Search Results (106)

Nowadays, there is special interest in promoting the consumption of ancestral crops and minimally processed foods with high nutritional value. However, besides nutritional issues, safety assessments must be addressed. This study aimed to evaluate mycotoxin contamination in five minimally processed traditional Ecuadorian foods: ochratoxin A (OTA), fumonisin B₁ (FB₁), and aflatoxins (AFs) in brown rice, lupin, and quinoa; OTA, FB₁, and deoxynivalenol (DON) in whole-wheat flour; and OTA and AFs in peanuts. Samples (45 samples of peanuts and whole-wheat flour, 47 of brown rice, 46 of quinoa, and 36 of lupin) were collected from local markets and supermarkets in the three most populated cities in Ecuador. Mycotoxins were determined by RP-HPLC with fluorescence and detection. Results were compared with the maximum permitted levels (MPLs) of European Regulation 2023/915/EC. Overall contamination reached up to 59.8% of the analyzed samples (38.4% with one mycotoxin and 21.5% with co-occurrence). OTA was the most prevalent mycotoxin (in 82.6% of quinoa, 76.7% of whole-wheat flour, 53.3% of peanuts, 48.6% of lupin, and 25.5% of brown rice), and a modest number of quinoa (17%) and lupin (5.7%) samples surpassed the MPLs. DON was found in 82.2% of whole-wheat flour (28.9% > MPL). FB₁ was detected in above 25% of brown rice and whole-wheat flour and in 9% of the quinoa samples. FB₁ levels were above the MPLs only for whole-wheat flour (17.8%). AFB₁ and AFG₁ showed similar prevalence (about 6.5 and 8.5%, respectively) in quinoa and rice and about 27% in peanuts. Overall, these findings underscore the importance of enhancing fungal control in the pre- and post-harvest stages of these foods, which are recognized for their high nutritional value and ancestral worth; consequently, the results present key issues related to healthy diet promotion and food sovereignty. This study provides compelling insights into mycotoxin occurrence in minimally processed Ecuadorian foods and highlights the need for further exposure assessments by combining population consumption data. Full article

Rice (Oryza sativa L.) is a crucial crop for biofortification that is widely consumed and is cultivated in soils with low levels of selenium (Se) and zinc (Zn). The study evaluated how upland rice genotypes can increase Se and Zn in grains with foliar fertilization and analyzed the impact on agronomic characteristics and protein and amino acid contents. Experiments in Lambari and Lavras used a 5 × 4 factorial design with five genotypes (BRS Esmeralda, CMG 2188, CMG ERF 221-16, CMG ERF 221-19, CMG ERF 85-15) and four treatments (control, without Se; 5.22 g Se ha⁻¹; 1.42 kg Zn ha⁻¹; and combined Zn+Se) with three replicates. The study showed that CMG ERF 85-15, with Se fertilization, increased grain yield in Lambari. In Lavras, adding Zn to CMG 2188 and CMG ERF 85-15 improved grain yield. In Lambari, most variables were grouped with Zn+Se, except grain yield and free amino acids in the grain. In Lavras, variables associated with Se, proteins, free amino acids in the polished grain, hulling in whole and polished grain, and milling yield were grouped under the treatment Zn+Se. We recommend the genotype CMG ERF 85-15 based on the results for foliar biofortification with Zn+Se. Full article

Soil salinization, a major challenge caused by climate change over the past century, critically affects cultivated land and consequently reduces agricultural production worldwide. Recently, plant growth-promoting rhizobacteria have been collected and utilized to enhance plant growth and mitigate the effects of salt stress in different plant species including rice. In our current study, the Serratia marcescens strain VIRS2 with remarkable salt tolerance was successfully isolated from the saline soil in the Mekong River Delta of Vietnam. This isolate exhibited diverse plant growth-promoting properties, especially the production of a high indole acetic acid level. Treatments under both in vitro and greenhouse conditions indicated that VIRS2 could enhance growth and salt tolerance in rice. The VIRS2-inoculated rice plants exhibited biochemical profile alterations including proline, malondialdehyde, and relative water contents. In addition, the expression of genes involved in the plant stress response pathways was upregulated in the VIRS2-inoculated rice under salt treatments. Importantly, the whole genome sequencing data of VIRS2 also showed the presence of different genes associated with plant growth-promotion and stress-tolerance mechanisms. These results indicated the potential of the VIRS2 isolate for enhancing growth and salt tolerance in rice as well as other important crops. Full article

The Normalized Difference Vegetation Index (NDVI) is an important remote sensing index that is widely used to assess vegetation coverage, monitor crop growth, and predict yields. Traditional NDVI calculation methods often rely on multispectral or hyperspectral imagery, which are costly and complex to operate, thus limiting their applicability in small-scale farms and developing countries. To address these limitations, this study proposes an NDVI estimation method based on low-cost RGB (red, green, and blue) UAV (unmanned aerial vehicle) imagery combined with deep learning techniques. This study utilizes field data from five major crops (cotton, rice, maize, rape, and wheat) throughout their whole growth periods. RGB images were used to extract conventional features, including color indices (CIs), texture features (TFs), and vegetation coverage, while convolutional features (CFs) were extracted using the deep learning network ResNet50 to optimize the model. The results indicate that the model, optimized with CFs, significantly enhanced NDVI estimation accuracy. Specifically, the R² values for maize, rape, and wheat during their whole growth periods reached 0.99, while those for rice and cotton were 0.96 and 0.93, respectively. Notably, the accuracy improvement in later growth periods was most pronounced for cotton and maize, with average R² increases of 0.15 and 0.14, respectively, whereas wheat exhibited a more modest improvement of only 0.04. This method leverages deep learning to capture structural changes in crop populations, optimizing conventional image features and improving NDVI estimation accuracy. This study presents an NDVI estimation approach applicable to the whole growth period of common crops, particularly those with significant population variations, and provides a valuable reference for estimating other vegetation indices using low-cost UAV-acquired RGB images. Full article

Germinated whole seeds possess elevated levels of bioactive nutrients; however, their application is hindered by several constraints. The germination process is typically time-consuming, and germinated seeds present challenges in terms of storage and transportation compared to dry seeds. This study introduces a novel processing method for rice, termed prolonged priming (PLP), aiming to combine the benefits of germinated and dry seeds. PLP involves soaking the seeds until the embryo exposure stage, followed by redrying. At 10 h (hour) germination post PLP, the γ-aminobutyric acid (GABA) levels in Hanyou73 (HY73) and IRAT exceeded 20 mg/100 g. Additionally, there was an induction of various nutrient components, including an increase in protein content, a reduction in amylose levels, and an elevation in fatty acid content, among others. Malondialdehyde levels, indicating oxidative damage, remained stable, and PLP preserved better seed integrity compared to routine priming in the desiccation-tolerant HY73. Collectively, the PLP treatment demonstrates an optimization of the nutritional value and storage in germinated brown rice (GBR). This novel process holds potential for enhancing the nutritional profile of GBR and may be applicable to other crop species. Full article

The pigment content of rice leaves plays an important role in the growth and development of rice. The accurate and rapid assessment of the pigment content of leaves is of great significance for monitoring the growth status of rice. This study used the Analytical Spectra Device (ASD) FieldSpec 4 spectrometer to measure the leaf reflectance spectra of 4 rice varieties during the entire growth period under 4 nitrogen application rates and simultaneously measured the leaf pigment content. The leaf’s absorption spectra were calculated based on the physical process of spectral transmission. An examination was conducted on the variations in pigment composition among distinct rice cultivars, alongside a thorough dissection of the interrelations and distinctions between leaf reflectance spectra and absorption spectra. Based on the vegetation index proposed by previous researchers in order to invert pigment content, the absorption spectrum was used to replace the original reflectance data to optimize the vegetation index. The results showed that the chlorophyll and carotenoid contents of different rice varieties showed regular changes during the whole growth period, and that the leaf absorption spectra of different rice varieties showed more obvious differences than reflectance spectra. After replacing the reflectance of pigment absorptivity-sensitive bands (400 nm, 550 nm, 680 nm, and red-edge bands) with absorptivities that would optimize the vegetation index, the correlation between the vegetation index, which combines absorptivity and reflectivity, and the chlorophyll and carotenoid contents of 4 rice varieties during the whole growth period was significantly improved. The model’s validation results indicate that the pigment inversion model, based on the improved vegetation index using absorption spectra, outperforms the traditional vegetation index-based pigment inversion model. The results of this study demonstrate the potential application of absorption spectroscopy in the quantitative inversion of crop phenotypes. Full article

Leaf nitrogen content (LNC) is a vital agronomic parameter in rice, commonly used to evaluate photosynthetic capacity and diagnose crop nutrient levels. Nitrogen deficiency can significantly reduce yield, underscoring the importance of accurate LNC estimation for practical applications. This study utilizes hyperspectral UAV imagery to acquire rice canopy data, applying various machine learning regression algorithms (MLR) to develop an LNC estimation model and create a nitrogen concentration distribution map, offering valuable guidance for subsequent field nitrogen management. The analysis incorporates four types of spectral data extracted throughout the rice growth cycle: original reflectance bands (OR bands), vegetation indices (VIs), first-derivative spectral bands (FD bands), and hyperspectral variable parameters (HSPs) as model inputs, while measured nitrogen concentration serves as the output. Results demonstrate that the random forest regression (RFR) and gradient boosting decision tree (GBDT) algorithms performed effectively, with the GBDT achieving the highest average R² of 0.76 across different nitrogen treatments. Among the nitrogen estimation models for various rice varieties, RFR exhibited superior accuracy, achieving an R² of 0.95 for the SuXiangJing100 variety, while the GBDT reached 0.93. Meanwhile, the support vector machine regression (SVMR) showed slightly lower accuracy, and partial least-squares regression (PLSR) was the least effective. This study developed an LNC estimation method applicable to the whole growth stage of common rice varieties. The method is suitable for estimating rice LNC across different growth stages, varieties, and nitrogen treatments, and it also provides a reference for nitrogen estimation and fertilization planning at flight altitudes other than the 120 m used in this study. Full article

The rice variety Bomba is grown in Calasparra—a rice of origin in southeast Spain—resulting in a product with excellent cooking quality, although its profitability has declined in recent years due to low grain yields and susceptibility to rice blast disease (Pyricularia oryzae Cavara). An innovation project to test the efficacy of mechanized transplanting against traditional direct seed sowing was conducted in 2022 and 2023 at four locations for the first time. A lower plant density (67–82 plants m⁻²) and shorter plants with higher leaf nitrogen content were observed in transplanted plots compared with seed sowing (130–137 plants m⁻²) in the first year. The optimal climatic conditions for P. oryzae symptom appearance were determined as temperatures of 25–29 °C and a 50–77% relative humidity. The most-affected sowing plots presented 3–20% leaf area damage and a reduction in yield to values of 1.5 t ha⁻¹ in the first year and 2.12 t ha⁻¹ in the second year. In transplanted plots, there was generally less humidity at the plant level and therefore, disease incidence was low in both seasons. Grain yields did not significantly differ among the treatments studied; however, there were differences in the yield components of panicle density and the number of grains for panicles. Principal component analysis revealed two principal components that explained 81% of the variability. Variables related to yield contributed positively to the first component, while plant biomass variables contributed to the second component. Plant density, tiller density, and panicle density were found to be positively correlated (r > 0.81 ***). Overall, transplanting (frame of 30 × 15–18 cm²) resulted in uniform crop growth with less rice blast disease, as well as higher grain yields (2.92–3.89 t ha⁻¹), in comparison with the average for the whole D.O. Calasparra (2.3–2.5 t ha⁻¹) in both seasons and a good percentage of whole grains at milling. This is novel knowledge which can be considered useful for farmers operating in the region. Full article

Salinity is a common abiotic stress that limits crop productivity. Although there is a wealth of evidence suggesting that miRNA and lncRNA play important roles in the response to salinity in rice seedlings and reproductive stages, the mechanism by which competing endogenous RNAs (ceRNAs) influence salt tolerance and yield in rice has been rarely reported. In this study, we conducted full whole-transcriptome sequencing of rice panicles during the reproductive period to clarify the role of ceRNAs in the salt stress response and yield. A total of 214 lncRNAs, 79 miRNAs, and 584 mRNAs were identified as differentially expressed RNAs under salt stress. Functional analysis indicates that they play important roles in GO terms such as response to stress, biosynthesis processes, abiotic stimuli, endogenous stimulus, and response to stimulus, as well as in KEGG pathways such as secondary metabolite biosynthesis, carotenoid biosynthesis, metabolic pathways, and phenylpropanoid biosynthesis. A ceRNA network comprising 95 lncRNA–miRNA–mRNA triplets was constructed. Two lncRNAs, MSTRG.51634.2 and MSTRG.48576.1, were predicted to bind to osa-miR172d-5p to regulate the expression of OsMYB2 and OsMADS63, which have been reported to affect salt tolerance and yield, respectively. Three lncRNAs, MSTRG.30876.1, MSTRG.44567.1, and MSTRG.49308.1, may bind to osa-miR5487 to further regulate the expression of a stress protein (LOC_Os07g48460) and an aquaporin protein (LOC_Os02g51110) to regulate the salt stress response. This study is helpful for understanding the underlying molecular mechanisms of ceRNA that drive the response of rice to salt stress and provide new genetic resources for salt-resistant rice breeding. Full article

Expansin is a cell wall relaxant protein that is common in plants and directly or indirectly participates in the whole process of plant root growth, development and morphogenesis. A well-developed root system helps plants to better absorb water and nutrients from the soil while effectively assisting them in resisting osmotic stress, such as salt stress. In this study, we observed and quantified the morphology of the roots of Arabidopsis overexpressing the TaEXPAs gene obtained by the research group in the early stage of development. We combined the bioinformatics analysis results relating to EXPA genes in five plants and identified TaEXPA7-B, a member of the EXPA family closely related to root development in winter wheat. Subcellular localization analysis of the TaEXPA7-B protein showed that it is located in the plant cell wall. In this study, the TaEXPA7-B gene was overexpressed in rice. The results showed that plant height, root length and the number of lateral roots of rice overexpressing the TaEXPA7-B gene were significantly higher than those of the wild type, and the expression of the TaEXPA7-B gene significantly promoted the growth of lateral root primordium and cortical cells. The plants were treated with 250 mM NaCl solution to simulate salt stress. The results showed that the accumulation of osmotic regulators, cell wall-related substances and the antioxidant enzyme activities of the overexpressed plants were higher than those of the wild type, and they had better salt tolerance. This paper discusses the effects of winter wheat expansins in plant root development and salt stress tolerance and provides a theoretical basis and relevant reference for screening high-quality expansin regulating root development and salt stress resistance in winter wheat and its application in crop molecular breeding. Full article

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 OsALS1^627N 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 OsALS1^627N 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 OsALS1^627N 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. Full article

Rice cultivation serves as a significant anthropogenic source of methane (CH₄) and nitrous oxide (N₂O). Although N₂O emissions remain relatively small compared to CH₄ emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. While numerous studies have investigated nitrous oxide emissions in response to nitrogen fertilization, existing research assessing nitrous oxide emissions based on nitrogen fertilizer levels has often been limited to cultivation periods. Therefore, there is a need for comprehensive analyses covering the entire year, including the dry periods, to address nitrous oxide emissions as an important source throughout the entire agricultural cycle. In this case study, we investigated the characteristics of N₂O emissions in a central region of South Korea, where a single rice-cropping cycle occurs annually over a span of three whole years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N₂O emissions during rice cultivation and fallow periods. In this context, we attempted to discover the complex dynamics of N₂O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We discovered that the greater contribution of cumulative N₂O emissions during the fallow period made a much greater contribution (up to approximately 90%) to the whole-year N₂O emissions than those during the rice cultivation period. During the fallow period from rice harvest to rice planting in the following year, variations in N₂O emissions were associated with high-flux events after rainy periods on dry soils. This highlights the considerable influence of soil moisture content and weather conditions on N₂O emissions during the fallow period. This affects high emission events, which in turn significantly impact the cumulative emissions over the entire period. We underscore that assessing N₂O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N₂O emissions, periodic gas collection throughout a year covering both rice cultivation and fallow phases is required in alignment with the monitoring of different temperature and soil moisture conditions. We captured statistical differences in cumulative N₂O emissions due to nitrogen fertilization treatments across the three years. However, no significant difference was observed in the three-year average emissions among the different (one, one-and-a-half, and double) nitrogen fertilization treatments, with the exception of the control treatment (no fertilization). Based on the findings, we recommend at least three whole-year evaluations to ensure the estimation accuracy of N₂O emissions under different nitrogen fertilization conditions. The findings from this study could help prepare the further revision or refinement of N₂O emission factors from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC). Full article

Understanding the agronomic interventions that ensure higher crop yields and minimize their chances of failure is critical for meeting global nutritional demands. Rice is a staple food crop that is prone to lodging risk, particularly when higher yields are desired. The potential role of a combined application of Zinc (Zn) and Silicon (Si) in determining the grain yield and lodging resistance has been rarely investigated under field conditions. Thus, field trials were carried out to evaluate the grain yield and lodging resistance of rice at two different locations i.e., Qionghai and Wuzhishan, under three levels of Zn (0, 40, and 80 kg ha⁻¹) and Si (0, 120, and 240 kg ha⁻¹). The results showed that Zn application at the rates of 40 and 80 kg ha⁻¹ increased rice yield by 9% and 5% at Qionghai, and by 5% and 6% at Wuzhishan, respectively. The improved grain yield due to Zn application could be attributed to the increased panicles m⁻², splikelets m⁻², and aboveground biomass. Meanwhile, Zn failed to show any remarkable impact on stem and root lodging susceptibility. Conversely, no significant influence of applying Si on grain yield was observed, while its application at the rates of 120 and 240 kg Si ha⁻¹ enhanced the stem and root lodging resistance (denoted by their respective safety factors, for stem (SF_s) and for root (SF_r) by 32% and 22% at Qionghai, and by 11% and 34% at Wuzhishan, respectively, compared to zero Si application. The improved lodging resistance in terms of SF_s and SF_r could be ascribed to the increased stem bending strength and anchorage strength, while self-weight moment of whole plant decreased. In summary, a beneficial role of Si in lodging resistance and Zn in yield enhancement were evidenced in the present study across the two sites. It can be concluded that by combining 40 kg Zn ha⁻¹ with 120 kg Si ha⁻¹, both grain yield and lodging resistance could be simultaneously improved in rice crops. Full article

Rice is an essential diet component for a significant portion of the population worldwide. Due to the high water demand associated with rice production, improving water use efficiency and grain quality is critical to increasing the sustainability of the crop. This species includes rice varieties with diverse pigmentation patterns. Grain quality, including industrial, nutritional, and functional quality traits, of two black rice genotypes and a commercial white rice cultivar were evaluated in different locations and under different water regimes. Flooding produced higher grain weight compared to alternate wetting and drying irrigation. A high correlation was found between grain color, total phenolic content (TPC), and antioxidant activity. The black rice genotypes showed higher TPC levels and antioxidant capacity, mainly due to higher levels of cyanidin 3-O-glucoside. The phenolic profile varied between whole and polished grains, while mineral composition was influenced by location and irrigation regime. In turn, the environment influenced grain quality in terms of industrial and nutritional characteristics, with significant differences in quality between whole and polished grains. This study provides valuable information on the genotype–environment relationship in rice and its effect on grain quality, which could contribute to selecting genotypes for an appropriate environment. Full article

Aimed at addressing the problems of the existing straw choppers on combine harvesters, such as a large cutting resistance and poor cutting effect, combined with bionic engineering technology and biological characteristics, a bionic model was used to extract the characteristics of the cutting blades of locusta migratoria manilensis’s upper jaw. A 3D point cloud reconstruction and machine vision methods were used to fit the polynomial curve of the blade edge using Matlab 2016. A straw-cutting process was simulated using the discrete element method, and the cutting effect of the bionic blade was verified. Cutting experiments with rice straws were conducted using a physical property tester, and the cutting resistance of straw to bionic blades and general blades was compared. On the whole, the average cutting force of the bionic blades was lower than that of the general blades. The average cutting force of the bionic blade was 18.74~38.23% lower than that of a smooth blade and 1.63~25.23% lower than that of a serrated blade. Similarly, the maximum instantaneous cutting force of the bionic blade was reduced by 2.30~2.89% compared with the general blade, which had a significant drag reduction effect. By comparing the time–force curves of different blades’ cutting processes, it was determined that the drag-reducing effect of the bionic blade lies in shortening the straw rupture time. The larger the contact area between the blade and the straw, the more uniform the cutting morphology of the straw after cutting. Field experiment results indicate that the average power consumption of a straw chopper partially installed with bionic blades was 5.48% lower than one with smooth blades, measured using a wireless torque analysis module. In this research study, the structure of the straw chopper of an existing combine harvester was improved based on the bionic principle, which reduced resistance when cutting crop straw, thus reducing the power consumption required by the straw chopper and improving the effectiveness and stability of the blades. Full article