Search Results (3,533)

Shifts in the environment due to climate change necessitate breeding efforts aimed at adapting wheat to longer, warmer growing seasons. In this study, 21 modern wheat (Triticum aestivum L.) cultivars and 29 landraces were screened for flag leaf starch levels, with the goal of identifying a genetic marker for targeted breeding. The landrace PI 61693 was identified as having exceptionally high flag leaf starch values. Yield trials were carried out in a Berkut × PI 61693 recombinant inbred line (RIL) population and a negative correlation was observed between leaf starch, flowering time, and yield. Genetic mapping identified a Quantitative Trait Loci (QTL) explaining 22–34% variation for leaf starch, flowering time, biomass, and seed yield. The starch synthase TraesCS7D02G117800 (wSsI-1) is located in this region, which possibly accounts for leaf starch variation in this population; also within this QTL is TraesCS7D02G111600 (FT-D1). Sequencing of FT-D1 identified a single base pair deletion in the 3rd exon of the Berkut allele. This indel has recently been shown to significantly impact flowering time and productivity, and likely led to significant variation in flowering date and yield in this population. Here, we illustrate how allelic selection of FT-D1 within breeding programs may aid in adapting wheat to changing environments. Full article

High-throughput sequencing (HTS) has revolutionized phytopathology by overcoming many limitations of traditional diagnostic methods, as it permits precise pathogen monitoring, identification, and control, with ribosomal DNA (rDNA) regions serving as reliable markers for fungal classification. In this study, next-generation sequencing (NGS) was used, targeting the ITS1 and ITS2 regions to explore fungal diversity and pathogen presence in winter wheat grain samples and identifying 183 OTU sequences across 115 taxa. The ITS1 analysis yielded 249,743 reads, with Fusarium sp. (61%) as the dominant pathogenic taxon, followed by Sporobolomyces sp. (14%), Cladosporium sp. (3%), and other yeast-like or saprotrophic fungi, such as Cryptoccocus spp., F. wieringae, and B. alba. Sequencing of ITS1 also permitted the detection of F. acuminatum and the quarantine-regulated pathogens T. caries and T. triticoides. The ITS2 analysis produced 179,675 reads, with F. culmorum (47%) as the most abundant taxon, confirming significant grain contamination with this pathogen. Other frequently detected taxa included yeast-like fungi such as C. tephrensis (21%) and V. victoriae (13%), along with saprotrophic species like S. roseus and Davidella sp. ITS2 provided better resolution for the identification of Fusarium species by the detection of more pathogenic taxa associated with cereal diseases, including F. culmorum, as well as F. cerealis, F. poae, and F. tricinctum. The analysis revealed a diverse fungal community, including other pathogens such as A. porri, B. cinerea, and C. herbarum, as well as various non-pathogenic and saprotrophic fungal taxa. These findings underscore the complementary utility of ITS1 and ITS2 in profiling fungal diversity and detecting critical pathogens using HTS, highlighting the potential of these DNA regions for monitoring and managing cereal crop health. Full article

Durum wheat (Triticum durum Desf.) is the second most cultivated species of wheat after common wheat. In this study, the physical properties of ears and kernels of durum winter wheat were evaluated, focusing on the effects of sowing date and density. Understanding these properties is crucial for assessing the quality and technological utility of wheat. Three winter varieties of wheat, Komnata, Pentadur, and Auradur, were cultivated in the Małopolska Voivodeship of Poland. Two sowing dates (optimal and delayed) and three sowing densities (400, 500, and 600 kernels/m²) were employed. Significant variations in morphological traits—including plumpness, uniformity, density, and kernel dimensions—were analyzed. The results indicated that while the sowing date significantly influenced spike characteristics and grain yields, the sowing density had minimal effects. For example, plants sown earlier produced longer spike rachis and higher grain yield, reflecting the correlation between sowing time and spike development. This study highlights that grain plumpness varied significantly due to sowing dates, with delayed sowing yielding higher plumpness percentages. However, the overall volumetric weight of the grains was lower than the standard, indicating suboptimal growing conditions in Małopolska. Ultimately, this research underscores the importance of selecting appropriate sowing dates for optimal developmental outcomes in durum wheat, particularly under atypical growing conditions. Moreover, the results obtained partially indicate that worse physical spike biometry parameters can, to some extent, play a role in determining better quality of grain yield. Full article

Accurate regional crop classification, acreage estimation, yield prediction, and crop water requirement assessment are essential for effective agricultural planning and market forecasts. This study uses an integrated geospatial and statistical approach to assess major winter crops wheat and sugarcane cultivation in Ghotki District, Pakistan, from 2017/18 to 2022/23. It combines satellite data from Landsat 8 and Sentinel-2, ground truthing, and crop reporting records to analyze key factors such as cultivation area, crop gradients, vegetation health, normalized difference vegetation index (NDVI)-based wheat and sugarcane yield models, crop water requirements, and total irrigation water consumption. Results showed that wheat cultivation areas ranged from 15% to 19%, with the highest coverage observed in the 2021/22 winter season. Sugarcane cultivation ranged from 6% to 10%, peaking in the 2018/19 season. A strong linear association between NDVI and wheat yield (R² = 0.86) was observed. Wheat and sugarcane yield predictions utilized linear regression, and robust linear regression models, all of which were validated by the findings. Irrigation water demand for the winter season was calculated at 1887 million cubic meters (MCM) in 2017/18, with 1357 MCM supplied by the Sindh Irrigation Drainage Authority (SIDA). By 2020/21, water demand reached 2023 MCM, while SIDA’s supply was 1357 MCM. These results highlight the significance of integrating geospatial analysis with statistical records to provide timely, reliable estimates for cropped areas, yield forecasting, vegetation dynamics, and irrigation planning. The proposed methodology contributes a scaleable solution for informed decision-making in agricultural and water resource management, applicable across other districts in Pakistan and on a global scale. Full article

Agricultural productions are deeply affected by the phenological changes, especially in Shanxi Province, where Southern Shanxi is the main production area of winter wheat. Studying the phenological changes of this region and clarifying the effects of varieties and sowing dates on the phenological characteristics of southern Shanxi can be used for efficient introduction and scientific sowing. We have analyzed the meteorological datasets, phenological period data, and crop management data of seven observation points in the main winter wheat producing areas of Shanxi Province from 1992 to 2021. Trend analysis was used to analyze the time variation trend of various meteorological factors from 1992 to 2021. These results showed that the growth period was mainly advanced, especially in Changzhi and Yuncheng. The sensitivity analysis showed that the growth period of most sites were positively correlated with the sensitivity of various climate factors. Except for jointing to heading stage, the sensitivity of the duration of other growth stages to average temperature was positive, indicating that high temperature had an effect on effective vernalization and early reproductive growth of winter wheat. The modeling results showed that the growth period of winter wheat in Shanxi showed a trend of delay from sowing to ripening, and the sensitivity to temperature showed an increasing trend from sowing to ripening, while the sensitivity to precipitation was the opposite. Meanwhile, an earlier sowing date will make winter wheat develop earlier in warm climate conditions, requiring attention to cold prevention after winter. It is recommended to plant YH-20410 or YH-805 as suitable varieties in the Yuncheng area. In the future, this area can also moderately introduce new varieties with high heat requirements, which can, to some extent, offset the negative impacts of climate change. Full article

Bioethanol is a renewable, environmentally-friendly biofuel conventionally produced through the alcoholic fermentation of sugary or starch-rich substrates by microorganisms, commonly Yeast Saccharomyces cerevisiae. Intermediates of industrial wheat flour wet milling processing to starch, such as A-starch and B-starch milk, are cost-effective, abundant, and non-seasonal feedstocks for bioethanol production. This study evaluates the bioethanol production from wheat A-starch and B-starch milk and mixtures of these two substrates in different ratios (1:3, 1:1, and 3:1) using two cold hydrolysis procedures at 65 °C: (i) simultaneous liquefaction and saccharification (SLS) followed by fermentation, and (ii) liquefaction by alpha-amylase followed by simultaneous saccharification and fermentation (SSF). The results demonstrated that SSF and SLS are equally efficient procedures for reaching a high ethanol yield of 53 g per 100 g of starch and 93% of starch conversion to ethanol for all investigated substrates. Lower levels of non-starch components in A-starch milk, which typically contribute to volatile by-product formation, allowed clear distillate profiles in terms of and lower content of aldehydes, methanol, and volatile acidity, enhancing ethanol distillate purity compared to B-starch milk. Mixing high-quality A-starch milk with low-cost B-starch milk enables higher ethanol yield, improved distillate quality, and energy savings for efficient industrial-scale applications. Full article

Common wheat production is significantly influenced by abiotic stresses. Identifying the genetic loci for seedling root traits and developing the available molecular markers are crucial for breeding high yielding and stable varieties. In this study, five wheat seedling root traits, including root length (RL), root surface area (RA), root volume (RV), number of root tips (RT), and root dry weight (RW), were measured in the Wp-072/Wp-119 recombinant inbred line (RIL) population. Genotyping was conducted for the RIL population and their parents using the wheat 90K single-nucleotide polymorphism (SNP) chip. In total, three quantitative trait loci (QTLs) for RL (QRL.gau-1DS, QRL.gau-1DL and QRL.gau-4AL), two QTLs for RA (QRA.gau-1D and QRA.gau-2DL), one locus for RV (QRV.gau-6AS), two loci for RW (QRW.gau-2DL and QRW.gau-2AS), and two loci for RT (QRT.gau-3AS and QRT.gau-6DL) were identified, with each explaining 4.5–8.4% of the phenotypic variances, respectively. Among these, QRT.gau-3AS, QRL.gau-4AL, and QRV.gau-6AS overlapped with the previous reports, whereas the other seven QTLs were novel. The favorable alleles of QRL.gau-1DS, QRL.gau-1DL, QRL.gau-4AL, QRA.gau-1D, QRW.gau-2AS, QRV.gau-6AS, QRT.gau-3AS, and QRT.gau-6DL were contributed by Wp-072, whereas the other two loci originated from Wp-119. Additionally, five kompetitive allele-specific PCR (KASP) markers, KASP-RL-1DL for RL, KASP-RA-1D and KASP-RA-2DL for RA, KASP-RW-2AS and KASP-RW-2DL for RW, were developed and validated successfully in 149 wheat accessions. Furthermore, seven candidate genes mainly for plant hormones were selected and validated by quantitative real-time PCR (qRT-PCR). This study provides new loci, new candidate genes, available KASP markers, and varieties for optimizing wheat root system architecture. Full article

Wheat is a key staple crop globally, essential for food security and sustainable agricultural development. The results of this study highlight how innovative monitoring techniques, such as UAV-based multispectral imaging, can significantly improve agricultural practices by providing precise, real-time data on crop growth. This study utilized unmanned aerial vehicle (UAV)-based remote sensing technology at the wheat experimental field of the Hebei Academy of Agriculture and Forestry Sciences to capture the dynamic growth characteristics of wheat using multispectral data, aiming to explore efficient and precise monitoring and management strategies for wheat. A UAV equipped with multispectral sensors was employed to collect high-resolution imagery at five critical growth stages of wheat: tillering, jointing, booting, flowering, and ripening. The data covered four key spectral bands: green (560 nm), red (650 nm), red-edge (730 nm), and near-infrared (840 nm). Combined with ground-truth measurements, such as chlorophyll content and plant height, 21 vegetation indices were analyzed for their nonlinear relationships with wheat growth parameters. Statistical analyses, including Pearson’s correlation and stepwise regression, were used to identify the most effective indices for monitoring wheat growth. The Normalized Difference Red-Edge Index (NDRE) and the Triangular Vegetation Index (TVI) were selected based on their superior performance in predicting wheat growth parameters, as demonstrated by their high correlation coefficients and predictive accuracy. A random forest model was developed to comprehensively evaluate the application potential of multispectral data in wheat growth monitoring. The results demonstrated that the NDRE and TVI indices were the most effective indices for monitoring wheat growth. The random forest model exhibited superior predictive accuracy, with a mean squared error (MSE) significantly lower than that of traditional regression models, particularly during the flowering and ripening stages, where the prediction error for plant height was less than 1.01 cm. Furthermore, dynamic analyses of UAV imagery effectively identified abnormal field areas, such as regions experiencing water stress or disease, providing a scientific basis for precision agricultural interventions. This study highlights the potential of UAV-based remote sensing technology in monitoring wheat growth, addressing the research gap in systematic full-cycle analysis of wheat. It also offers a novel technological pathway for optimizing agricultural resource management and improving crop yields. These findings are expected to advance intelligent agricultural production and accelerate the implementation of precision agriculture. Full article

CRISPR/Cas9-mediated homology-directed repair (HDR) is a powerful tool for precise genome editing in plants, but its efficiency remains low, particularly for targeted amino acid substitutions or gene knock-ins. Successful HDR requires the simultaneous presence of Cas9, guide RNA, and a repair template (RT) in the same cell nucleus. Among these, the timely availability of the RT at the double-strand break (DSB) site is a critical bottleneck. To address this, we developed a sequential transformation strategy incorporating a deconstructed wheat dwarf virus (dWDV)-based autonomously replicating delivery system, effectively simplifying the process into a two-component system. Using this approach, we successfully achieved the targeted editing of the OsEPSPS gene in rice with a 10 percent HDR efficiency, generating three lines (TIPS1, TIPS2, and TIPS3) with amino acid substitutions (T172I and P177S) in the native EPSPS protein. The modifications were confirmed through Sanger sequencing and restriction digestion assays, and the edited lines showed no yield penalties compared to wild-type plants. This study demonstrates the utility of viral replicons in delivering gene-editing tools for precise genome modification, offering a promising approach for efficient HDR in crop improvement programs. Full article

Fusarium head blight (FHB) is a serious fungal disease of wheat and other small cereal grains, significantly reducing grain yield and producing mycotoxins that affect food safety. There is a need for disease detection technologies to determine the right time to apply fungicides, as FHB infection begins before visible symptoms appear. Using multispectral remote sensing by an unmanned aircraft system (UAS), wheat plants were observed under field conditions infested with FHB and simultaneously protected with fungicides sprayed with four different types of nozzles, as well as corresponding control plots infested with FHB only. The results showed that the levels of deoxynivalenol (DON) differed significantly between the five treatments, indicating that the control had the highest DON concentration as no fungicide treatment was applied. This study revealed that the assessment of the normalized difference vegetation index (NDVI) after FHB infection could be useful for predicting DON accumulation in wheat, as a significant negative correlation between DON and NDVI values was measured 24 days after anthesis. The decreasing NDVI values at the end of the growth cycle were expected due to senescence and yellowing of the wheat spikes and leaves. Therefore, significant differences in the NDVI were observed between three measurement points on the 13th, 24th, and 45th day after anthesis. Additionally, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge index (NDRE) were in significant positive correlation with the NDVI at 24th day after anthesis. The use of appropriate measurement points for the vegetation indices can offer the decisive advantage of enabling the evaluation of very large breeding trials or farmers’ fields where the timing of fungicide application is particularly important. Full article

This study investigates the dynamic changes in wheat canopy spectral characteristics across seven critical growth stages (Tillering, Pre-Jointing, Jointing, Post-Jointing, Booting, Flowering, and Ripening) using UAV-based multispectral remote sensing. By analyzing four key spectral bands—green (G), red (R), red-edge (RE), and near-infrared (NIR)—and their combinations, we identify spectral features that reflect changes in canopy activity, health, and structure. Results show that the green band is highly sensitive to chlorophyll activity and low canopy coverage during the Tillering stage, while the NIR band captures structural complexity and canopy density during the Jointing and Booting stages. The combination of G and NIR bands reveals increased canopy density and spectral concentration during the Booting stage, while the RE band effectively detects plant senescence and reduced spectral uniformity during the ripening stage. Time-series analysis of spectral data across growth stages improves the accuracy of growth stage identification, with dynamic spectral changes offering insights into growth inflection points. Spatially, the study demonstrates the potential for identifying field-level anomalies, such as water stress or disease, providing actionable data for targeted interventions. This comprehensive spatio-temporal monitoring framework improves crop management and offers a cost-effective, precise solution for disease prediction, yield forecasting, and resource optimization. The study paves the way for integrating UAV remote sensing into precision agriculture practices, with future research focusing on hyperspectral data integration to enhance monitoring models. Full article

Wheat plants encounter both biotic and abiotic pressure in their surroundings. Among the biotic stress factors, the Russian wheat aphid (RWA: Diuraphis noxia Kurdjumov) decreases grain yield and quality. The current RWA control strategies, including resistance breeding and the application of aphicides, are outpaced and potentially environmentally harmful. Alternatively, priming can stimulate defence responses to RWA infestation. This study investigated the priming potential of two priming agents, avirulent Puccinia triticina (Pt) isolates and salicylic acid (SA), against RWA infestation. The priming effect of Pt isolates and SA in reducing RWA-induced leaf damage and increased antioxidant activities is an indication of defence responses. Selected South African wheat cultivars and Lesotho landraces, grown under greenhouse conditions, were inoculated with Pt isolates (UVPt13: avirulent, UVPt26: virulent) and treated with SA at the seedling or booting stages. The leaf damage rating score was used for phenotyping. The antioxidant-mediated defence responses were evaluated in three selected cultivars for further priming investigation. Our results revealed that the priming agents significantly reduced the leaf damage in most cultivars at both growth stages, and UVPt13 and SA priming significantly (p ≤ 0.05) increased superoxide dismutase, peroxidase, and ascorbate peroxidase activities. However, catalase activity exhibited a more pronounced decline in plants treated with the UVPt13 isolate. The Pt isolate priming was more efficient than the SA application. However, it is crucial to investigate the potential of effectors from the avirulent Pt isolate to prime wheat plants for resistance against RWA infestation. This could contribute to developing strategies to enhance crop protection and relieve pest pressure in wheat production. Full article

In recent years, surface ozone (O₃) pollution has emerged as a significant barrier to the continued improvement of air quality in China, making O₃ risk assessment a critical research priority. Using nationwide O₃ monitoring data, this research investigated the spatial characteristics of O₃ pollution and assessed its potential impacts on human health and crop yields. The results showed that the maximum daily 8 h average O₃ (MDA8 O₃) exhibited higher concentrations in eastern and northern regions, and lower concentrations in the western and southern regions of China. Long-term O₃ exposure was associated with an estimated 175,154 all-cause deaths nationwide, with the highest health risks observed in Shandong, Henan, and Jiangsu provinces. The AOT40 values for the winter wheat and single-rice growing seasons in China were 9.30 × 10³ ppb·h and 1.29 × 10⁴ ppb·h, respectively. Moreover, O₃ exposure led to relative yield losses of 22.1% for winter wheat and 9.3% for single rice, corresponding to crop yield losses (CPLs) of 63 million metric tons and 14 million metric tons, respectively. Higher winter wheat CPL values were primarily concentrated in Henan, Shandong, and Hebei, while higher single rice CPL values were observed in Jiangsu, Hubei, and Anhui. This study presents a novel coupling of O₃ pollution exposure with human health and agricultural risk assessments across China, emphasizing the need for region-specific O₃ management strategies to protect public health and ensure agricultural sustainability. In conclusion, this study highlights the importance of targeted O₃ control in densely populated and major crop-producing areas to mitigate health risks and yield losses, thus safeguarding ecosystem health and food security. Full article

The agricultural water–soil matching coefficient is a key factor for reflecting regional grain production status, which can be used to evaluate the reasonableness of water–soil allocation in certain areas. Taking the North China Plain (NCP) as the study area, in this study, we constructed a framework from a “physical water–water footprint” standpoint. The binary matching characteristics of “water–soil–grain” were then analyzed, and the water–soil matching coefficient method was employed to evaluate the pattern of water–soil matching for the years 1984, 1998, 2003, and 2022. Through the perspective of physical water–water footprint coupling, field trials of grain were utilized to calculate the range of water–soil matching coefficients under high yields. The results showed the following: ① From 1949 to 2022, the grain yield and planting areas increased. Wheat, the dominant crop, required substantial irrigation. Precipitation, cultivated land, and irrigation water exhibited spatial mismatches over the last ten years. ② The total water footprint showed an increasing trend, and the blue water footprint accounted for 19.47%. The spatial distribution of the water and land footprints of grain crops largely overlapped, and their values were higher in the central and southern regions, and lower in the north. ③ The current water–soil matching coefficient was in the range of [0.28, 1.75], which fell outside the optimal range of [0.534, 0.724]. The soil–water matching coefficients of wheat and rice were overall higher than those of other crops. We found higher values in the southwestern region and lower values in the northern areas, which aligns with the boundary of the groundwater funnel area. To address the identified challenges, we recommend implementing a tiered regulatory zone system based on the matching coefficient. The government should encourage a reduction in water-intensive crops like wheat and rice in high-value regions by providing subsidies. Additionally, a monitoring mechanism for water and soil compatibility should be established, considering the specific growth requirements of various crops. Full article

As an important physiological indicator, wheat canopy temperature (CT) can be observed after flowering in an attempt to predict wheat yield and quality. However, the relationship between CT and wheat yield and quality is not clear. In this study, the CT, photosynthetic rate (Pn), filling rate, wheat yield, and wheat quality of 68 wheat lines were measured, in an attempt to establish a connection between CT and yield and quality and accelerate the selection of new varieties. This experiment used an infrared imaging camera to measure the CT of wheat materials planted in the field in 2022. Twenty materials with significant temperature differences were selected for planting in 2023. By comparing the temperature trends in 2022 and 2023, it is believed that materials 4 and 13 were cold-type materials, while materials 3 and 11 were warm-type materials. The main grain filling period of cold-type materials occurs in the middle and late stages of the grain filling period and the Pn and the thousand-grain weights of cold-type materials were higher than those of warm-type materials. Similarly, under continuous rainy conditions, cold-type materials had a higher protein and wet gluten contents, while warm-type materials had higher sedimentation values and shorter formation times. Full article