BMPR1Bis a pivotal gene that influences reproductive performance in sheep. The sheep populations that carry the FecB^Bmutation within this gene exhibit significantly higher lambing rates compared to wild-type populations. Therefore, screening for individuals carrying the FecB^Bmutation is crucial for effective sheep breeding programs. This study aims to establish a rapid, precise, and visualised on-site detection method for genotyping the prolific FecB^Bmutation in sheep. We combined the CRISPR/Cas12a system with the recombinase-polymerase amplification (RPA) technique. We introduced an additional nucleotide mismatch on the amplification primers to form a Cas12a-recognised protospacer adjacent motif (PAM) sequence. In addition, mismatches were introduced in CRISPR-derived RNA (crRNA) to enable naked-eye differentiation of the assay results. Subsequently, we validated the accuracy of the method by examining additional blood samples from 56 sheep representing four breeds. The results of using our developed system were highly consistent with the Sanger sequencing. Overall, the CRISPR/Cas12a-based detection provides a rapid and more versatitle method for FecB^Bgenotyping. It holds promise in enhancing efficiency in livestock breeding programmes for any single nucleotide mutations.

Different types of dietary fiber (DF) play important roles in enhancing intestinal health and overall performance in animals. This study investigated the effects of high-DF diets containing different ratios of soluble to insoluble dietary fiber (SDF:IDF) on growth performance, intestinal barrier integrity, microbiota, and metabolite profiles in weaned piglets. The four dietary treatments consisted of a basal diet (CON) and three high-DF diets withSDF:IDF ratios of 0.37, 0.25, and 0.13 (designated HF-0.37, HF-0.25, and HF-0.13, respectively). On days 14 and 28, colonic tumor necrosis factor-α, interleukin-1β, interleukin-6, and interleukin-8 concentrations were higher in the HF-0.37 group than in the CON, HF-0.25, and HF-0.13 groups (P<0.05). Plasma D-lactate and endotoxin levels were lower in the HF-0.25 group compared to the CON group at both time points (P<0.05). Furthermore, colonic zonula occludens 1 expression was upregulated in the HF-0.25 and HF-0.13 groups compared to the CON and HF-0.37 groups on day 14 (P<0.05). At the transcriptional level, all three high-DF diets modulated signaling pathways associated with inflammation and immune responses in the colon. Notably, DF supplementation particularly the HF-0.25 diet upregulated coloniclevels of 3-indole butyric acid, nicotinic acid, and 3-methylthiopropylamine on d 14 and reduced certain peptide levels by d 28. These findings indicate that DF supplementation, especially at an SDF:IDF ratio of 0.25, exerts beneficial effects on intestinal integrity in weaned piglets, potentially mediated by alterations in colonic metabolite profiles, whereas HF-0.37 and HF-0.13 exhibited limited impacts on intestinal barrier function.

The role of β-hydroxybutyric acid (BHBA) includes providing energy, regulating signaling pathways, and ameliorating the gut microbiota in the host, while its nutrient mechanism to improve rumen epithelium development in young ruminants is still unclear. In this study, a total of 12 female Haimen goats with 30 d of age were chosen and divided into two groups. One group was fed with basic diet (CON), and the other group was fed a basal diet supplemented with 6 g d–1 dietary β-hydroxybutyrate sodium (BHBA-Na). The experimental period was 30 d, and all goats were slaughtered at 60 d of age. The joint analysis of multi-omics, including rumen microbiota, rumen epithelial transcriptome and rumen epithelial metabolomics in young goat model, was performed to systematically investigate the effect of dietary BHBA-Na on rumen development in young goats. As the results, we found that dietary BHBA-Na improved the growth performance of young goat including body weight, average daily gain (ADG) and dry matter intake (DMI) (P<0.05). Dietary BHBA-Na also increased the weight of rumen, and promoted the growth of rumen epithelium development (P<0.05). The abundance of several beneficial bacteria was increased (Fibrobacter, Succinivibrio, Clostridiales, etc.). The rumen epithelium transcriptome and metabolomics indicated that BHBA-Na supplementation showed a remarkable effect on the nutrient metabolism of the rumen epithelium. Specifically, the pathways of “fatty acid metabolism”, “cholesterol homeostasis”, “reactive oxygen species (ROS) pathway” and “peroxisome” were activated in response to BHBA-Na addition (P<0.05). Moreover, the genes (HMGCS2, ECSH1, ACAA2, ECH1, ACADS etc.) and metabolites (succinic acid, alpha-ketoisovaleric acid, etc.) involved in these pathways were also regulated positively (P<0.05). The rumen epithelium obtained the energy for its development from the process of volatile fatty acids (VFAs) decomposition. Finally, we observed the close correlations among the phenotypes, ruminal microbiota, host genes and epithelial metabolites. Overall, our results revealed that the BHBA-Na promoted the growth and rumen development of young goats possibly by enhancing DMI and regulating the rumen microbiota and the metabolisms of VFA and amino acid in the rumen epithelium.

The H9N2 subtype avian influenza virus (AIV) hemagglutinin (HA) protein is a major immunogen in which HA1 is a genetic variant and HA2 is relatively conserved. Identifying broad-spectrum antigen epitopes targeting HA1 is crucial for vaccine design and detection. Based on the phylogenetic and serological analyses, we identified 2 antigenic groups and 3 representative viruses: A/chicken/Jiangsu/JY040218C/2019, A/pigeon/Jiangsu/JY020616/2019, and A/chicken/Jiangsu/WX090312/2018. An overlapping peptide library was synthesized using HA1 amino acid sequences of the viruses as templates. Through peptide scanning of the sera against different strains of H9N2 subtype AIV, we identified peptides from 4 regions (H9-2/3, H9-20/21, H9-26, and H9-29/30/31) that demonstrated broad-spectrum reactivity. Immunological assay results demonstrated that H9-21 (²¹⁹RIFKPLIGPRPLVNGLMGRI²³⁹), H9-26 (²⁶⁹SGESHGRILKTDLKMGSCTV²⁸⁹), and H9-30 (³⁰⁹YAFGNCPKYI GVKSLKLAVG³²⁹) effectively induced antibody generation and conferred partial protective efficacy against the parent virus JY040218C. The results of lymphocyte proliferation and ELISpot assays indicated that peptides H9-15 (¹⁵⁹MRWLTQKNNAYPTQDAQYTN¹⁷⁹), H9-22 (²²⁹PLVNGLMGRINYYWSVLKP G²⁴⁹), and H9-23 (²³⁹NYYWSVLKPGQTLRIKSDGN²⁵⁹) could effectively stimulate the expression of interferon-gamma in peripheral blood lymphocytes of chickens immunized against different strains of H9N2 AIV. Collectively, 5 novel cell epitopes H9-15, H9-22, H9-23, H9-26, and H9-30, including the best B cell epitope H9-26 and the best T cells epitope H9-22, were identified that could be targeted for vaccine design or detection approaches against H9N2 AIVs.

Soil organic carbon (SOC),representing the largest terrestrial organic carbon pool, significantly influences soil quality. The incorporation of residues is widely recognized as a method to regulate SOC sequestration. A 365-day incubation experiment was conducted to evaluate the contribution of straw-derived carbon (SDC) of varying quality to SOC fractions (free-floating particulate organic carbon (fPOC), occluded POC (oPOC) and mineral-associated OC (MAOC)), and examine the relationships between microorganisms and SOC fractions by incorporating ¹³C-labelled maize stem straw (ST), leave straw (LE), sheath straw (SH) (1%) in Chinese Mollisols. Results indicated that compared to control (CK), ST, LE and SH treatments enhanced SOC, fPOC and MAOC by 4.8–19.5, 35.7–49.5 and 1.6–3.9%, respectively. The SDC-SOC and MAOC content of LE were 29.1–38.1%and 17.5–44.5% higher than ST and SH, respectively. The SDC-oPOC content of SH was 3.1% higher than LE. The PLFA concentration decreased steadily throughout the incubation period, while necromass remained in-fluctuating until an obvious increasing trend observed at later stage. Furthermore, structural equation model (SEM) revealed that lignin to nitrogen ratio (LigN) of ST exhibited negative association with SDC-fPOC, and bacterial diversity in SH showed negative correlation with LigN and positive correlation with SDC-oPOC, while demonstrating positive correlation between microbial necromass and SDC-MAOC in LE. These findings indicated that POC dynamics correlated with straw chemical traits, while MAOC showed links toboth microbial necromass traits and straw chemical characteristics. These findings advance our understanding of how straw residue quality influences SOC turnover and stabilization through microbial communityinteractions, contributing to the development of policies to improve soil fertility, and promote the rational and efficient utilizationof straw.

Water-saving rice systems must maintain yield targets while reducing water consumption. Applying biodegradable film to cover the soil surface reduces water loss through evapotranspiration, establishing a warmer, more humid microenvironment for rice growth compared to traditional paddy rice systems. This study examined soil water regimes for rice production in Northeast China, comparing rice growth with and without biodegradable mulch film under continuous flooding, drip irrigation, and controlled irrigation conditions. The implementation of biodegradable mulch film elevated soil temperature and sustained soil moisture during early rice development. Continuous flooding with biodegradable mulch film yielded the highest rice production (9.4 Mg ha^–1) and net profit of approximately 11,800 CNY ha^–1. Drip irrigation with biodegradable mulch film achieved maximum water efficiency, demonstrating the highest water productivity (1.25 kg m^–3) and minimum water consumption (235 mm). Root length, weight, and surface area in the 0–40 cm soil layer exhibited positive correlations with water productivity, shoot dry matter, and yield, indicating that root morphological characteristics, particularly during the panicle initiation stage, enhanced rice production and water conservation. The findings demonstrate that biodegradable mulch film created favorable soil conditions for root proliferation, enabling higher yields in water-saving rice systems.

Despite the essential role of micronutrients in plant metabolic processes and carbon cycle, the mechanisms by which micronutrients regulate plant community traits remain poorly understood. Here, we used a long-term experiment to explore the potential mechanisms of plant community micronutrients and traits along a precipitation gradient. Our results showed that plants shifted toward lateral growth and asexual reproduction over time. From 1985 to 2022, the plant community Fe content increased by 18.8% in the north but declined by 25.2% in the south of the typical steppe. Furthermore, plant community growth and reproduction were sensitive to both micronutrient contents and uptake efficiencies in the north of the typical steppe. While plant community Mn and Zn contents enhanced growth longitudinally, Zn and Fe uptake efficiencies hindered sexual reproduction. Furthermore, soil moisture and GDP per capita were the key drivers of micronutrient variation in the north and south of the typical steppe, respectively. Precipitation fluctuations primarily regulated community traits across all sites. In the arid site, micronutrient-driven shifts in reproduction stabilized the soil carbon stock by balancing biomass allocation. These findings can help us to better understand the coupling of plant micronutrients, traits, and soil carbon stocks, thereby providing the basis for a scientific grassland conservation strategy under global change scenarios.

The timely and accurate assessment of soil nutrient information is essential for ensuring global food security and sustainable agricultural development. This study evaluated the individual and fusion performance of mid-infrared (MIR) and portable X-ray fluorescence (pXRF) spectroscopy for predicting selected soil properties. Four sensor fusion strategies were implemented: direct concatenation (DC), feature-level fusion using stability competitive adaptive reweighted sampling (sCARS) and least absolute shrinkage and selection operator (LASSO) algorithms (sCARS-C and LASSO-C), multi-block fusion viasequential orthogonal partial least squares (SO-PLS), and Granger-Ramanathan model averaging (GRA) method to enhance prediction accuracy for 13 soil properties. The findings revealed that single sensor models using either MIR or pXRF provided accurate estimations for soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), calcium (Ca), iron (Fe), manganese (Mn), and pH, but showed limitations for total potassium (TK), magnesium (Mg), copper (Cu), zinc (Zn), available potassium (AK), and total phosphorus (TP). The DC model significantly improved predictions for Mg (Rp²=0.76, RMSEp=358.76 mg kg^–1, RPDp=2.03) and TK (Rp²=0.75, RMSEp=775.96 mg kg^–1, RPDp=2.00). The LASSO-C model demonstrated superior prediction accuracy compared to the DC model for AP, AK, TP, Zn, Mn, and Cu, achieving optimal results for AP (Rp²=0.89, RMSEp=21.37 mg kg^–1, RPDp=3.01) and Zn (Rp²=0.80, RMSEp=9.88 mg kg^–1, RPDp=2.32). This enhancement is attributed to LASSO's effective selection of feature information from the complete MIR and pXRF spectra. The GRA models achieved the highest prediction accuracy for TP, pH, AK, and Cu, with Rp²values of 0.80, 0.82, 0.82, and 0.65, RMSEp values of 129.21 mg kg^–1, 0.13, 48.38 mg kg^–1, and 3.87 mg kg^–1, and RPDp values of 2.23, 2.34, 2.37, and 1.67, respectively. For single-sensor applications, MIR spectra are recommended for predicting SOM, TN, and Ca (Rp²≥0.88, RPDp≥2.87), while pXRF is more cost-effective for measuring Ca, Fe, and Mn (Rp²≥0.80, RPDp≥2.22). This research demonstrates the effectiveness of MIR and pXRF sensor fusion in enhancing soil nutrient assessment accuracy, particularly for available nutrients and micronutrients.

Soil organic matter (SOM) monitoring using remote sensing is critical for effective land resource management and environmental protection. Mapping SOM in areas where saline and black soils are intertwined, with complex soil types and significant environmental variability, remains a challenging task. This study integrated prior knowledge and classified Jilin Province, China, into saline-alkali and black soil areas. All available Sentinel-2 images from 2019 to 2023 during the bare soil period (April to July) were collected, and the images were categorized into three time windows: day of year (DOY) 90–120, DOY 120–150, and DOY 150–180. The potentials of these time windows, spectral indices (salinity index and vegetation moisture index), environmental variables (topography and climate), and local regression models for SOM mapping in the saline-black soil transition areas were then systematically evaluated. The results revealed four key findings: (1) the optimal time window for SOM mapping in both the saline-alkali area and black soil area was DOY 90–120; (2) including the salinity index improved SOM mapping accuracy in the saline-alkali area but reduced it in the black soil area, whereas the vegetation moisture index enhanced accuracy in both areas; (3) incorporating environmental variables improved the SOM mapping accuracy in all areas, with topographic variables being more influential in the black soil area and climatic variables being more significant in the saline-alkali area; and (4) local regression models based on the saline-alkali area and black soil area outperformed the global regression model in terms of SOM mapping accuracy, although they exhibited higher uncertainty. This study demonstrates that the integration of prior knowledge and multi-temporal remote sensing images significantly enhance SOM mapping accuracy in areas where saline and black soils intersect, thus providing a scientific foundation for the precise management and protection of areas with different soil types.

Agriculture is the foundation of socio-economic development and is highly influenced by weather and climate conditions. Drought is one of the most significant threats to agricultural development and food security. Currently, in-situ drought monitoring based on weather stations and based on remote sensing data has limitations, including infrequent updates, limited coverage, and low accuracy. This study leverages multi-source remote sensing data to monitor agricultural drought in Heilongjiang Province, China. We developed multi-source composite drought indices (MCDIs) at various timescales (3, 6, 9, and 12 months) by integrating precipitation, land surface temperature, soil moisture, and vegetation indices. Utilizing remote sensing data from various sources, we calculated a series of single drought indices, which are the precipitation condition index, soil moisture condition index, vegetation condition index, and temperature condition index. These are then integrated into MCDIs using a multivariable linear regression approach. The analysis reveals that MCDIs correlate more with standardized precipitation evapotranspiration index (SPEI) than single drought indices. When examining the correlation between different MCDIs and the affected area of crops and major grain production, MCDI-9 showed the highest correlation with the affected area of crops, while MCDI-12 showed the highest correlation with grain production. This suggests that these two MCDIs at different timescales are better indicators of agricultural drought. The spatio-temporal analysis of MCDI indicates that drought in Heilongjiang Province primarily occurs in early spring, gradually spreading from the Greater Khingan Mountains region to the southeastern plains. The drought gradually alleviates during the summer, ending by the autumn harvest period. Therefore, the MCDIs constructed in this study can serve as effective methods and indicators for drought monitoring in Heilongjiang Province and similar regions.