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Recording growth stage information is an important aspect of precision agriculture, crop breeding and phenotyping. In practice, crop growth stage is still primarily monitored by-eye, which is not only laborious and time-consuming, but also subjective and error-prone. The application of computer vision on digital images offers a high-throughput and non-invasive alternative to manual observations and its use in agriculture and high-throughput phenotyping is increasing. This paper presents an automated method to detect wheat heading and flowering stages, which uses the application of computer vision on digital images. The bag-of-visual-word technique is used to identify the growth stage during heading and flowering within digital images. Scale invariant feature transformation feature extraction technique is used for lower level feature extraction; subsequently, local linear constraint coding and spatial pyramid matching are developed in the mid-level representation stage. At the end, support vector machine classification is used to train and test the data samples. The method outperformed existing algorithms, having yielded 95.24, 97.79, 99.59% at early, medium and late stages of heading, respectively and 85.45% accuracy for flowering detection. The results also illustrate that the proposed method is robust enough to handle complex environmental changes (illumination, occlusion). Although the proposed method is applied only on identifying growth stage in wheat, there is potential for application to other crops and categorization concepts, such as disease classification.

An attempt was made in the current study to identify the main-effect and co-localized quantitative trait loci (QTLs) for germination and early seedling growth traits under low-temperature stress (LTS) conditions in rice. The plant material used in this study was an early backcross population of 230 introgression lines (ILs) in BC I F 7 generation derived from the Weed Tolerant Rice-1 (WTR-1) (as the recipient) and Haoannong (HNG) (as the donor). Genetic analyses of LTS tolerance revealed a total of 27 main-effect quantitative trait loci (M-QTLs) mapped on 12 chromosomes. These QTLs explained more than 10% of phenotypic variance (PV), and average PV of 12.71% while employing 704 high-quality SNP markers. Of these 27 QTLs distributed on 12 chromosomes, 11 were associated with low-temperature germination (LTG), nine with low-temperature germination stress index (LTGS), five with root length stress index (RLSI), and two with biomass stress index (BMSI) QTLs, shoot length stress index (SLSI) and root length stress index (RLSI), seven with seed vigor index (SVI), and single QTL with root length (RL). Among them, five significant major QTLs ( qLTG(I) 1 , qLTGS(I) 1–2 , qLTG(I) 5 , qLTGS(I) 5 , and qLTG(I) 7 ) mapped on chromosomes 1, 5, and 7 were associated with LTG and LTGS traits and the PV explained ranged from 16 to 23.3%. The genomic regions of these QTLs were co-localized with two to six QTLs. Most of the QTLs were growth stage-specific and found to harbor QTLs governing multiple traits. Eight chromosomes had more than four QTLs and were clustered together and designated as promising LTS tolerance QTLs ( qLTTs ), as qLTT 1 , qLTT 2 , qLTT 3 , qLTT 5 , qLTT 6 , qLTT 8 , qLTT 9 , and qLTT 11 . A total of 16 putative candidate genes were identified in the major M-QTLs and co-localized QTL regions distributed on different chromosomes. Overall, these significant genomic regions of M-QTLs are responsible for multiple traits and this suggested that these could serve as the best predictors of LTS tolerance at germination and early seedling growth stages. Furthermore, it is necessary to fine-map these regions and to find functional markers for marker-assisted selection in rice breeding programs for cold tolerance.

Background and Aims Epichloë endophytes are a unique model system for the study of the linkages between organisms above and belowground in ecosystems. However, the impact of Epichloë gansuensis in Achnatherum inebrians on soil enzymes activity and soil nutrients remains poorly understood. Methods Achnatherum inebrians with (E+) and without E. gansuensis (E−) were established in different plots of an experimental field in 2011. At 2016, the activity of soil invertase, soil urease, soil alkaline phosphatase and the soil nutrient of E+ and E− plots was determined in the A. inebrians growth and senescent stages; further, we used NMDS to evaluate the roles of endophyte and growth phase for each sample with soil properties. Results The interaction of E. gansuensis -infection and growth phase significantly influences TN and AN. E. gansuensis enhanced the activity of soil invertase and soil alkaline phosphatase in growth and senescence stages of A. inebrians , E. gansuensis increased the activity of urease in the growth stage. E. gansuensis significantly increased the content of soil TN and AN in the A. inebrians growth stage. The results of NMDS showed that E. gansuensis and growth phase significantly influenced the soil properties, respectively. Therefore, E. gansuensis played an important role in improving soil enzymes activity and soil nutrients content. Conclusions E. gansuensis improve soil fertility through regulating soil enzymes activity and soil nutrients. This study provided insights into a poorly understood ecosystem function of Epichloë and enhanced knowledge of the benefits provided by these mutualistic fungal endophytes of many grass species.

Main conclusionThis is the first report on the involvement of abscisic acid signaling in regulating post-germination growth under Cs stress, not related to potassium deficiency.Cesium (Cs) is known to exert toxicity in plants by competition and interference with the transport of potassium (K). However, the precise mechanism of how Cs mediates its damaging effect is still unclear. This fact is mainly attributed to the large effects of lower K uptake in the presence of Cs that shadow other crucial effects by Cs that were not related to K. RNA-seq was conducted on Arabidopsis roots grown to identify putative genes that are functionally involved to investigate the difference between Cs stress and low K stress. Our transcriptome data demonstrated Cs-regulated genes only partially overlap to low K-regulated genes. In addition, the divergent expression trend of High-affinity K+Transporter (HAK5) from D4 to D7 growth stage suggested participation of other molecular events besides low K uptake under Cs stress. Potassium deficiency triggers expression level change of the extracellular matrix, transfer/carrier, cell adhesion, calcium-binding, and DNA metabolism genes. Under Cs stress, genes encoding translational proteins, chromatin regulatory proteins, membrane trafficking proteins and defense immunity proteins were found to be primarily regulated. Pathway enrichment and protein network analyses of transcriptome data exhibit that Cs availability are associated with alteration of abscisic acid (ABA) signaling, photosynthesis activities and nitrogen metabolism. The phenotype response of ABA signaling mutants supported the observation and revealed Cs inhibition of root growth involved in ABA signaling pathway. The rather contrary response of loss-of-function mutant of Late Embryogenesis Abundant 7 (LEA7) and Translocator Protein (TSPO) further suggested low K stress and Cs stress may activate different salt tolerance responses. Further investigation on the crosstalk between K transport, signaling, and salt stress-responsive signal transduction will provide a deeper understanding of the mechanisms and molecular regulation underlying Cs toxicity.

Background Mammalian skin exhibits profound cellular and molecular restructuring across lifespan, yet an integrated single-cell mapping from embryogenesis to senescence remains limited. The Chenghua (CH) pig, with exceptional skin thickness characteristics, provides a promising model for investigating human skin development and physiology. Results We constructed a comprehensive single-cell RNA atlas of 443,529 cells from CH pig skin spanning 10 developmental stages (embryonic day 56 to postnatally year 7). Our analysis identified eight major skin cell types and revealed stage-specific shifts in cellular composition. Fibroblasts (FBs) and mesenchymal stem cells (MSCs) dominated embryonic development while smooth muscle cells and endothelial cells increased postnatally, with aging marked by FB dysfunction and significant dermal thinning. Pseudotime trajectory analysis identified that FBs differentiated from a common progenitor with MSCs, diverging into five functionally distinct subpopulations including papillary, reticular, mesenchymal, pro-inflammatory, and a novel AUTS2⁺ subtype with neuromodulatory roles. Critically, FBs regulated postnatal skin aging via COL1A1-(ITGA1 + ITGB1) and MDK-SDC1 interaction signaling pathways, with the transcription factor EGR1 regulating collagen-related genes ( DPT , COL12A1 , COL5A2 ) during development; the age-dependent suppression of FBs coincided with collagen downregulation, reduced intercellular communication, and elevated transcriptional noise. Concurrently, immune cells including dendritic cells (DCs) and T cells (TCs) exhibited a marked decrease of cell numbers perinatally, with cytotoxic NKT cells reaching peak abundance at rapid growth stage; DCs and TCs primarily utilized SPP1 and TGF-β signaling pathways to regulate skin immunity during development and aging. Cross-species analysis confirmed the evolutionary conservation of skin cell types and FB functional gene profiles related to ECM deposition and inflammatory responses across pigs, humans, and mice during development and aging. Conclusions This work delineates cellular dynamics underpinning skin homeostasis, uncovers the vital physiological functions of FBs and immune cells during skin development and aging, and validates the pig model for human cutaneous physiology research. The atlas serves as a pivotal resource for skin mechanistic and translational studies.

PurposeSilicon (Si) accumulation is an important strategy for plant defense against biotic and abiotic stress. Solid amorphous silica (ASi) deposits have been found to protect plants against different stressors (e.g., drought stress, ultraviolet radiation, herbivory, and pests). Most research on ASi deposits and their subsequent function is conducted under lab conditions. However, it is still unclear at which stage in ontogeny ASi deposits are developed to fulfill their function in plant protection under field conditions.MethodsWe combined SEM–EDX, NMR spectroscopy, and Si extractions to analyze silicification patterns in wheat leaves (blades and sheaths) in relation to ontogeny and soil Si availability.ResultsSilicification patterns in wheat leaves varied strongly in intensity between four different growth stages (tillering, stem extension, heading, and grain filling) and ASi deposition did not just continuously increase over the growing season. Newly formed leaf tissues showed relatively low Si concentrations, which increased over time. A high condensation state of the silica bodies and trichomes was found at all growth stages, referring to a high rigidity of the silica bodies.ConclusionsOur results indicate that development of ASi deposits in wheat leaves depends on growth stage and Si availability. Detailed knowledge on solid ASi deposition in wheat during ontogeny and its consequences for stress mitigation is crucial for farmers worldwide.

Geyer larkspur is a native perennial forb that is toxic to cattle. Herbicide control of Geyer larkspur is variable and depends on the growth stage of the plant when the herbicide is applied. The objectives of this study were to 1) evaluate aminopyralid, aminopyralid + florpyrauxifen-benzyl, aminopyralid + 2,4-D, aminopyralid + metsulfuron-methyl, metsulfuron-methyl, triclopyr, and triclopyr + 2,4-D for efficacy in controlling Geyer larkspur; 2) determine whether plant growth stage (vegetative or flowering) at the time of herbicide application influences herbicide effectiveness; and 3) determine whether herbicide treatment alters the norditerpenoid alkaloid content of Geyer larkspur. Plots were established in eastern Wyoming in 2021 and northern Colorado in 2022. Herbicide application at the different phenological stages did not affect Geyer larkspur density at the Wyoming site (P = 0.1065; data not shown). Geyer larkspur density at the Wyoming site was reduced by all herbicide treatments 1 yr after treatment (YAT) at the vegetative stage and by all herbicides except triclopyr 2 YAT (P = 0.0249). Geyer larkspur density at the flowering stage was reduced by all herbicides except metsulfuron-methyl, triclopyr, and triclopyr + 2,4-D at 1 YAT and by triclopyr and triclopyr + 2,4-D at 2 YAT. In contrast, there were no differences in Geyer larkspur density across treatments at the Colorado site (P = 0.9621). Precipitation was below average several months prior to herbicide application, which may have affected herbicide effectiveness. The metsulfuron-methyl treatment resulted in the highest total alkaloid concentrations of Geyer larkspur at the vegetative stage and the lowest concentrations at the flowering stage at the Wyoming site. Efforts to control Geyer larkspur in semiarid rangelands can be effectively accomplished by applying aminopyralid herbicides at either the vegetative or flowering growth stage provided environmental conditions prior to herbicide application are sufficient for plant growth and uptake of the herbicide.

This study investigated the impact of sow microbiota and developmental stages on the gut microbiome of pigs throughout their life cycle. Fecal samples using rectal swab from 30 sows and 179 piglets were collected on days 5, 35, 80, and 145. A dynamic shift in the gut microbiota was observed as the pigs progressed through different growth stages. Maternal fecal microbiota influenced the piglets’ microbiota, with higher transfer rates of Escherichia-Shigella , Bacteroides , and Fusobacterium . Notably, our findings revealed that not only Bacteroides , a genus essential for breast milk digestion, but also Escherichia-Shigella and Fusobacterium , previously regarded as and assumed to be of environmental origin, in fact originated from the sow. Correlation analysis between bacterial genera and metabolic functional pathways revealed that heme biosynthesis, crucial for pregnancy maintenance, was predicted to increase in postpartum sows and was significantly associated with the presence of Acinetobacter and Campylobacter . Furthermore, potentially beneficial genera such as Butyricicoccus , Parabacteroides , Ruminiclostridium , Ruminococcus , Blautia , Prevotella , Alloprevotella , and Eubacterium were significantly correlated with energy metabolism pathways in pigs during the growing period. This study emphasizes the importance of analyzing microbial functions and networks beyond abundance alone, highlighting the potential of computational microbiome analysis to guide swine health and productivity strategies.

Background The accurate estimation of potato yield at regional scales is crucial for food security, precision agriculture, and agricultural sustainable development. Methods In this study, we developed a new method using multi-period relative vegetation indices (rVIs) and relative leaf area index (rLAI) data to improve the accuracy of potato yield estimation based on the weighted growth stage. Two experiments of field and greenhouse (water and nitrogen fertilizer experiments) in 2018 were performed to obtain the spectra and LAI data of the whole growth stage of potato. Then the weighted growth stage was determined by three weighting methods (improved analytic hierarchy process method, IAHP; entropy weight method, EW; and optimal combination weighting method, OCW) and the Slogistic model. A comparison of the estimation performance of rVI-based and rLAI-based models with a single and weighted stage was completed. Results The results showed that among the six test rVIs, the relative red edge chlorophyll index (rCI red edge ) was the optimal index of the single-stage estimation models with the correlation with potato yield. The most suitable single stage for potato yield estimation was the tuber expansion stage. For weighted growth stage models, the OCW-LAI model was determined as the best one to accurately predict the potato yield with an adjusted R 2 value of 0.8333, and the estimation error about 8%. Conclusion This study emphasizes the importance of inconsistent contributions of multi-period or different types of data to the results when they are used together, and the weights need to be considered.

Invasive alien species have environmental, economic and social impacts, disproportionally threatening livelihood and food security of smallholder farmers in low- and medium-income countries. Fall armyworm (FAW) ( Spodoptera frugiperda ), an invasive insect pest from the Americas, causes considerable losses on maize to smallholder farmers in Africa since 2016. The increased use of pesticides to control FAW in Africa raises concerns for health and environmental risks resulting in a growing interest in research on biological control options for smallholder farmers. In order to evaluate the occurrence of local natural enemies attacking FAW, we collected on a weekly basis FAW eggs and larvae during a maize crop cycle in the rainy season of 2018–2019 at four locations in the Lusaka and Central provinces in Zambia. A total of 4373 larvae and 162 egg masses were collected. For each location and date of collection, crop stage, the number of plants checked and amount of damage were recorded to analyse which factors best explain the occurrence of the natural enemy species on maize. Overall parasitism rates from local natural enemies at each location varied between 8.45% and 33.11%. We identified 12 different egg-larval, larval and larval-pupal parasitoid species. Location, maize growth stage, pest density and larval stage significantly affected parasitoid species occurrence. Our findings indicate that there is potential for increasing local populations of natural enemies of FAW through conservation biological control programmes and develop safe and practical control methods for smallholder farmers.