The wheat above-ground biomass (AGB) is an important index that shows the life activity of vegetation, which is of great significance for wheat growth monitoring and yield prediction.  Traditional biomass estimation methods specifically include sample surveys and harvesting statistics.  Although these methods have high estimation accuracy, they are time-consuming, destructive, and difficult to implement to monitor the biomass at a large scale.  The main objective of this study is to optimize the traditional remote sensing methods to estimate the wheat AGB based on improved convolutional features (CFs).  Low-cost unmanned aerial vehicles (UAV) were used as the main data acquisition equipment.  This study acquired RGB and multi-spectral (MS) image data of the wheat population canopy for two wheat varieties and five key growth stages.  Then, field measurements were conducted to obtain the actual wheat biomass data for validation.  Based on the remote sensing indices (RSIs), structural features (SFs), and convolutional features (CFs), this study proposed a new feature named AUR-50 (Multi-source combination based on convolutional feature optimization) to estimate the wheat AGB.  The results show that AUR-50 could more accurately estimate the wheat AGB than RSIs and SFs, and the average R² exceeded 0.77.  AUR-50_MS had the highest estimation accuracy (R² of 0.88) in the overwintering period.  In addition, AUR-50 reduced the effect of the vegetation index saturation on the biomass estimation accuracy by adding CFs, where the highest R² was 0.69 at the flowering stage.  The results of this study provide an effective method to evaluate the AGB in wheat with high throughput and a research reference for the phenotypic parameters of other crops.

Identification of the S genotype of Malus plants will greatly promote the discovery of new genes, the cultivation and production of apple, the breeding of new varieties, and the origin and evolution of self-incompatibility in Malus plants.  In this experiment, 88 Malus germplasm resources, such as Aihuahong, Xishuhaitang, and Reguanzi, were used as materials.  Seven gene-specific primer combinations were used in the genotype identification.  PCR amplification using leaf DNA produced a single S-RNase gene fragment in all materials.  The results revealed that 70 of the identified materials obtained a complete S-RNase genotype, while only one S-RNase gene was found in 18 of them.  Through homology comparison and analysis, 13 S-RNase genotypes were obtained: S₁S₂ (Aihuahong, etc.), S₁S₂₈ (Xixian Haitang, etc.), S₁S₅₁ (Hebei Pingdinghaitang), S₁S₃ (Xiangyangcun Daguo, etc.), S₂S₃ (Zhaiyehaitang, etc.), S₃S₅₁ (Xishan 1), S₃S₂₈ (Huangselihaerde, etc.), S₂S₂₈ (Honghaitang, etc.), S₄S₂₈ (Bo 11), S₇S₂₈ (Jiuquan Shaguo), S₁₀S_e (Dongchengguan 13), S₁₀S₂₁ (Dongxiangjiao) and S_eS₅₁ (Xiongyue Haitang).  Simultaneously, the frequency of the S gene in the tested materials was analyzed.  The findings revealed that different S genes had varying frequencies in Malus resources, as well as varying frequencies between intraspecific and interspecific.  S₃ had the highest frequency of 68.18%, followed by S₁ (42.04%).  In addition, the phylogenetic tree and origin evolution analysis revealed that the S gene differentiation was completed prior to the formation of various apple species, that cultivated species also evolved new S genes, and that the S₅₀ gene is the oldest S allele in Malus plants.  The S₁, S₂₉, and S₃₃ genes in apple-cultivated species, on the other hand, may have originated in M. sieversii, M. hupehensis, and M. kansuensis, respectively.  In addition to M. sieversii, M. kansuensis and M. sikkimensis may have also played a role in the origin and evolution of some Chinese apples.

Improving plant resistance to Verticillium wilt (VW), which causes massive losses in Gossypium hirsutum, is a global challenge.  Crop plants need to efficiently allocate their limited energy resources to maintain a balance between growth and defense.  However, few transcriptional regulators specifically respond to Verticillium dahliae and the underlying mechanism has not been identified in cotton.  In this study, we found that the that expression of most R2R3-MYB members in cotton is significantly changed by V. dahliae infection relative to the other MYB types.  One novel R2R3-MYB transcription factor (TF) that specifically responds to V. dahliae, GhMYB3D5, was identified.  GhMYB3D5 was not expressed in 15 cotton tissues under normal conditions, but it was dramatically induced by V. dahliae stress.  We functionally characterized its positive role and underlying mechanism in VW resistance.  Upon V. dahliae infection, the up-regulated GhMYB3D5 bound to the GhADH1 promoter and activated GhADH1 expression.  In addition, GhMYB3D5 physically interacted with GhADH1 and further enhanced the transcriptional activation of GhADH1.  Consequently, the transcriptional regulatory module GhMYB3D5-GhADH1 then promoted lignin accumulation by improving the transcriptional levels of genes related to lignin biosynthesis (GhPAL, GhC4H, Gh4CL, and GhPOD/GhLAC) in cotton, thereby enhancing cotton VW resistance.  Our results demonstrated that the GhMYB3D5 promotes defense-induced lignin accumulation, which can be regarded as an effective way to orchestrate plant immunity and growth. 

Skeletal muscle is composed of multinucleated muscle fibers, which play a crucial role in determining the quality of meat products in livestock. Quantifying the total number of muscle fibers (TNM) is essential for understanding muscle composition, yet remains challenging in poultry, particularly due to the size of the livestock that complicates the preparation of tissue sections for analysis and renders the counting process laborious. Our previous study developed an automatic muscle fiber quantification tool powered by deep learning, named MyoV, which has addressed this bottleneck. This study aimed to employ the tool for the accurate quantification of the TNM in the pectoral muscles of slow-growing (SL), medium-growing (ML), and fast-growing (FL) broilers. Results showed that FL exhibited higher growth performance compared to ML and SL from embryonic to rearing stages. Processing of whole slide images of pectoral muscle revealed significantly higher TNM in FL and ML than in SL (P < 0.01). The TNM of FL, ML and SL were 693,568.00 ± 54,169.80, 652,122.00 ± 65,822.60 and 539,778.57±40,722.94 at 7 days of age (D7), respectively. And the TNM at D35 were 663,014.93±58,801.11, 645,784.76±80,204.34 and 507,280.29±98,092.16 of FL, ML and SL. Differences in cross-sectional area (CSA) of muscle fibers among the three groups were consistent with TNM results. Correlation analysis showed a correlation coefficient of 0.73-0.89 between body weight (BW) and TNM and a correlation coefficient of 0.78-0.87 between BW and CSA. These findings directly indicate that the number of muscle fibers in broilers is an important foundation for their rapid growth and development. This study precisely quantifies the muscle fiber number of important skeletal muscle in poultry for the first time, providing the direct evidence for the physiological basis of rapid development in broilers and offering important data support for further in-depth researches on muscle fiber development.

Ketosis, a common metabolic disease during early lactation, is associated with high circulating levels of β-hydroxybutyrate (BHB). A portion of BHB that reaches the mammary gland is utilized as precursor for synthesis of fatty acids. Recent findings from nonruminant studies revealed that long chain fatty acyl-CoA ligase 4 (ACSL4) could play a role in the regulation of cellular fatty acid metabolism, but the mechanisms by which ACSL4 mediates cellular lipid metabolism in response to BHB remains unclear. To achieve the aims, we conducted in vivo or in vitro analyses using bovine mammary gland biopsies and the immortalized mammary epithelial cell line (MAC-T). The in vivo study (n = 6 cows group^-1) involved healthy cows (plasma BHB < 0.60 mmol L^-1) or ketotic cows (plasma BHB > 2.0 mmol L^-1) from which mammary gland tissue was biopsied. In vitro, MAC-T cells were challenged with 0, 0.3, 0.6, 1.2, or 2.4 mmol L^-1 BHB for 24 h to determine an optimal dose. Subsequently, MAC-T were incubated with 1.2 mmol L^-1 BHB for 0, 3, 6, 12, 24, or 48 h. Furthermore, MAC-T cells were treated with small interfering ACSL4 (siACSL4) for 24 h or ACSL4 overexpression plasmid (pcACSL4) for 36 h followed by a challenge with 1.2 mmol L^-1 BHB for 24 h. Results showed that increased mRNA and protein abundance of lipogenic genes were linked to both mammary gland and in vitro challenge with BHB. BHB increased fatty acid content by activating ACSL4 expression, whereas inhibition of ACSL4 reduced BHB-induced reactive oxygen species (ROS) overproduction, enhancement of mitochondrial membrane potential, increase in fatty acid content, and lipid droplet accumulation. Furthermore, we also elevated ACSL4 expression with an overexpression plasmid to clarify its molecular role in response to BHB challenge. ACSL4 overexpression enhances BHB-induced lipid droplet accumulation by increased fatty acid content. Overall, the information showed that ACSL4 is crucial for the process of producing fatty acids from exogenous BHB. Reduced ACSL4 decreased fatty acid content and lipid droplet accumulation, improved mitochondrial function, directed more fatty acids towards oxidation. Thus, ACSL4 plays an important role in determining the fate of intracellular fatty acids and BHB in BMECs.

Pepper fruit is highly favored for its spicy taste, diverse flavors, and high nutritional value. The proper development of its flower and fruit directly determines the quality of pepper fruit. The YABBY gene family exhibits diverse functions in growth and development, which is crucial to the identity of plant flower organs, but its specific role in pepper is still unclear. In this study, nine CaYABBY genes were identified and characterized in pepper. Most CaYABBY genes were highly expressed in reproductive organs, albeit with varying patterns of expression. The CaYABBY5 gene, uniquely expressed in petals and carpels, has been demonstrated to modulate floral organ determinacy and fruit shape through gene silencing in pepper and ectopic expression in tomato. Protein interaction analysis revealed an interacting protein SEPALLATA3-like protein (SEP3), exhibiting a similar expression profile to that of CaYABBY5. These findings suggest that CaYABBY5 may modulate the morphogenesis of floral organs and fruits by interacting with CaSEP3. This study provided valuable insights into the classification and function of CaYABBY genes in pepper.

Intervention strategies to control non-point source nitrogen (N) and phosphorus (P) pollution in agriculture are expensive and there is a trade-off between engineering cost and treatment effectiveness. Implementing strategies often result in unsatisfactory outcomes and massive engineering costs when managing diffusive pollution in agricultural catchments. To address this issue, this paper proposes a robust, handy, catchment N & P decision support system (CNPDSS), an Android-based smartphone system integrated with a web-based Geographic Information System (GIS). The CNPDSS aims to provide artificial intelligence-driven decisions that minimize N & P loadings and engineering costs for mitigating pollution in agricultural catchments. It consists of four components: a general user interface (GUI), GIS, N & P pollution modeling (NPPM), and a DSS. The CNPDSS simplifies the GUI and integrates GIS modules to create a user-friendly interface, enabling non-professional users to operate the system easily through intuitive actions. The NPPM uses straightforward empirical models to predict N & P loadings, enhancing efficiency by avoiding excessive parameters. Taking into account the N & P movement pathway in the catchment, the DSS incorporates three control measures: source reduction in farmland (before migration stage), process retention by ecological ditch (midway transport stage), and down-end purification by constructed wetland (waterbody discharge stage), to formulate a comprehensive ternary controlling strategy. To optimize the cost-effectiveness of any proposed N & P control strategies for sub-catchments, a differential evolution algorithm (DEA) is employed in CNPDSS to carry out a dual-objective decision-making optimization computation. In this study, the CNPDSS is applied to a case study in an agricultural catchment in central China to develop the most cost-effective ternary N & P control strategies that ensure the catchment water quality within Criterion III of the Chinese Surface Water Quality Standard GB3838-2002 is met (total N concentration≤1.0 mg L⁻¹ and total P concentration≤0.2 mg L⁻¹). Our results demonstrate that the CNPDSS is feasible and also possesses an adaptive design and flexible architecture to enable its generalization and extension to support strong hands-on applications in other catchments.