the lowest. Overall, our study suggests that ratoon rice crops generally outperform main rice crops in terms of quality, with the optimal measurement at a stubble height of 30 cm. This study holds substantial importance for selecting appropriate stubble heights for ratoon rice crops and enhancing overall rice quality. [ABSTRACT FROM AUTHOR]

Iron is an essential element for plants growth and development. Biofortification has become an efficient way for iron accumulation in grains to enhance the nutritional quality of crops. Both iron and sucrose are transported via phloem during grain filling in rice. However, the relationship between iron and sucrose transport remains unclear. In this study, we aimed to elucidate the relationship between sucrose transport and iron accumulation in rice. We first found that the efficient iron accumulated stage and sucrose unloading stage overlapped at 5–10 DAF during grain filling. The close relationship was further validated by transgenic lines (Y2 and Y6) overexpressing yeast (Y) invertase (INV). The sucrose efflux rate in phloem decreased by 40.1% and 30.6%, and the iron efflux rate in phloem was also reduced by 73.7% and 51.0% in Y2 and Y6, respectively. Thus, the iron content in grains was decreased. The transcriptome analysis on grains of WT and Y2 at 10 DAF was used to compare the difference in carbohydrate and iron metabolism. Seven upregulated DEGs and twenty-four downregulated DEGs related to carbohydrate metabolism were identified in Y2. The expression levels of starch synthesis and sugar transport genes in Y2 were lower than those in WT. The expression levels of iron-related genes, including OsTOM1, OsNAS1, OsNAS2, OsIRT1, OsYSL9, and OsOPT7, were significantly downregulated in Y2. These results indicated that blocking photoassimilates allocation between source and sink reduces iron accumulation in grains. [ABSTRACT FROM AUTHOR]

Monitoring plant diseases is essential for farmers to secure crop quantity and quality. Deep learning has recently been applied to plant disease recognition to help farmers take prompt and proper actions to prevent reductions in crop quantity and quality. Generally, deep learning requires a large‐scale dataset with supervised information annotated often by specialists. However, because collecting plant disease images in natural environments is difficult and obtaining proper annotations from specialists is costly, deep learning is infeasible for plant disease recognition tasks. Few‐shot learning (FSL) is an alternative for plant disease recognition using prior knowledge. Although FSL has attracted considerable attention, comprehensive reports on the application of FSL methods for plant disease recognition are required. Here, we introduce FSL with its applications in plant disease recognition. We begin with an overview of computer vision tasks using machine learning and FSL. We provide practical examples of FSL applications. Utilizing these practical examples, we describe different approaches for data augmentation and FSL methods of embedding, multitask learning, transfer learning, and meta‐learning. Further, we summarize how models are optimized for performance with reference to existing studies. Finally, the advantages and disadvantages are discussed, along with potential challenges for FSL applications in plant disease recognition. Core Ideas: Generally, machine learning requires a large‐scale dataset with supervised information annotated by specialists.Few‐shot learning (FSL) is a new paradigm machine learning that enables machines to learn from small samples.FSL has attracted research attention in plant disease recognition.This review introduces FSL with its applications in plant disease recognition. [ABSTRACT FROM AUTHOR]

Infections with phytoplasma present one of the most significant biotic stresses influencing plant health, growth, and production. The phytoplasma 'Candidatus Phytoplasma solani' infects a variety of plant species. This pathogen impacts the physiological and morphological characteristics of plants causing stunting, yellowing, leaf curling, and other symptoms that can lead to significant economic losses. The aim of this study was to determine biochemical changes in peony (Paeonia tenuifolia L.), mint (Mentha × piperita L.), and dill (Anethum graveolens L.) induced by 'Ca. Phytoplasma solani' in Serbia as well as to predict the impact of the biotic stress using artificial neural network (ANN) modeling. The phylogenetic position of the Serbian 'Ca. Phytoplasma solani' strains originated from the tested hosts using 16S rRNA (peony and carrot strains) and plsC (mint and dill strains) sequences indicated by their genetic homogeneity despite the host of origin. Biochemical parameters significantly differed in asymptomatic and symptomatic plants, except for total anthocyanidins contents in dill and the capacity of peony and mint extracts to neutralize superoxide anions and hydroxyl radicals, respectively. Principal Component Analysis (PCA) showed a correlation between different chemical parameters and revealed a clear separation among the samples. Based on the ANN performance, the optimal number of hidden neurons for the calculation of TS, RG, PAL, LP, NBT, •OH, TP, TT, Tflav, Tpro, Tant, DPPH, and Car was nine (using MLP 8-9-13), as it produced high r2 values (1.000 during the training period) and low SOS values. Developing an effective early warning system for the detection of plant diseases in different plant species is critical for improving crop yield and quality. [ABSTRACT FROM AUTHOR]

Mycotoxins are toxins produced by various types of fungi, including Fusarium, which can produce different types of mycotoxins, such as Deoxynivalenol (DON), Zearalenone, T-2 toxin, and Fumonisins (FUM). Mycotoxins have the potential to reduce the quality of crops and pose health risks to both humans and animals. This can result in reduced animal production and substantial economic consequences on a global scale. Extensive research has been carried out to investigate the high incidence of contamination in grains by Fusarium fungi. In this study, 80 samples of maize from silos of dairy farms in Fars province, Iran were collected and examined for fungal contamination by Fusarium and potential production of DON and FUM. For this purpose, identification using specific primers for different genes was carried out by polymerase chain reaction test and gel electrophoresis with agarose (1%). Among different counties, the silos in Kharameh with 47.05% and Jahrom with 46.15% had the highest contamination rates, and the lowest contamination rate belonged to Kazeroon with 27.27%. Out of the 30 positive samples contaminated by Fusarium, 21 produced FUM, 4 produced DON, and 5 produced both toxins. Fusarium species that contaminated the maize samples were also identified, including 13, 10, and 7 samples contaminated by F. proliferatum, F. verticillioides, and F. graminearum, respectively. As a conclusion, the findings of the study indicated that 37.5% of the corn samples from dairy farm silos in Fars province were contaminated with the Fusarium fungus, which had the potential to produce the toxic mycotoxins, deoxynivalenol, and fumonisins. [ABSTRACT FROM AUTHOR]

Weed management impacts crop yield and quality. Machine vision technology is crucial to the realization of site-specific precision weeding for sustainable crop production. Progress has been made in developing computer vision algorithms, machine learning models, and datasets for weed recognition, but there has been a lack of open-source, publicly available software tools that link imaging hardware and offline trained models for system prototyping and evaluation, hindering community-wise development efforts. Graphical user interfaces (GUIs) are among such tools that can integrate hardware, data, and models to accelerate the deployment and adoption of machine vision-based weeding technology. This study introduces a novel GUI called OpenWeedGUI, designed for the ease of acquiring images and deploying YOLO (You Only Look Once) models for real-time weed detection, bridging the gap between machine vision and artificial intelligence (AI) technologies and users. The GUI was created in the framework of PyQt with the aid of open-source libraries for image collection, transformation, weed detection, and visualization. It consists of various functional modules for flexible user controls and a live display window for visualizing weed imagery and detection. Notably, it supports the deployment of a large suite of 31 different YOLO weed detection models, providing flexibility in model selection. Extensive indoor and field tests demonstrated the competencies of the developed software program. The OpenWeedGUI is expected to be a useful tool for promoting community efforts to advance precision weeding technology. [ABSTRACT FROM AUTHOR]

Climate change-induced environmental stress significantly affects crop yield and quality. In response to environmental stressors, plants use defence mechanisms and growth suppression, creating a resource trade-off between the stress response and development. Although stress-responsive genes have been widely engineered to enhance crop stress tolerance, there is still limited understanding of the interplay between stress signalling and plant growth, a research topic that can provide promising targets for crop genetic improvement. This review focuses on Cytokinin Response Factors (CRFs) transcription factor's role in the balance between abiotic stress adaptation and sustained growth. CRFs, known for their involvement in cytokinin signalling and abiotic stress responses, emerge as potential targets for delaying senescence and mitigating yield penalties under abiotic stress conditions. Understanding the molecular mechanisms regulated by CRFs paves the way for decoupling stress responses from growth inhibition, thus allowing the development of crops that can adapt to abiotic stress without compromising development. This review highlights the importance of unravelling CRF-mediated pathways to address the growing need for resilient crops in the face of evolving climatic conditions. [ABSTRACT FROM AUTHOR]

The Flavin Monooxygenase (FMO) gene superfamily in plants is involved in various processes most widely documented for its involvement in auxin biosynthesis, specialized metabolite biosynthesis, and plant microbial defense signaling. The roles of FMOs in defense signaling and disease resistance have recently come into focus as they may present opportunities to increase immune responses in plants including leading to systemic acquired resistance, but are not well characterized.We present a comprehensive catalogue of FMOs found in genomes across vascular plants and explore, in depth, 170 wheat TaFMO genes for sequence architecture, cis-acting regulatory elements, and changes due to Transposable Element insertions. A molecular phylogeny separates TaFMOs into three clades (A, B, and C) for which we further report gene duplication patterns, and differential rates of homoeologue expansion and retention among TaFMO subclades.We discuss Clade B TaFMOs where gene expansion is similarly seen in other cereal genomes. Transcriptome data from various studies point towards involvement of subclade B2 TaFMOs in disease responses against both biotrophic and necrotrophic pathogens, substantiated by promoter element analysis. We hypothesize that certain TaFMOs are responsive to both abiotic and biotic stresses, providing potential targets for enhancing disease resistance, plant yield and other important agronomic traits. Altogether, FMOs in wheat and other crop plants present an untapped resource to be exploited for improving the quality of crops. [ABSTRACT FROM AUTHOR]

Although biochar application to soils has been found to increase soil quality and crop yield, the biochar dispersion extent and its impacts on native soil organic carbon (SOC) has received relatively little attention. Here, the vertical and lateral migration of fine, intermediate and coarse-sized biochar (<0.5, 0.5–1 and 1–5 mm, respectively), applied at low and high doses (1.5–2 and 3–4% w/w, respectively), was tracked using stable isotope methods, along with its impact on native SOC stocks. Biochar was homogeneously mixed into the surface layer (0–7 cm depth) of a loamy sandy Acrisol in Zambia. After 4.5 y, 38–75% of the biochar carbon (BC) was lost from the applied layer and 4–25% was detected in lower soil layers (7–30 cm). Estimating BC mineralization to be no more than 8%, 25–60% was likely transported laterally out of the experimental plots. This conclusion was supported by observations of BC in the control plot and in soils up to 2 m outside of the experimental plots. These processes were likely progressive as recovery of BC in similar plots 1 year after application was greater in both surface and lower soil layers than after 4.5 y. Fine and intermediate-sized BC displayed the greatest downward migration (25.3 and 17.9%, respectively), particularly when applied at lower doses, suggesting its movement through soil inter-particle spaces. At higher dosages, fine and intermediate-sized particles may have clogged pore, so coarse biochar displayed the greatest downward migration when biochar was applied at higher doses. In the BC treatment plot soil profiles, native SOC stocks were reduced by 2.8 to 24.5% (18.4% on average), i.e. positive priming. However, some evidence suggested that the soils may switch to negative priming over time. The dispersion of biochar in soil should be considered when evaluating biochar's agronomic benefits and environmental effects. [ABSTRACT FROM AUTHOR]

Introduction: The severity of flood disasters is increasing due to climate change, resulting in a significant reduction in the yield and quality of forage crops worldwide. This poses a serious threat to the development of agriculture and livestock. Hemarthria compressa is an important high-quality forage grass in southern China. In recent years, frequent flooding has caused varying degrees of impacts on H. compressa and their ecological environment. Methods: In this study, we evaluated differences in flooding tolerance between the root systems of the experimental materials GY (Guang Yi, flood-tolerant) and N1291 (N201801291, flood-sensitive). We measured their morphological indexes after 7 d, 14 d, and 21 d of submergence stress and sequenced their transcriptomes at 8 h and 24 h, with 0 h as the control. Results: During submergence stress, the number of adventitious roots and root length of both GY and N1291 tended to increase, but the overall growth of GY was significantly higher than that of N1291. RNA-seq analysis revealed that 6046 and 7493 DEGs were identified in GY-8h and GY-24h, respectively, and 9198 and 4236 DEGs in N1291-8h and N1291-24h, respectively, compared with the control. The GO and KEGG enrichment analysis results indicated the GO terms mainly enriched among the DEGs were oxidation-reduction process, obsolete peroxidase reaction, and other antioxidant-related terms. The KEGG pathways that were most significantly enriched were phenylpropanoid biosynthesis, plant hormone signal transduction etc. The genes of transcription factor families, such as C2H2, bHLH and bZIP, were highly expressed in the H. compressa after submergence, which might be closely related to the submergence adaptive response mechanisms of H. compressa. [ABSTRACT FROM AUTHOR]

Rice is a staple food for more than half of the global population due to its food security and sustainable development. Weeds compete with crops for sunlight and indispensable nutrients, affecting the yield and quality of crops. Breeding herbicide-tolerant rice varieties paired with herbicide application is expected to help with weed control. In this study, 194 Japonica/Geng rice varieties or lines collected from the Huanghuaihai region of China were screened by Kompetitive Allele-Specific PCR (KASP) markers based on four mutation sites within OsALS1 (LOC_Os02g30630), which is the target of imidazolinone (IMI) herbicides. Only the OsALS1627N haplotype was identified in 18 varieties, including the previously reported Jingeng818 (JG818), and its herbicide resistance was validated by treatment with three IMIs. To investigate the origin of the OsALS1627N haplotype in the identified varieties, six codominant PCR-based markers tightly linked with OsALS1 were developed. PCR analysis revealed that the other 17 IMI-tolerant varieties were derived from JG818. We randomly selected three IMI-tolerant varieties for comparative whole-genome resequencing with known receptor parent varieties. Sequence alignment revealed that more loci from JG818 have been introduced into IMI-tolerant varieties. However, all three IMI-tolerant varieties carried clustered third type single nucleotide polymorphism (SNP) sites from unknown parents, indicating that these varieties were not directly derived from JG818, whereas those from different intermediate improved lines were crossed with JG818. Overall, we found that only OsALS1627N from JG818 has been broadly introduced into the Huanghuaihai region of China. Additionally, the 17 identified IMI-tolerant varieties provide alternative opportunities for improving such varieties along with other good traits. [ABSTRACT FROM AUTHOR]

Leaves are the main site of photosynthesis in plants, and leaf color plays a major role in crop quality, yield, resistance, as well as other aspects. Although the genes related to photosynthesis have been well characterized in plants in general, yellow-green leaf mutants have not yet been fully studied in tomatoes. In the present study, a dark green leaf (GL) mutant was isolated from yellow-leaf tomato (wild-type). The dark GL displays a distinct yellow-green phenotype, and has a greater chlorophyll content and higher photosynthetic rate. Furthermore, the lamellae were clear, and the stroma and grana were orderly, with more stacking and larger starch grains according to the ultrastructure analysis of chloroplasts in GL leaves. Comparative transcriptome analysis of GL and wild-type plants was performed to identify the pathways and genes related to photosynthesis. In this work, a total of 292 differentially expressed genes (DEGs) between GL plants and WT plants were identified, of which 131 genes were upregulated and 161 genes were downregulated. The diterpenoid biosynthesis and photosynthesis antenna proteins were the two most significantly enriched in the first 20 pathways according to KEGG analysis. Most of the DEGs involved in diterpenoid biosynthesis and photosynthesis were antenna proteins. The photosynthesis antenna protein Solyc02g071030 (LHCB1) and the diterpenoid biosynthesis-related genes, Solyc08g005710 and Solyc09g059240, were significantly upregulated in GL leaves compared with WT leaves. The expression patterns of the DEGs were similar to those determined by qRT-PCR. Overall, our research not only revealed the diterpenoid biosynthesis and photosynthesis pathways involving in leaf color variation, but also identified the putative target genes for genetic manipulation in the future. [ABSTRACT FROM AUTHOR]

One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve more accurate crop yield forecasts. Therefore, this study used the data of wheat growth environment, crop management, and historical yield in experimental fields in Anding District, Dingxi City, Gansu Province from 1984 to 2021 to construct eight machine learning models and ensemble models. Furthermore, Agricultural Production Systems sIMulator (APSIM), machine learning (ML), and APSIM combined with machine learning (APSIM-ML) were employed to predict wheat yields in 2012, 2016, and 2021. The results show that the APSIM-ML weighted ensemble prediction model, optimized to minimize the MSE, performed the best. Compared to the optimized ML and APSIM models, the average improvements in the RMSE, RRMSE, and MBE for the test years were 43.54 kg/ha, 3.55%, and 15.54 kg/ha, and 93.96 kg/ha, 7.55%, and 104.21 kg/ha, respectively. At the same time, we found that the dynamic flow of water and nitrogen between the soil and crops had the greatest impact on wheat yield prediction. This study improved the accuracy of dryland wheat yield prediction in Gansu Province and provides technical support for the intelligent production of dryland wheat in the loess hilly area. [ABSTRACT FROM AUTHOR]

Alternative fertilizers are essential to minimizing the deteriorating effects of chemical fertilizers on soil and water quality/health. Accordingly, the present work investigated the effects of combined organic–inorganic fertilization (COIF) on wheat and rice yields, soil nutrients, and soil Cd accumulation. Hence, seven different treatments were set up: control (CK); conventional fertilization (CF); adequate fertilization (OF); organic fertilizer replacing 25% (T1) and 50% (T2) of OF; and organic nitrogen (N) replacing 25% (M1) and 50% (M2) of OF-N. Overall, significant increases occurred in the yields of COIF crops. Compared with the CF, the highest wheat and rice yields happened in the M1 treatment (with a difference of approximately 18.5%) (p < 0.05). COIF slightly alleviated soil acidification, and improved the cation exchange capacity (CEC) of the study soils. Furthermore, COIF treatments significantly increased the contents of total phosphorus, total potassium, available phosphorus, and available potassium by 6.35 to 16.9%, 3.17 to 10.9%, 5.53 to 28.7%, and 2.6 to 12%, respectively (p < 0.05). Nevertheless, negligible increases took place in the Cd content of COIF soils compared with that of the CK. Altogether, our results concluded that 25% replacement of OF-N by organic N (M1) effectively improved the fertility/ecological sustainability of the study soils. [ABSTRACT FROM AUTHOR]

Crop diseases have a significant impact on crop yield and quality, so there is an urgent need for a fast and accurate detection method to identify the types of diseases and treat them in a timely manner. In this study, we propose an improved method for crop disease detection using the grape, corn, and tomato disease datasets from PlantVillage. By introducing the depthwise separable group convolution (DSGC) technique and the adaptive feature fusion mechanism (AFFM), this method combines with the convolutional neural network (CNN) model to reduce model computational resource consumption while enhancing the model's ability to learn feature information at different scales. Experimental results show that the accuracy, precision, recall, and F1-score of crop disease classification using the Resnet50 model + AFFM are 99.56%, 99.53%, 99.56%, and 99.57%, respectively. This confirms the effectiveness of the proposed method in successfully distinguishing different crop diseases. Therefore, the method proposed in this study provides a new and efficient solution for crop disease detection and has broad application prospects. [ABSTRACT FROM AUTHOR]

Egypt suffers from limited water resources, which threatens food security and reduces the chances of horizontal expansion by reclaiming new desert lands. Therefore, it was necessary to achieve this target for the productivity and quality of crops under harsh conditions. Field experiments proceeded at the Nubaria research station under sandy soil conditions to evaluate the effects of different silicon sources (silica gel, algae rich in silicon, and potassium silicate) on sugar beet yield and quality under different irrigation regimes (100%, 75%, and 50%) of water requirement (WR) during the growing seasons of 2020 and 2021. Results showed that potassium silicate was most effective for increasing chlorophyll content and growth parameters compared with other sources under water stress conditions. Also, improved nutrient contents in the root and shoot of sugar beet gave the highest values on N (0.58%, 2.54%), P (0.132%, 0.318%), K (0.42%, 1.05%), Fe (67.18, 83.28 ppm), and Zn (11.29, 12.73 ppm) content, respectively, when applied with K2SiO3 compared with deficit irrigation conditions. Stimulating rich-Si remains the most effective for enhancing the growth, quality, and yield of sugar beet grown under deficit irrigation regimes, which makes plants more resistant to weather conditions and water stress. [ABSTRACT FROM AUTHOR]

Maize breeding appears to be a key strategy to ensure global food security. Improving the grain yield and nutritional quality of maize can progress through breeding programs, where hybridization between two genetically contrasting inbreds might lead to producing superior hybrids. This phenomenon occurs as the developed hybrids are 100% heterozygous, and in consequence, expressing heterosis. However, to select parents for the ideal combinations, it is fundamental to understand the genetic status and the ability to combine the different inbreds. This review aimed to highlight the effectiveness of the general combining ability (GCA) and the specific combining ability (SCA) approaches to develop high-yielding and nutritionally enriched maize hybrids adapted to Malaysia's conditions. Maize breeders have applied various breeding methods, including the biofortification technique to augment the grain yield and nutritional quality of the crop. This technique is the most sustainable, feasible, and affordable one, as it offers more nutritious plants with the required micronutrients. Although a considerable amount of research has succeeded in identifying potential inbred combinations for specific traits and sites, the application of combining ability methods toward developing high-yielding and nutritionally enriched maize hybrids adapted to Malaysia's conditions has not been maximized. Therefore, it is important to understand the combining ability approaches to develop maize hybrids that could lead to the maximum output for combating the increasing maize global demand. [ABSTRACT FROM AUTHOR]

CRISPR/Cas9-based targeted gene editing has emerged as a versatile tool for deciphering gene function and improving traits in plants. However, this technique has not been applied to Zoysia japonica, a prominent warm-season turfgrass widely used for green spaces. Leaf senescence, a vital process affecting crop quality, occurs in Z. japonica during late growth, diminishing its aesthetic value and performance. In this study, we adeptly employed CRISPR/Cas9-mediated gene editing to create Z. japonica exhibiting delayed leaf senescence by targeting the ZjEIN2 gene, a crucial regulator of ethylene-mediated senescence. Precise gene editing, which generated knockout mutations in ZjEIN2, led to delayed leaf senescence in both dark and ethylene treatment conditions. This provided strong evidence for ZjEIN2's role in leaf senescence regulation. These findings highlight the potential of CRISPR/Cas9-mediated gene editing as a biotechnological strategy to enhance anti-senescence traits in Z. japonica and potentially other crops. This study carries significant implications for sustainable agriculture and turfgrass management, offering promising avenues for future applications and research. [ABSTRACT FROM AUTHOR]

Apple (Malus pumila Mill.) is one of the important economic crops in the arid areas of Xinjiang, China. For a long time, there has been a problem of high consumption but low yield in water and fertilizer management, prevent improvements in apple quality and yield. In this study, 5-year-old 'Royal Gala' apple trees in extremely arid areas of Xinjiang were used as experimental materials to carry out field experiments. considering 5 irrigation levels (W1, 30 mm; W2, 425 mm; W3, 550 mm; W4, 675 mm; W5, 800 mm) and 5 fertilization levels (F1, 280 kg·ha-1; F2, 360 kg·ha-1; F3, 440 kg·ha-1; F4, 520 kg·ha-1; F5, 600 kg·ha-1) under magnetoelectric water irrigation conditions. The results demonstrated that magnetoelectric water combined with the application of 675 mm irrigation amount and 520 kg·ha-1 fertilization amount was themost effective combination. These results occurred by increasing net photosynthetic rate of apple leaves, improved the quality of apples, increased apple yield, and promoted the improvement of water and fertilizer use efficiency. Additionally, the quadratic regression model was used to fit the response process of yield, IWUE and PFP to irrigation amount and fertilization amount, and the accuracy was greater than 0.8, indicating good fitting effects. The synergistic effect of water and fertilizer has a positive effect on optimizing apple water and fertilizer management. Principal component analysis showed that the magnetoelectric treatment combined water and fertilizer mainly affected apple yield, water and fertilizer use efficiency and vitamin C content related to quality. This study provides valuable guidance for improving water and fertilizer productivity, crop yield and quality in extreme arid areas of Xinjiang by using Magnetoelectric water irrigation. [ABSTRACT FROM AUTHOR]

This study investigates the impact of sweet potato plant sanitation on the yield and external and internal quality root storage exploring the nutritional content affected by various cooking methods (raw, boiled, and oven-cooked). The presence of viruses, and concretely of the sweet potato leaf curl virus (SPLCV), in sweet potato propagation material is shown to significantly reduce yield and modify storage root quality. Notably, the research reveals a substantial improvement in crop yield and external quality, reinforcing the efficacy of plant sanitation methods, specifically apical meristem culture, in preserving the overall productivity of sweet potato crops. Furthermore, the investigation identifies a noteworthy decrease in starch content, suggesting a dynamic interaction between plant sanitation and starch metabolism in response to viral diseases. The study also delves into the alteration of mineral absorption patterns, shedding light on how plant sanitation influences the uptake of essential minerals in sweet potato storage roots. While the health status of the plants only slightly affected magnesium (Mg) and manganese (Mn) accumulation, indicating a potential resilience of mineral balance under virus-infected conditions. Moreover, the research identifies significant modifications in antioxidant levels, emphasizing the role of plant sanitation in enhancing the nutritional quality of sweet potatoes. Heat-treated storage roots, subjected to various cooking methods such as boiling and oven-cooking, exhibit notable differences in internal quality parameters. These differences include increased concentrations of total soluble solids (SS) and heightened levels of antioxidant compounds, particularly phenolic and flavonoid compounds. The observed increase in antioxidant capacity underscores the potential health-promoting benefits associated with plant sanitation practices. Overall, the study underscores the critical importance of plant sanitation in enhancing sweet potato production sustainability, contributing to food security, and supporting local agricultural economies. The results emphasize the need for further research to optimize plant sanitation methods and promote their widespread adoption globally, providing valuable insights into the complex relationships in food quality. [ABSTRACT FROM AUTHOR]

Nutrient management plays a crucial role in the yield and quality of sweet corn. A field experiment was conducted in consecutive two kharif seasons in 2018 and 2019 to investigate the effect of various organic sources of nutrients in combination with inorganic sources on the yield and quality of sweet corn under new alluvial soils of West Bengal, India. Treatments were: T1: Control (without fertilizers); T2: 100% recommended dose (RDF) of chemical fertilizers (CF) (RDF CF100%); T3: 100% recommended dose of N (RDN) through vermicompost (VC) (RDN VC100%); T4: 50 RDN through CF + 50% RDN through VC (RDN CF50% + RDN VC50%); T5: 50% RDF through CF + 50% RDN through organic source (OS)1, Soligro (Ascophyllum nodosum) granular (RDN CF50% + RDN OS150%); T6: 50% RDN through CF + 50% RDN through OS 2, Bioenzyme (liquid) (RDN CF50% + RDN OS250%); T7: 50% RDN through CF + 50% RDN through OS 3, Opteine (Ascophyllum nodosum) filtrate [RDN CF50% + RDN OS350%]; T8: 50% RDN through VC + 50% RDF through OS 1, Soligro (Ascophyllum nodosum) granular (RDN VC50% + RDN OS150%). The OS of fertilizers were VC, SoliGro Gr (OS1) (Ascophyllum nodosum), Bioenzyme liquid (OS2), and Opteine (Ascophyllum nodosum) filtrate (OS3). The inorganic source was traditional CF applied at the RDF (150:75:75 kg ha-1 of N: P2O5:K2O). The VC was used to supply 100% RDN as one source or 50% RDN when combined with CF or OS. Maximum fruit yield (10.75 and 10.79 t ha-1 in 2018 and 2019, respectively) was recorded when RDF was substituted through CF only, being statistically at par with 50% CF + 50% VC on a nitrogen equivalent basis (9.92 and 10.00 t ha-1 in 2018 and 2019, respectively) and 100% VC (8.22 and 8.32 t ha-1 in 2018 and 2019, respectively). Compared to chemical sources of nutrients, VC-based treatments produced a larger percentage of large-size cob (>25 cm). The 100% VC increased antioxidant (8.35 and 8.45 mg g-1 ), carotenoid (0.59 and 0.61 mg/100 g), and phenol (55.06 and 55.02 mg 100 g-1 ) content compared with its 50% dose in combination with other sources. The study revealed the potentiality of organic sources towards achieving improved cob quality of sweet corn. [ABSTRACT FROM AUTHOR]

Rice is the major food crop in India. It is affected by many fungal, bacterial and viral diseases. Among them, brown leaf spot caused by Bipolaris oryzae is one of the important disease which reduces the yield (6-90%) and quality of the crop. The present investigation was carried out to study the cultural and morphological characteristics of Rice brown spot in Cauvery command region of Karnataka. Roving survey was conducted in Hassan, Mandya, Mysuru and Chamarajanagar districts of Cauvery command region to record the disease severity of brown leaf spot of rice during kharif 2022 and disease severity was expressed in Percent Disease Index (PDI). The symptoms are seen on coleoptile, leaves, panicle branches, glumes and spikelet and in the field it is recognized by the greyish brown spots. Among the four districts surveyed, the mean PDI was highest in Mysore (12.11 %) and least was recorded in Chamarajanagar district (7.21 %). Among the different media's tested, paddy leaf extract agar showed maximum radial growth (80.40 mm) in all the isolates followed by potato dextrose agar (78.80 mm). Different isolates showed different colony characters, colony diameter, colony abundance, colony colour, margin, texture, topography and time taken to cover entire petri plate. Conidia in different isolates were light brown, brown and dark brown with size ranging 16.39 - 103.06 × 6.45 - 19.60 µm. The shape of the conidia was either curved, slightly curved, spindle or fusoid and number of septa was between 3-10. [ABSTRACT FROM AUTHOR]

Soil tillage is widely acknowledged to affect soil characteristics and agricultural productivity. This research investigates the short‐term effects of various tillage methods on soil physical properties and crop yields at a Central German field site with a dry climate (mean temperature 9.5°C; annual precipitation 470 mm). Three tillage approaches were evaluated: conventional plough tillage (25 cm depth), cultivator tillage (18 cm depth), and double‐layer plough tillage (15 and 30 cm depth). We assessed soil physical properties through standard laboratory analyses, compression tests, soil pore structure via X‐ray computed tomography (X‐ray CT) and crop yields over 3 years. The results indicate that cultivator tillage approach increased soil bulk density relative to conventional tillage, especially in the second year, though this effect diminished over time. Double‐layer plough tillage emerged as a viable short‐term alternative to conventional tillage, achieving comparable soil bulk density. Saturated hydraulic conductivity values were generally higher for soils under conventional tillage or double‐layer plough tillage than for cultivator tillage, highlighting their soil loosening effect. Classical soil analysis methods combined with X‐ray computed tomography provided valuable insights into tillage induced changes to soil structure. Cultivator tillage resulted in a distinct pore structure with reduced macroporosity and pore connectivity. Despite notable soil property variations, crop yields remained consistent across the tillage methods. Overall, double‐layer plough tillage presents a sustainable option, moderately improving soil physical properties while maintaining crop yields. This study highlights the need to assess the short‐term effects of tillage on soils and contributes to the broader dialogue on optimizing tillage strategies for effective soil management and crop production. [ABSTRACT FROM AUTHOR]

This document is a special issue of the journal Horticulturae titled "Preharvest and Postharvest Factors Improving Horticultural Crops Quality and Shelf-Life." The issue focuses on the factors that affect the quality, disease, ripening, senescence, and shelf life of horticultural crops. It includes thirteen articles that examine field management, preharvest treatments, and postharvest treatments to improve the quality and shelf life of fresh horticultural products. The articles provide valuable insights into the intrinsic and extrinsic factors that impact the postharvest quality of horticultural crops and aim to promote communication and knowledge exchange in the field of horticultural postharvest studies. [Extracted from the article]

Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers have no proper knowledge to select which crop is suitable to grow according to the environmental factors and soil characteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sector of the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning, and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC), and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggesting a suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, firstmodule uses static data and the second module takes hybrid data collection (IoT-based real-time data and manual data) with machine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the yield. Python is used to train themodel that predicts the crop. This systemproposed an intelligent and low-cost solution for the farmers to process the data and predict the suitable crop. We implemented the proposed system in the field. The efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop. [ABSTRACT FROM AUTHOR]

Brassica crops are well known for the accumulation of glucosinolates—secondary metabolites crucial for plants' adaptation to various stresses. Glucosinolates also functioning as defence compounds pose challenges to food quality due to their goitrogenic properties. Their disruption leaves plants susceptible to insect pests and diseases. Hence, a targeted reduction in seed glucosinolate content is of paramount importance to increase food acceptance. GLUCOSINOLATE TRANSPORTERS (GTRs) present a promising avenue for selectively reducing glucosinolate concentrations in seeds while preserving biosynthesis elsewhere. In this study, 54 putative GTR protein sequences found in Brassica were retrieved, employing Arabidopsis GTR1 and GTR2 templates. Comprehensive bioinformatics analyses, encompassing gene structure organization, domain analysis, motif assessments, promoter analysis, and cis-regulatory elements, affirmed the existence of transporter domains and stress-related regulatory elements. Phylogenetic analysis revealed patterns of conservation and divergence across species. Glucosinolates have been shown to increase under stress conditions, indicating a potential role in stress response. To elucidate the role of GTRs in glucosinolate transportation under NaCl stress in two distinct Brassica species, B. juncea and B. napus, plants were subjected to 0, 100, or 200 mM NaCl. Based on the literature, key GTR genes were chosen and their expression across various plant parts was assessed. Both species displayed divergent trends in their biochemical profiles as well as glucosinolate contents under elevated salt stress conditions. Statistical modelling identified significant contributors to glucosinolate variations, guiding the development of targeted breeding strategies for low-glucosinolate varieties. Notably, GTR2A2 exhibited pronounced expressions in stems, contributing approximately 52% to glucosinolate content variance, while GTR2B1/C2 displayed significant expression in flowers. Additionally, GTR2A1 and GTR1A2/B1 demonstrated noteworthy expression in roots. This study enhances our understanding of glucosinolate regulation under stress conditions, offering avenues to improve Brassica crop quality and resilience. [ABSTRACT FROM AUTHOR]

Early detection of plant leaf diseases is a major necessity for controlling the spread of infections and enhancing the quality of food crops. Recently, plant disease detection based on deep learning approaches has achieved better performance than current state-of-the-art methods. Hence, this paper utilized a convolutional neural network (CNN) to improve rice leaf disease detection efficiency. We present a modified YOLOv8, which replaces the original Box Loss function by our proposed combination of EIoU loss and α -IoU loss in order to improve the performance of the rice leaf disease detection system. A two-stage approach is proposed to achieve a high accuracy of rice leaf disease identification based on AI (artificial intelligence) algorithms. In the first stage, the images of rice leaf diseases in the field are automatically collected. Afterward, these image data are separated into blast leaf, leaf folder, and brown spot sets, respectively. In the second stage, after training the YOLOv8 model on our proposed image dataset, the trained model is deployed on IoT devices to detect and identify rice leaf diseases. In order to assess the performance of the proposed approach, a comparative study between our proposed method and the methods using YOLOv7 and YOLOv5 is conducted. The experimental results demonstrate that the accuracy of our proposed model in this research has reached up to 89.9% on the dataset of 3175 images with 2608 images for training, 326 images for validation, and 241 images for testing. It demonstrates that our proposed approach achieves a higher accuracy rate than existing approaches. [ABSTRACT FROM AUTHOR]

Background: Root knot nematode, Meloidogyne incognita is one of the main biotic constraints in reducing the quantity and quality of the cowpea crop in most of the growing areas of the world. The nematode produces galls on roots and disrupt the physiology of the plant by reducing crop yield and product quality and are therefore of great economic importance. Methods: Studies were conducted to estimate the yield loss of cowpea in field condition along with evaluation of few genotypes under net house condition against root knot nematode based on gall index, reaction response and number of egg masses/ 5 g of root at Directorate of Research, BCKV, West Bengal. Estimation of cowpea yield loss was conducted with the parameter of mean yield, percentage avoidable and increase in yield, Root Knot Index (RKI in 1-5 scale) and final nematode population reduction. Result: Under treated condition, cowpea yield was significantly increased ranging from 10.93 to 14.58% with 37.19 to 38.17% reduction of nematode population. The range of avoidable yield loss was 9.85 to 12.72%. In response reaction, 28 genotypes were found as moderately resistant. Local cowpea cultivar, Kashikanchan may be avoided at nematode infection area due to its high susceptibility and the moderately resistant genotypes may be suggested for the use in future breeding studies as a parental material to develop the root knot nematode resistant cultivars. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the genetic diversity (GD) and association analysis for 100-kernel weight (100KW) and understand the population structure and genetic distance among Korean waxy maize inbred lines collected in South Korea. The average value of 100KW was 19.8 ± 4.7 g, with statistically significant differences between low and high groups based on the average value. GD analysis using 150 simple sequence repeat (SSR) loci showed an average of 3.94 alleles and 4.32 genotypes per locus. The average GD was 0.581, and the average polymorphic information content (PIC) was 0.522. Pairwise genetic similarity coefficients ranged from 0.229 to 0.893 with an average of 0.385. A distance-based unweighted pair group method with arithmetic mean (UPGMA) dendrogram showed all the inbred lines dividing into five subgroups at a genetic similarity of 35.1%. Group I consisted of 16 inbred lines, with nine low inbred lines and seven high inbred lines. Group II included 20 inbred lines, composed of 10 low and 10 high 100KW inbred lines. Groups III and V each had two high or low inbred lines, respectively. Group IV had only one high inbred line. The model-based population structure classified K = 2 and K = 4 based on delta K. Association analysis between 100KW and SSR markers identified five marker-trait associations (MTAs) involving four SSR markers. The information from this study may support opportunities for selecting inbred lines with desirable traits and for developing new waxy maize varieties in South Korea. This could enable maize breeders to improve crop yield and quality through marker-assisted selection (MAS). [ABSTRACT FROM AUTHOR]

The rising adoption of agricultural technologies such as the Internet of Things (IoT) or "smart farming" aims to boost crop production in terms of both quantity and quality. This study compares the benefits of a smart farm employing an IoT-based hydroponic system with those of a conventional hydroponic farm, using Chinese cabbage (Brassica pekinensis L.) as the experimental crop. Our primary objective was to automate environmental monitoring, achieving pH level and electrical conductivity (EC) maintenance through smartphone or computer interfaces for nutrient and acid–base solution adjustments. Additionally, we evaluated plant growth and crop quality, finding superior results with the smart hydroponic system. On average, there were substantial increases in various parameters, including total fresh weight (27.14%), total dry weight (48.90%), plant height (11.14%), stem diameter (32.89%), leaf area (94.30%), leaf width (32.36%), leaf length (38.12%), and chlorophyll content (22.73%). Nitrate accumulation in the edible parts of Chinese cabbage remained within safe limits for both systems, reflecting careful nutrient management. These findings highlight the potential of IoT-based technology in enhancing productivity and quality in hydroponic farming, marking a significant step towards revolutionizing traditional agricultural practices for more efficient crop production systems. [ABSTRACT FROM AUTHOR]

Weeds interfere with agricultural production activities worldwide and have a very serious impact on agriculture and animal husbandry. Identifying a safe and reliable weed control strategy may increase the yield and production net income, and improve crop quality. Licorice is one of the most popular traditional Chinese herbal medicines and has been used for over 2000 years in China. Liquiritin and glycyrrhizic acid are crucial active ingredients. A field experiment was carried out to explore the effects of weeding frequency on the yield and quality of Glycyrrhiza uralensis Fisch in an arid and semi-arid area of northwest China. The experiment consisted of seven treatments: (1) no weeding, marked as WF0, and (2)–(7) artificial weeding using a hoe once every 1, 2, 4, 6, 8 and 10 weeks after emergence, marked as WF1, WF2, WF4, WF6, WF8 and WF10, respectively. We found that a higher weeding frequency resulted in greater plant height, photosynthesis, yield and quality. The highest yield was obtained when the WF1 treatment was applied, while the cost of weeding was high among all treatments. The concentrations of liquiritin and glycyrrhizic acid were increased by 53.24% and 36.57%, with the highest nitrogen metabolism enzymatic activities and quality observed when the WF4 treatment was applied. The WF4 treatment resulted in the largest increase in the net income among all treatments in both growing seasons, with respective increases of up to 71.39% and 78.81%. These findings suggest that weeding once every four weeks could be an effective and sustainable measure to control weeds in an arid and semi-arid area. [ABSTRACT FROM AUTHOR]

The impact of changing meteorological conditions on crop quality has become a trending topic in current agriculture research. In this study, we analyzed the combined effects of both meteorological conditions and key stages on the nutritional quality of maize based on the data of field-staged sowing trials from 2018 to 2022. The results are as follows: (1) The key stage of meteorological conditions affecting the content of major nutritional qualities of maize is from 6 d before to 35 d after flowering. (2) The maximum temperature from 6 d before to 8 d after flowering, average temperature from 5 d before to 20 d after flowering, and minimum temperature from 9–20 d after flowering have significant positive effects on protein, fat, and essential amino acids, respectively; the daily difference in temperature from 9 to 35 d and 24 to 35 d after flowering have a significant negative effect on crude fiber and essential amino acids, respectively, and the daily difference in temperature from 24 to 35 d and the minimum temperature from 5 d before to 35 d after flowering have a significant effect on non-essential amino acids. (3) When the maximum temperature during the key stage of nutritional quality is 31.2 °C, the average temperatures are 24.9 °C and 22.4 °C, the minimum temperature is 18.9 °C, and the daily difference in temperature is 15.0 °C, the contents could reach the optimal values of 9.66% (protein), 4.80% (fat), 4.97% (crude fiber), 40.39 g·kg−1 (essential amino acids), and 58.96 g·kg−1 (non-essential amino acids), respectively. The findings provide a basis for adjusting the sowing period to improve the nutritional quality of maize in the context of climate change. [ABSTRACT FROM AUTHOR]

In this study, we evaluated Polimaize lines, named Polimaize, through the integration of alleles from the Native Blue Corn (NBC-JIQ), a local Mexican maize variety indigenous to the northeast region of Michoacán, Mexico, into elite maize lines curated by the International Maize and Wheat Improvement Center (CIMMYT). This crossbreeding aimed to enhance the nutritional profile of maize, particularly in terms of antioxidants and anthocyanins, which are scarce in elite lines. Our results demonstrated a significant increase in these compounds in the Polimaize lines, with variations due to heterosis. Despite these nutritional improvements, some traits showed decreased concentrations compared to parent lines, notably in sucrose and tryptophan, suggesting a potential trade-off. The study also found significant heritability in amino acids and tryptophan, while hexose sugars showed no substantial heritability. The Polimaize variety exhibited high starch content heritability, comparable to elite lines. Field trials confirmed Polimaize's promising yield and agronomic traits, highlighting its potential for enhancing consumer health and contributing to sustainable agriculture through enriched crop nutritional quality. This project underscores the value of integrating local race alleles into elite lines, offering genetic diversity in maize cultivation. [ABSTRACT FROM AUTHOR]

Aims: Elevated atmospheric CO2 (eCO2) and restricted iron (Fe) supply are known to impact plant growth and nutritional quality of food crops. However, studies aimed at understanding how eCO2 will interact with Fe deficiency are scarce. Changes in the nutritional status of the common bean (Phaseolus vulgaris L.) may significantly impact the nutritional status of populations that rely heavily on this crop. Methods: To understand the combined effects of eCO2 and Fe deficiency on mechanisms relevant to plant nutrient uptake and accumulation, common bean plants were grown under Fe sufficiency (Fe+, 20 mM Fe-EDDHA) and Fe deficiency (Fe-, 0 mM Fe-EDDHA) combined with eCO2 (800 ppm) or ambient CO2 (aCO2, 400 ppm) in hydroponics until maturity. Results: Elevated CO2, besides stimulating photosynthesis and stomatal closure, highly affected plant Fe metabolism: stimulated root ferric chelate reductase (FCR) activity by 6-fold and downregulated the expression of root FRO1 and IRT1 expressions by about 4-fold. In leaves, citrate and oxalate increased, but ferritin expression decreased by 9-fold. Such changes may have determined the differences on mineral accumulation patterns particularly the lower levels of Fe in roots (62%), leaves (38%) and seeds (50%). The combination of Fe deficiency and eCO2 doubled the effect of a single factor on FCR up-regulation, balanced the internal pH of Fe deficient plants, and resulted in the lowest Fe accumulation in all plant parts. Conclusions: These results suggest that eCO2 directly affects the Fe uptake mechanism of common bean plants, decreasing plant Fe content. [ABSTRACT FROM AUTHOR]

In order to monitor the temperature of agricultural planting in real time and avoid losses in the yield and quality of crops due to excessive temperature fluctuation, a multinode temperature monitoring method for digital agricultural planting based on a wireless sensor network (WSN) was proposed herein. First, the WSN structure for the digital agricultural temperature monitoring system was designed, and then the overall structure of the digital agricultural planting multinode temperature monitoring system was designed by combining it with the upper computer to collect agricultural planting temperature data. Next, the characteristics of the agricultural planting temperature data were extracted, and the data were transmitted to the upper computer by establishing a temperature transmission route. Then, the efficiency of the temperature anomaly monitoring was optimized based on multiple input multiple output (MIMO) mode. Finally, the real-time collected temperature value was input into a Bayesian classifier to monitor the temperature anomaly, determine the type of temperature anomaly, and send a warning to the administrator, who, based on the type of warning, takes the appropriate measures to adjust the multinode temperatures at the agricultural planting points. The experiments showed that this method had strong data transmission ability, and the survival time of the data transmission nodes was longer, and the energy consumption of the data transmission was less, and the accuracy of the abnormal temperature monitoring was above 96%. The results showed that this method can accurately monitor abnormal temperatures and provide a warning in real time, accurately control the temperatures of the agricultural planting points, and promote the digital development of agriculture. [ABSTRACT FROM AUTHOR]

Land degradation will remain an important global issue for the 21st century because of its adverse impact on agronomic productivity of crop yields, the environment and its effect on food security and the quality of life. However, the on-site impacts of land degradation on productivity are easily screened due to use of additional inputs and adoption of improved technology and have led some to question the negative effects of extreme land degradation. The relative magnitude of economic losses due to productivity decline versus environmental deterioration also has created a debate. Therefore, land is a non-renewable resource, and the productive capacity of the land would be reduced unless proper management options would be taken at a right time. The proper management options of land degradation for sustaining the crop yields are controlling overgrazing, reduced population pressures on natural resources, using energy efficient sources, contour farming, avoiding cultivation of steep slopes for crop production purposes, afforestation and hillside tree plantations and along gullies, increasing soil fertility by adding organic matter, reducing compaction of soil structures and making soil and water conservation structures to reduce soil erosion, sediment loss and run-off. [ABSTRACT FROM AUTHOR]

Achieving high yield and good quality in crops is essential for human food security and health. However, there is usually disharmony between yield and quality. Seed storage protein (SSP) and starch, the predominant components in cereal grains, determine yield and quality, and their coupled synthesis causes a yield–quality trade‐off. Therefore, dissection of the underlying regulatory mechanism facilitates simultaneous improvement of yield and quality. Here, we summarize current findings about the synergistic molecular machinery underpinning SSP and starch synthesis in the leading staple cereal crops, including maize, rice and wheat. We further evaluate the functional conservation and differentiation of key regulators and specify feasible research approaches to identify additional regulators and expand insights. We also present major strategies to leverage resultant information for simultaneous improvement of yield and quality by molecular breeding. Finally, future perspectives on major challenges are proposed. [ABSTRACT FROM AUTHOR]

Plastic pollution is global concern, affecting most aspects of global food production systems. Plasticulture, a practice used in agriculture to improve crop quality and quantity, among other factors, is a significant source of plastic pollution. This review examines the extent of plasticulture in China, the implications of the practice across decades of use and the legislative instruments used to resolve those issues. It briefly assesses the effectiveness of these policies and proposes possible future innovations to promote increases in long-term food and eco-security, where sustainable plasticulture is a key agent for change. While plasticulture has increased agricultural productivity in growth-limiting conditions, plastic pollution in agricultural soils has become acute in China. Consequently, plastic pollution is having deleterious effects on soil health and in turn, crop productivity in China. Plastic pollution in agriculture is a multifaceted issue and so proposed solutions should be informed by this complexity. Current measures do not reflect a holistic approach to solving this socioecological challenge and adopt a top-down approach, with little or no supportive mechanisms. Future recommendations need to consider the particular set of conditions that influence the production, use and end-of-life management of agriplastics, specific to the environmental, economic and social conditions in each location. [ABSTRACT FROM AUTHOR]

Gray mold caused by Botrytis cinerea is a serious disease of grape (Vitis vinifera) during storage. The aim of this study is to evaluate the effect of atmosphere cold plasma (a novel and nonthermal technology) on inactivation of B. cinerea and preservation of chemical, physical, and mechanical characteristics of grape inoculated with B. cinerea. Herein, different time of cold plasma (0, 10, 20, and 40 s) was firstly considered to be the main factors, besides different storage time (1, 2, 3, 4, and 5 weeks) at 4°C. According to the results, plasma treatment exhibited inhibitory effect on gray mold percentage and microbial load of B. cinerea (log CFU g−1) during postharvest storage. So, in the last week, the gray mold percentage and microbial load in the control were 100% and 3.6 log CFU g−1, and in 40‐s plasma were 4.5% and 2.53 log CFU g−1, respectively. Although the minimum infection and microbial load were observed in 40‐s plasma, better postharvest quality preservation was observed in short‐time cold plasma treatment (≤20 s). Forty‐second plasma caused fruit tissue destruction and negatively decreased mechanical indices (Emod: 0.0028, Fmax = 1.78, and W = 3.18) and weight loss (91.9) in comparison with ≤20‐s plasma, in which mechanical indices (Emod =0.0077, Fmax = 3.6, and W = 10.06) and weight loss (1/1) were higher. The long‐time cold plasma treatment (40 s) had also maximum effects on color changes (10) and surface temperature (2.8°C). Although the highest TSS and TA were observed in 40‐s Plasma, but different time of plasma treatments had no effect on pH. Altogether, these results indicate that the short‐time cold plasma treatment can inactivate B. cinerea on grape berries and preserve crop quality properties. [ABSTRACT FROM AUTHOR]

The uniformity of seed distribution and sowing speed directly impact crop quality and productivity. This experiment assessed how the position of the sowing monitoring sensor influences the distribution of cotton seeds using a pneumatic meter at different operating speeds. The experiment employed a completely randomized two-factor factorial design on a static simulation bench. The first factor involved the sensor installation sites (upper, middle, and lower portions of the conductor tube and conveyor belt), while the second factor encompassed simulated speeds of 3.0, 5.0, 7.0, 9.0, and 11.0 km/h. Parameters such as frequency of double, flawed, and acceptable spacing, coefficient of variation, and precision index were measured based on five replications of 250 consecutive spacing. The results indicated that the sensor's placement significantly influences reading accuracy. Optimal results were observed when the sensor was positioned at the final portion of the conductor tube, providing more accurate seed deposition, and facilitating decision-making. [ABSTRACT FROM AUTHOR]

Background: Plant viruses cause economic losses by reducing the quantity and quality of major crops. This issue is a growing concern due to the expansion of global trade and climate change. In addition, the emergence of new pathogen strains increases the difficulty of controlling viral diseases. Effective management strategies are therefore needed. The control strategy for viral diseases relies primarily on non-chemical and cultural practices, as no commercial viricides are currently available. Some compounds have been identified as effective against certain viruses, but their use in the field is limited due to issues such as concentration, toxicity, and efficacy. Therefore, it is imperative to discover novel antiviral agents that address the existing challenges associated with the identified antiviral candidate compounds. Results: In this study, we evaluated iodine-conjugated organic compounds mixed with sialic acid, whey, and blood meal for virus disease management against seven viruses that cause significant yield losses and economic damage to plants. The candidate compounds reduced virus accumulation and symptom development. Treatment with candidate compounds, A4 and A5, reduced viral RNA accumulation to about half that of those in the control group and showed reduced symptoms along with healthier growth. In addition, we performed transcriptome analysis of treatment with two viruses, which suggested that the mechanism of viral RNA replication inhibition might relate to plant defense systems based on phytohormone pathways. Conclusions: This study demonstrated that treatments with naturally derived materials, such as iodine, nitrogen, and sialic acid-conjugated organic substances, may directly or indirectly impact the host plant's resistance to various virus infections. Moreover, our findings suggest that these natural candidate materials could be utilized for managing virus diseases in the field. [ABSTRACT FROM AUTHOR]

Wheat stands as a cornerstone of global food security. To increase its productivity as well as quality, nutrient management is one of the most important factors. To evaluate the potential contribution of micronutrients to enhancing wheat yield, an experiment was conducted to investigate the interactive effect of zinc and copper on yield and quality indicators (protein, sedimentation value) of wheat under manganese-deficient and sufficient soils in potted plants during the rabi season 2020-21. The experiment was laid out in CRD with three replications and treatments comprised of Zn and Cu levels each @ 0, 2.5, 5.0, 7.5, and 10.0 mg kg-1 applied through ZnSO4 & CuSO4. The results revealed a significant increase in both grain and straw yield, as well as the quality of wheat over their respective control with the application of Zn and Cu. The highest wheat grain yield (6.24 g per pot) was achieved in soils with sufficient Mn when treated with Zn at 10.0 mg kg-1 and Cu at 10.0 mg kg-1. It was further observed that the significant increase in protein content was noticed only up to Cu7.5 when compared with Cu2.5 and a further increase in Cu level from Cu7.5 to Cu10.0 did not affect the protein content significantly in Mn-sufficient soil. The treatments with the best economic aspect were found 5.0 mg kg-1 of zinc sulfate x 7.5 mg kg-1 of copper sulfate, in terms of using less zinc and copper fertilizers and having a favorable impact on the attributes. In conclusion, the application of micronutrients like Zn and Cu should be considered an integral part of a holistic nutritional approach to support optimal wheat growth and its quality. This approach enables farmers to achieve the highest potential yield and quality in their wheat crops. [ABSTRACT FROM AUTHOR]

In the present study, a field establishment was initiated in 2018 with eight treatment conditions using biochar application rates of 0, 10, 20, or 30 t/ha and nitrogen application rates of 0 or 150 kg/ha. After two years, the impact of biochar on carbon-nitrogen distributions, soil aggregate stability, and wheat yields was then assessed. The predominant mechanical aggregates after two years were > 5 mm and 2–5 mm granular aggregates, with notable increases in the amounts of these aggregates following the application of biochar with or without nitrogen that coincided with an increase in soil aggregate mechanical stability. Relative to control conditions, aggregate mean weight diameter (MWD) and geometric weight diameter (GMD) values rose by 17.6% and 24.3% for biochar with nitrogen treatment (N: 150 kg/ha; biochar: 20 t/ha), respectively. Biochar application alone and the application of both biochar and nitrogen fertiliser were associated with 6.4–20.2% and 20.7–42.7% increases in spring wheat yields, respectively. Overall, the results of these analyses highlight the value of applying biochar to improve soil quality and boost crop yields proximal to the study site. This study provided the scientific basis for the rational fertilisation and scientific management of biochar combined with nitrogen fertiliser in the irrigation area of Northern Xinjiang, China. [ABSTRACT FROM AUTHOR]

Plant growth regulators (PGRs) play an important role in increasing crop yield, and quality, and enhancing crop stress resistance in agricultural production, especially for important crops. PGRs can affect the transport and distribution of assimilates by changing the content and distribution of endogenous hormones in plants. Numerous empirical research results have proven that PGRs have an important impact on the growth, development, and yield composition of wheat. Taking wheat plants as an example, this study reviews the application of PGRs in wheat production and explores their impact on wheat growth and yield. Furthermore, residues and microbial degradation of PGRs are summarized in detail. Finally, future research directions on PGR application in wheat production are proposed. This summary is of great significance for understanding the role of PGRs in wheat production. [ABSTRACT FROM AUTHOR]

Salt stress is one of the preeminent abiotic stressors capable of strongly impacting crop productivity and quality. Within the array of strategies garnering interest in safeguarding crops against abiotic stresses, the use of plant biostimulants is emerging as a noteworthy avenue. For the above, there is an increasing interest in finding new plant extracts showing biostimulating effects in crops. In the present study, the efficacy of an aqueous extract from an aquatic species, the duckweed (Lemna minor L.), was assessed in olive plants (cv. Arbequina) grown in hydroponics and exposed to severe saline stress (150 mM NaCl). Salt stress caused considerable diminutions in biomass production, leaf net photosynthesis (Pn), leaf transpiration rate (E), and stomatal conductance (gs). The application of the duckweed extract resulted in a notable plant functionality recovery and counteracted the detrimental effects of the NaCl stress. Indeed, the plants stressed with NaCl and treated with the extract showed enhanced physiological and biometric traits compared to samples treated with NaCl alone. In particular, the duckweed extract improved photosynthetic activity and stomatal conductance, reduced the intercellular CO2 concentration, and ameliorated other physiological and morphological parameters. All these benefits influenced the whole plant growth, allowing samples treated with the extract to maintain a similar performance to that exhibited by the Control plants. [ABSTRACT FROM AUTHOR]

Plant probiotic bacteria are being increasingly used to maximize both the productivity and quality of field crops. Pseudomonas chlororaphis O6 (PcO6) is a plant root colonizer with probiotic activities. This bacterium produces an array of metabolites, including a group of phenazines that are functional in plant protection. The paper reports responses of PcO6 to a nonionic triblock copolymer surfactant, Pluronic F68. This Pluronic exhibits membrane "healing" activity and improves cryopreservation recovery in eukaryotic cells. The product is FDA-approved and is applied as an adjuvant in formulations used in agriculture, medicine, and biotechnology. Growth of PcO6 on lysogeny broth at 25 °C was unhindered by 0.1 and 1.0 g/L F68, reduced at 10 g/L, and with significant inhibition at 100 g/L F68; micelle formation could account for inhibited growth at higher doses. Phenazine production was not changed by F68, whereas the surfactant activity of F68 induced the spread of bacterial colonization on 0.5% agar. Exposure of cells to fluorescein-labeled F68 resulted in intense fluorescence, stable to washing, showing a direct association of the Pluronic with the bacterium. However, neither protection nor harm was found for PcO6 cells suspended in either 0.1% or 1% F68 after three freeze (−20 °C)/thaw cycles. These findings suggest that F68 could be compatible for use in agricultural formulations with little effect on probiotics such as PcO6. [ABSTRACT FROM AUTHOR]

The degradation of chernozems and increased soil erosion led to the search for more advanced methods of tillage, taking into account climatic conditions, the quantity and quality of crop residues, and the volume of fertilizer application. The aim of the study was to establish the effect of various methods of basic tillage in the presence of preceding plant's crop residues on the growth and development of spring barley plants. The experiment was carried out in the forest-steppe of Ukraine. During the experiment, the influence of various methods of basic tillage on the agrophysical properties of the soil, its water regime, and weed infestation of spring barley crops was studied. For comparison, the following types of basic tillage were used: dump to a depth of 20–22 cm, chisel tillage to a depth of 14–16 cm, and disc tillage to a depth of 10–12 cm. Dump and chisel processing were characterized by higher grain yield. Chisel tillage provided better moisture accumulation compared to reverse ploughing. In spring, at the time of sowing grain crops in the layer of 0–15 cm, the reserves of productive moisture during chiselling were 145 mm, and during mouldboard processing 122.6 mm. Thus, chisel tillage for spring barley creates the best conditions for moisture supply and guarantees a high level of grain yield and significant profitability of production. [ABSTRACT FROM AUTHOR]

Leaf senescence is a crucial trait that has a significant impact on crop quality and yield. Previous studies have demonstrated that light is a key factor in modulating the senescence process. However, the precise mechanism by which plants sense light and control senescence remains largely unknown, particularly in crop species. In this study, we reveal that the reduction in blue light under shading conditions can efficiently induce leaf senescence in soybean. The blue light receptors GmCRY1s rather than GmCRY2s, primarily regulate leaf senescence in response to blue light signals. Our results show that GmCRY1s interact with DELLA proteins under light-activated conditions, stabilizing them and consequently suppressing the transcription of GmWRKY100 to delay senescence. Conversely, LBL reduces the interaction between GmCRY1s and the DELLA proteins, leading to their degradation and premature senescence of leaves. Our findings suggest a GmCRY1s-GmDELLAs-GmWRKY100 regulatory cascade that is involved in mediating LBL-induced leaf senescence in soybean, providing insight into the mechanism of how light signals regulate leaf senescence. Additionally, we generate GmWRKY100 knockout soybeans that show delayed leaf senescence and improved yield under natural field conditions, indicating potential applications in enhancing soybean production by manipulating the leaf senescence trait. This study provides insights into how shade induces leaf senescence in soybean. The reduction of blue light intensity deactivates GmCRY1s, leading to the degradation of GmRGAs and the upregulation of WRKY100, ultimately promoting leaf senescence. [ABSTRACT FROM AUTHOR]