Search Results (2,300)

Fumonisins, primarily produced by Fusarium spp. and Aspergillus section nigri, are common contaminants in maize, cereal grains, and other processed and derived products, representing a significant risk to food safety and public health. This study presents the development and optimisation of a high-performance liquid chromatography method with fluorescence detection (HPLC-FLD) for the quantification of fumonisin B1 (FB1) and B2 (FB2) in various food matrices. In contrast with conventional protocols employing potassium phosphate buffers as the mobile phase, the proposed method utilises formic acid, offering enhanced compatibility with liquid chromatography systems. An automated online precolumn derivatisation with o-phthaldialdehyde (OPA) was optimised through experimental design and response surface methodology, enabling baseline separation of FB1 and FB2 derivatives in less than 20 min. The method demonstrated high sensitivity, with limits of detection of 0.006 µg mL⁻¹ for FB1 and 0.012 µg mL⁻¹ for FB2, and excellent repeatability (intraday RSD values of 0.85% and 0.83%, respectively). Several solid-phase extraction (SPE) strategies were evaluated to enhance sample clean-up using a variety of food samples, including dried figs, raisins, dates, corn, cornmeal, wheat flour, and rice. FumoniStar Inmunoaffinity columns were the only clean-up method that provided optimal recoveries (70–120%) across all tested food matrices. However, the MultiSep™ 211 column yielded good recoveries for both fumonisins in dried figs and raisins. Additionally, the C18 cartridge achieved acceptable recoveries for both fumonisins in dried figs and wheat flour. Full article

Achieving food security for a growing population under a changing climate is a key concern in Senegal, where agriculture employs 77% of the workforce with a majority of small farmers who rely on the production of crops for their subsistence and for income generation. Moreover, due to the underproductive soils and variable rainfall, Senegal depends on imports to fulfil 70% of its food requirements. In this research, we considered four crops that are crucial for Senegalese agriculture: millet, sorghum, peanuts and rice. We used crop simulation models to explore existing yield gaps and optimal agronomic practices. Improving the N fertilizer management in sorghum and millet resulted in 40–100% increases in grain yields. Improved N symbiotic fixation in peanuts resulted in yield increases of 20–100% with highest impact in wetter locations. Optimizing irrigation management and N fertilizer use resulted in 20–40% gains. The best N fertilizer strategy for sorghum and millet included applying low rates at sowing and in early development stages and adjusting a third application, considering the expected rainfall. Peanut yields of the variety 73-33 were higher than Fleur-11 in all locations, and irrigation showed no clear economic advantage. The best N fertilizer management for rainfed rice included applying 30 kg N/ha at sowing, 25 days after sowing (DAS) and 45 DAS. The best combination of sowing dates for a possible double rice crop depended on irrigation costs, with a first crop planted in January or March and a second crop planted in July. Our work confirmed results obtained in field research experiments and identified management practices for increasing productivity and reducing yield variability. Those crop management practices can be implemented in pilot experiments to further validate the results and to disseminate best management practices for farmers in Senegal. Full article

Food security is crucial for social stability and economic development. Ensuring food security in the arid region of Northwest China presents unique challenges due to limited water and soil resources. This study addresses these challenges by integrating a comprehensive water and soil resource matching assessment with grain production forecasting. Based on data from 2000 to 2020, this research projects the food security status to 2035 using the GM(1,1) model, incorporating a comprehensive index of soil and water resource matching and regression analysis to inform production forecasts. Key assumptions include continued historical trends in population growth, urbanization, and dietary shifts towards an increased animal protein consumption. The findings revealed a consistent upward trend in grain production from 2000 to 2020, with an average annual growth rate of 3.5%. Corn and wheat emerged as the dominant grain crops. Certain provinces demonstrated comparative advantages for specific crops like rice and wheat. The most significant finding is that despite the projected growth in the total grain output by 2035 compared to 2020, the regional grain self-sufficiency rate is projected to range from 79.6% to 84.1%, falling below critical food security benchmarks set by the FAO and China. This projected shortfall carries significant implications, underscoring a serious challenge to regional food security and highlighting the region’s increasing vulnerability to external food supply fluctuations. The findings strongly signal that current trends are insufficient and necessitate urgent and proactive policy interventions. To address this, practical policy recommendations include promoting water-saving technologies, enhancing regional cooperation, and strategically utilizing the international grain trade to ensure regional food security. Full article

The improvement in yield in cultivar mixtures has been well established. Despite increasing knowledge of the improvement involving within-species diversification and resource use efficiency, little is known about the benefits arising from relatedness-mediated intraspecific interactions in cultivar mixtures. This study used a relatedness gradient of rice cultivars to test whether neighbor relatedness contributes to improvements in grain yields in cultivar mixtures. We experimentally demonstrated the grain yield of rice cultivar mixtures with varying genetic relatedness under both field and controlled conditions. As a result, a closely related cultivar mixture had increased grain yield compared to monoculture and distantly related mixtures by optimizing the root-to-shoot ratio and accelerating flowering. The benefits over monoculture were most pronounced when compared to the significant yield reductions observed in distantly related mixtures. The relatedness-mediated improvement in yields depended on soil volume and nitrogen use level, with effects attenuating under larger soil volumes or nitrogen deficiency. Furthermore, neighbor relatedness enhanced the richness and diversity of both bacterial and fungal communities in the rhizosphere soil, leading to a significant restructuring of the microbial community composition. These findings suggest that neighbor relatedness may improve the grain yield of rice cultivar mixtures. Beneficial plant–plant interactions may be generated by manipulating cultivar kinship within a crop species. A thorough understanding of kinship strategies in cultivar mixtures offers promising prospects for increasing crop production. Full article

Soil salinization and selenium (Se) deficiency threaten global food security. This study developed a composite bioinoculant combining ACC deaminase-producing Serratia liquefaciens and biogenically synthesized nano-selenium (SeNPs) to alleviate saline–alkali stress and enhance Se nutrition in rice (Oryza sativa L.). A strain of S. liquefaciens with high ACC deaminase activity was isolated and used to biosynthesize SeNPs with stable physicochemical properties. Pot experiments showed that application of the composite inoculant (S3: S. liquefaciens + 40 mmol/L SeNPs) significantly improved seedling biomass (fresh weight +53.8%, dry weight +60.6%), plant height (+31.6%), and root activity under saline–alkali conditions. S3 treatment also enhanced panicle weight, seed-setting rate, and grain Se content (234.13 μg/kg), meeting national Se-enriched rice standards. Moreover, it increased rhizosphere soil N, P, and K availability and improved microbial α-diversity. This is the first comprehensive demonstration that a synergistic bioformulation of ACC deaminase PGPR and biogenic SeNPs effectively mitigates saline–alkali stress, enhances soil fertility, and enables safe Se biofortification in rice. Full article

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

The translocation of cadmium (Cd) in the soil-rice system is complicated; therefore, most of the soil-plant models of Cd have not been extensively studied. Hence, we studied the back-propagation artificial neural network model (BP-ANN) and multiple regression model (MLR) to predict the cadmium (Cd) content in rice grain and soil through testing soil parameters. In this study, 486 pairs of rice grains and corresponding soil samples of 456 vectors were used for training + validation, and 30 vectors were collected from the southwestern karst area of Guangxi Province as a test data set. In this study, the Cd content in rice was successfully predicted by using the factors soil available cadmium (A_Cd), total soil cadmium (T_Cd), soil organic matter (SOM), and pH, which have a more significant impact on rice, as the main prediction variables. Root mean square error (RMSE), Relative Percent Difference (RPD), and correlation coefficient (R²) were used to assess the models. The R², RPD, and RMSE values for R_Cd medium obtained by the MLR model with pH, T_Cd, and A_Cd as entered variables were 0.551, 2.398, and 0.049, respectively. The R² and RMSE values for R_Cd medium obtained by the BP-ANN model with pH, T_Cd, and A_Cd as entered variables were 0.6846, 2.778, and 0.104, respectively. Therefore, it was concluded that BP-ANN was useful in predicting R_Cd and had better performance than MLR. Full article

Alterations in rice qualities during ageing are related to changes in starch molecular structures. However, if and how storage temperature determines starch structure–function relations remain unknown. This study applied four storage temperatures to investigate the effects of ageing on starch structure–function relations. A small but significant variation was observed for starch chain lengths, and this variation depended on both rice varieties and storage temperatures. Rice grains aged at higher temperatures had much higher peak (~25% larger) and setback viscosities (~50% larger) compared to those stored at lower temperatures. The digestion rate constant was lowered (~10%) most significantly at 40 °C. However, the maximum starch digested percentage increased after ageing. All rice varieties showed the lowest hardness at 4 °C and the highest hardness at 40 °C (~20% larger) after ageing. The changes in starch molecular structures were consistent with altered rice properties according to the established structure–property correlations. These results could improve our understanding of the complex rice ageing process. Full article

Cadmium (Cd) contamination in rice (Oryza sativa L.) poses serious health risks for human, necessitating effective mitigation strategies. This study investigated the effects of Cd stress on iron (Fe), manganese (Mn), zinc (Zn), and Cd accumulation and translocation in rice varieties with high (MY46) or low (ZS97B) Cd accumulation capacities grown in acidic and alkaline soils. Results demonstrated that Cd stress significantly inhibited plant growth, reducing plant height, shoot biomass, and grain yield in both soil types. Cd accumulation increased in roots, shoots, and grains, while Fe, Mn, and Zn concentrations decreased markedly. Molecular analysis revealed upregulation of metal transporter genes (OsIRT1, OsNRAMP1, OsNRAMP5) and the vacuolar sequestration gene (OsHMA3) in roots under Cd exposure. The translocation factor (TF) values of Mn and Zn from root to shoot were reduced in acidic soils, whereas Mn and Zn TFs exhibited an increasing trend in alkaline soils despite Cd exposure. Furthermore, correlation analyses indicated Mn and Zn play crucial roles in suppressing Cd accumulation in both acidic and alkaline soils. These findings provide critical insights for developing soil-specific strategies to reduce Cd accumulation in rice through micronutrient management. Full article

Investigating the factors influencing rice grain yield (GY) is critical for optimizing nitrogen (N) management and enhancing resource use efficiency in rice cultivation. However, few studies have comprehensively investigated the factors affecting rice GY, considering an entire influence chain encompassing rice N uptake, growth indicators, and GY components. In this study, field experiment with six different N fertilizer rates (0, 60, 120, 180, 225, and 300 kg N ha⁻¹, i.e., N0, N60, N120, N180, N225, and N300) was conducted in the Jianghan Plain in the Middle Reaches of the Yangtze River, China, to comprehensively elucidate the factors influencing rice GY from aspects of rice N uptake, growth indicators, and GY components and determine the optimal N fertilizer rate. The results showed that rice GY and N uptake initially increased and then either stabilized or declined with higher N fertilizer rate, while apparent N loss escalated with increased N fertilizer rate. The application of N fertilizer significantly promoted the increase in straw N uptake, which was significantly positively correlated with growth indicators (p < 0.05). Among all GY components, panicle number per hill was the most significant positive factor influencing rice GY, and it was significantly positively correlated with all rice growth indicators (p < 0.05). In addition, N180 was the optimal N fertilizer rate, ensuring more than 95% of maximum GY and reducing N loss by 74% and 39% compared to N300, respectively. Meanwhile, the average N balance for N180 remained below 60 kg N ha⁻¹. In conclusion, optimizing the N fertilizer application in paddy fields can effectively maintain stable rice GY and minimize environmental pollution. Full article

GOLDEN2-LIKEs (GLKs) are important transcription factors for the chloroplast development influencing photosynthesis, nutrition, senescence, and stress response in plants. Sunflower (Helianthus annuus) is a highly photosynthetic plant; here, a GLK-homologues gene HaGLK was identified from the sunflower genome by bioinformatics. To analyze the bio-function of HaGLK, transgenic rice plants overexpressing HaGLK (HaGLK-OE) were constructed and characterized via phenotype. Compared to the wild-type control rice variety Zhonghua 11 (ZH11), the HaGLK-OE lines exhibited increased photosynthetic pigment contents, higher net photosynthetic rates, and enlarged chloroplast area; meanwhile, genes involved in both photosynthesis and chlorophyll biosynthesis were also significantly up-regulated. Significantly, the HaGLK-OE plants showed a 12–13% increase in yield per plant. Additionally, the HaGLK-OE plants were demonstrated to have improved salt and drought tolerance compared to the control ZH11. Our results indicated that the HaGLK gene could play multiple roles in photosynthesis and stress response in rice, underscoring its potential value for improving crop productivity and environmental adaptability in breeding. Full article

Ozone pollution decreases rice yield and quality in general, but how ozone stress changes grain-filling capacity is unclear. A chamber experiment was conducted to compare the effects of ozone exposure during the rice growth season on the grain-filling capacity and quality of spikelets located on the upper primary rachis (superior spikelets, SS) and the lower secondary rachis (inferior spikelets, IS). Ozone stress significantly decreased filled grain percentage by 41.4% and grain mass by 10.2% in IS, but had little effect on grain-filling capacity in SS. Consistent with the reduction in grain mass, ozone stress decreased grain volume, mainly due to reduced grain thickness, and IS was reduced more than SS. After removing the hull, brown rice obtained from ozone treatment exhibited higher proportions of immature and abnormal kernels, resulting in a substantially lower proportion of perfect kernels. Under ozone stress, the proportion of perfect kernels was only one-third in IS, compared with two-thirds in SS. Ozone stress affected the pasting properties of brown rice for both SS and IS, as shown by the decreased amylose content, and the increased maximum viscosity, minimum viscosity, final viscosity, setback, and peak time of the rapid visco analyzer profile. Out of fourteen traits related to nutritional quality of brown rice, only five showed significant increases under ozone stress, and they were the concentrations of albumin, prolamin, sulfur, copper, and manganese. The differential ozone responses between SS and IS were rather small for rice pasting properties and chemical compositions as shown by very few significant interactions between ozone and grain position. It is concluded that ozone stress during plant growth imposed more adverse effects on IS than SS in terms of grain-filling capacity and appearance quality, suggesting an enlarged asynchronous grain-filling pattern in rice panicles under ozone pollution. Strategies to improve the grain-filling capacity of IS are needed to mitigate ozone-induced damage to rice production. Full article

Remote sensing tools have been proposed to assist with rice crop monitoring but have been developed and validated on ponded rice. This two-year study was conducted on a commercial rice farm with irrigation automation technology aimed to (i) understand how canopy reflectance differs between high-yielding ponded and aerobic rice, (ii) validate the feasibility of using the squared simplified canopy chlorophyll content index (SCCCI²) for N uptake estimates, and (iii) explore the SCCCI² and similar chlorophyll-sensitive indices for grain quality monitoring. Multispectral images were collected from an unmanned aerial vehicle during both rice-growing seasons. Above-ground biomass and nitrogen (N) uptake were measured at panicle initiation (PI). The performance of single-vegetation-index models in estimating rice N uptake, as previously published, was assessed. Yield and grain quality were determined at harvest. Results showed that canopy reflectance in the visible and near-infrared regions differed between aerobic and ponded rice early in the growing season. Chlorophyll-sensitive indices showed lower values in aerobic rice than in the ponded rice at PI, despite having similar yields at harvest. The SCCCI² model (RMSE = 20.52, Bias = −6.21 Kg N ha⁻¹, and MAPE = 11.95%) outperformed other models assessed. The SCCCI², squared normalized difference red edge index, and chlorophyll green index correlated at PI with the percentage of cracked grain, immature grain, and quality score, suggesting that grain milling quality parameters could be associated with N uptake at PI. This study highlights canopy reflectance differences between high-yielding aerobic (averaging 15 Mg ha⁻¹) and ponded rice at key phenological stages and confirms the validity of a single-vegetation-index model based on the SCCCI² for N uptake estimates in ponded and non-ponded rice crops. Full article

Soil organic nitrogen (SON) positively influences crop productivity, greenhouse gas (GHG) emissions, and sustained nitrogen (N) supply. Herein, we observed the effect of different treatments; no fertilizers (CK), chemical fertilizers (nitrogen, phosphorus, and potassium (NPK)), organic manure, and NPK + OM (NPKOM). This study was performed in a randomized complete block design (RCBD) with three replications. The results indicated that NPKOM treatment significantly decreased the nitrous oxide (N₂O) emissions by 19.97% and 17.47% compared to NPK in both years. This was linked with improved soil nutrient availability, soil organic carbon, soil organic nitrogen (SON) storage (10.06% and 12.38%), SON sequestration (150% and 140%), increased soil particulate (44.11% and 44%), and mineral-associated organic N (26.98% and 26.47%) availability. Furthermore, NPKOM also enhanced nitrate reductase (NR: 130% and 112%), glutamine synthetase (GS: 93% and 88%), sucrose phosphate synthase (SPS: 79% and 98%), SSs (synthetic direction; 57% and 50%), and decreased SSs activity in the decomposition direction (18% and 21%). This, in turn, inhibited the decomposition of sucrase and enhanced starch conversion into carbohydrates, thus leading to an increase in rice yield and a decrease in N₂O emissions. All fertilizations, particularly NPKOM, significantly enhanced grain protein contents by increasing N uptake and its availability. Therefore, NPKOM is an effective practice to enhance rice productivity, and SON sequestration and mitigate the N₂O emissions and subsequent climate change. Full article

Accurate and real-time detection of rice shelling rate (SR) and brown rice breakage rate (BR) is crucial for intelligent hulling sorting but remains challenging because of small grain size, dense adhesion, and uneven illumination causing missed detections and blurred boundaries in traditional YOLOv8n. This paper proposes a high-precision, lightweight solution based on an enhanced YOLOv8n with improvements in network architecture, feature fusion, and attention mechanism. The backbone’s C2f module is replaced with C2f-Faster-CGLU, integrating partial convolution (PConv) local convolution and convolutional gated linear unit (CGLU) gating to reduce computational redundancy via sparse interaction and enhance small-target feature extraction. A bidirectional feature pyramid network (BiFPN) weights multiscale feature fusion to improve edge positioning accuracy of dense grains. Attention mechanism for fine-grained classification (AFGC) is embedded to focus on texture and damage details, enhancing adaptability to light fluctuations. The Detect_Rice lightweight head compresses parameters via group normalization and dynamic convolution sharing, optimizing small-target response. The improved model achieved 96.8% precision and 96.2% mAP. Combined with a quantity–mass model, SR/BR detection errors reduced to 1.11% and 1.24%, meeting national standard (GB/T 29898-2013) requirements, providing an effective real-time solution for intelligent hulling sorting. Full article