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Household kitchen waste (HKW) is produced in large quantity and its management is difficult due to high moisture content and complex organic matter. Aerobic composting of HKW is an easy, efficient, cost-effective and eco-friendly method. This study is designed to achieve a zero-waste concept and to convert HKW. We optimized the type and size of three different bulking agents to speed up the composting process. The tested bulking agents were fallen leaves, sawdust and fly ash. The results showed a higher and longer thermophilic phase (55oC) for 11 days in C2. Higher moisture content (69%) and higher organic matter degradation (38.4%) were also observed in C2. The pH range in all compost treatments was 7-8.5, Electrical conductivity range was 1.8-3.55 mS/cm, C/N ratio range was 15.4-18.1, water holding capacity range was 3.25-4.3 g water/g dry sample, total potassium range was 1.52-1.61%, total phosphorous range was 0.83-1.14%. The highest germination index (119.1%) was also obtained in C2. The highest chili height (16.7 cm), greater number of leaves (20), greater shoot fresh weight (4.75 g) and root fresh weight (1.2 g) was obtained in the presence of C2. Similarly, greater water WHC (2.8 g water/g DW), higher porosity (55.49%) and higher aggregate stability (54.14%) of soil was also obtained by C2. This research effectively reduced the maturation time to 32 days and converted kitchen waste into compost (resource). This is a very practical idea for home composting and kitchen gardening to combat food security issues in developing countries.

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.ImportanceBioenergy crops provide an important strategy for mitigating climate change. Reducing the lignin in bioenergy crops could improve fermentable sugar yields for more efficient conversion into bioenergy and bioproducts. In this study, we assessed how switchgrass engineered for low lignin impacted aboveground and belowground switchgrass microbiome. Our results show unexpected reductions in mycorrhizas and actinobacteria in belowground tissues, raising questions on the resilience and function of genetically engineered plants in agricultural systems.

Compound soil drought and heat extremes are expected to occur more frequently with global warming, causing wide-ranging socio-ecological repercussions. Vegetation modulates air temperature and soil moisture through biophysical processes, thereby influencing the occurrence of such extremes. Global vegetation cover is broadly expected to increase under climate change, but it remains unclear whether vegetation greening will alleviate or aggravate future increases in compound soil drought-heat events. Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12-21% of the total increment at the end of 21st century. This increase is predominantly driven by reduced albedo and enhanced transpiration associated with increased leaf area. Although greening-induced transpiration enhancement has counteracting cooling and drying effects, the excessive water loss in the early growing season can lead to later soil moisture deficits, amplifying compound soil drought-heat extremes during the subsequent warm season. These changes are most pronounced in northern high latitudes and are dominated by the warming effect of CO2. Our study highlights the necessity of integrating vegetation biophysical effects into mitigation and adaptation strategies for addressing compound climate risks.

Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (Amax,2,000) and growth temperature ( Tair¯ ) across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites. We detect widespread thermal acclimation of canopy-scale photosynthesis, demonstrated by enhanced Amax,2,000 under higher Tair¯ , across flux sites with adequate water availability. A 14-day period is identified as the most relevant timescale for acclimation across all sites, with a range of 12-25 days for different plant functional types. The mean apparent thermal acclimation rate across all ecosystems is 0.41 (-0.38-1.04 for 5th-95th percentile range) µmol m-2 s-1 °C-1, with croplands showing the largest acclimation rates and grasslands the lowest. Incorporating an optimality-based prediction of leaf photosynthetic capacities into a biochemical photosynthesis model is shown to improve the representation of thermal acclimation. Our results underscore the critical need for enhanced understanding and modelling of canopy-scale photosynthetic capacity to accurately predict plant responses to warmer growing seasons.

The genetic control of many plant traits can be highly complex. Both allelic variation (sequence change) and dosage variation (copy number change) contribute to a plants phenotype. While numerous studies have investigated the effect of allelic or dosage variation, very few have documented both within the same system, leaving their relative contribution to phenotypic effects unclear. The Populus genome is highly polymorphic, and poplars are fairly tolerant of gene dosage variation. Here, using a previously established Populus hybrid F1 population, we assessed and compared the effect of natural allelic variation and induced dosage variation on biomass, phenology, and leaf morphology traits. We identified QTLs for many of these traits, but our results indicate limited overlap between the QTLs associated with natural allelic variation and induced dosage variation. Additionally, the integration of data from both allelic and dosage variation identifies a larger set of QTLs that together explain a larger percentage of the phenotypic variance. Finally, our results suggest that the effect of the large indels might mask that of allelic QTLs. Our study helps clarify the relationship between allelic and dosage variation and their effects on quantitative traits.

Increasing heatwaves are threatening forest ecosystems globally. Leaf thermal regulation and tolerance are important for plant survival during heatwaves, though the interaction between these processes and water availability is unclear. Genotypes of the widely distributed foundation tree species Populus fremontii were studied in a controlled common garden during a record summer heatwave-where air temperature exceeded 48 °C. When water was not limiting, all genotypes cooled leaves 2 to 5 °C below air temperatures. Homeothermic cooling was disrupted for weeks following a 72-h reduction in soil water, resulting in leaf temperatures rising 3 °C above air temperature and 1.3 °C above leaf thresholds for physiological damage, despite the water stress having little effect on leaf water potentials. Tradeoffs between leaf thermal safety and hydraulic safety emerged but, regardless of water use strategy, all genotypes experienced significant leaf mortality following water stress. Genotypes from warmer climates showed greater leaf cooling and less leaf mortality after water stress in comparison with genotypes from cooler climates. These results illustrate how brief soil water limitation disrupts leaf thermal regulation and potentially compromises plant survival during extreme heatwaves, thus providing insight into future scenarios in which ecosystems will be challenged with extreme heat and unreliable soil water access.

Improving photosynthesis, the fundamental process by which plants convert light energy into chemical energy, is a key area of research with great potential for enhancing sustainable agricultural productivity and addressing global food security challenges. This perspective delves into the latest advancements and approaches aimed at optimizing photosynthetic efficiency. Our discussion encompasses the entire process, beginning with light harvesting and its regulation and progressing through the bottleneck of electron transfer. We then delve into the carbon reactions of photosynthesis, focusing on strategies targeting the enzymes of the Calvin-Benson-Bassham (CBB) cycle. Additionally, we explore methods to increase carbon dioxide (CO2) concentration near the Rubisco, the enzyme responsible for the first step of CBB cycle, drawing inspiration from various photosynthetic organisms, and conclude this section by examining ways to enhance CO2 delivery into leaves. Moving beyond individual processes, we discuss two approaches to identifying key targets for photosynthesis improvement: systems modeling and the study of natural variation. Finally, we revisit some of the strategies mentioned above to provide a holistic view of the improvements, analyzing their impact on nitrogen use efficiency and on canopy photosynthesis.

Zymoseptoria tritici is the most economically significant fungal pathogen of wheat in Europe. However, despite the importance of this pathogen, the molecular interactions between pathogen and host during infection are not well understood. Herein, we describe the use of two libraries of cloned Z. tritici effectors that were screened to identify effector candidates with putative pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI)-suppressing activity. The effectors from each library were transiently expressed in Nicotiana benthamiana, and expressing leaves were treated with bacterial or fungal PAMPs to assess the effectors ability to suppress reactive oxygen species (ROS) production. From these screens, numerous effectors were identified with PTI-suppressing activity. In addition, some effectors were able to suppress cell death responses induced by other Z. tritici secreted proteins. We used structural prediction tools to predict the putative structures of all of the Z. tritici effectors and used these predictions to examine whether there was enrichment of specific structural signatures among the PTI-suppressing effectors. From among the libraries, multiple members of the killer protein-like 4 (KP4) and killer protein-like 6 (KP6) effector families were identified as PTI suppressors. This observation is intriguing, as these protein families were previously associated with antimicrobial activity rather than virulence or host manipulation. This data provides mechanistic insight into immune suppression by Z. tritici during infection and suggests that, similar to biotrophic pathogens, this fungus relies on a battery of secreted effectors to suppress host immunity during early phases of colonization.

Forecasting plant responses under global change is a critical but challenging endeavour. Despite seemingly idiosyncratic responses of species to global change, greater generalisation of 'winners' and 'losers' may emerge from considering how species functional traits influence responses and how these responses scale to the community level. Here, we synthesised six long-term global change experiments combined with locally measured functional traits. We quantified the change in abundance and probability of establishment through time for 70 alpine plant species and then assessed if leaf and stature traits were predictive of species and community responses across nitrogen addition, snow addition and warming treatments. Overall, we found that plants with more resource-acquisitive trait strategies increased in abundance but each global change factor was related to different functional strategies. Nitrogen addition favoured species with lower leaf nitrogen, snow addition favoured species with cheaply constructed leaves and warming showed few consistent trends. Community-weighted mean changes in trait values in response to nitrogen addition, snow addition and warming were often different from species-specific trait effects on abundance and establishment, reflecting in part the responses and traits of dominant species. Together, these results highlight that the effects of traits can differ by scale and response of interest.

Plants are colonized by distinct pathogenic and commensal microbiomes across different regions of the globe, but the factors driving their geographic variation are largely unknown. Here, using 16S ribosomal DNA and shotgun sequencing, we characterized the associations of the Arabidopsis thaliana leaf microbiome with host genetics and climate variables from 267 populations in the species native range across Europe. Comparing the distribution of the 575 major bacterial amplicon variants (phylotypes), we discovered that microbiome composition in A. thaliana segregates along a latitudinal gradient. The latitudinal clines in microbiome composition are predicted by metrics of drought, but also by the spatial genetics of the host. To validate the relative effects of drought and host genotype we conducted a common garden field study, finding 10% of the core bacteria to be affected directly by drought and 20% to be affected by host genetic associations with drought. These data provide a valuable resource for the plant microbiome field, with the identified associations suggesting that drought can directly and indirectly shape genetic variation in A. thaliana via the leaf microbiome.

With the anticipated foliar application of nanoparticles (NPs) as a potential strategy to improve crop production and ameliorate heavy metal toxicity, it is crucial to evaluate the role of NPs in improving the nutrient content of plants under Lead (Pb) stress for achieving higher agriculture productivity to ensure food security. Herein, Brassica napus L. grown under Pb contaminated soil (300 mg/kg) was sprayed with different rates (0, 25, 50, and 100 mg/L) of TiO2 and ZnO-NPs. The plants were evaluated for growth attributes, photosynthetic pigments, leaf exchange attributes, oxidant and antioxidant enzyme activities. The results revealed that 100 mg/L NPs foliar application significantly augmented plant growth, photosynthetic pigments, and leaf gas exchange attributes. Furthermore, 100 mg/L TiO2 and ZnO-NPs application showed a maximum increase in SPAD values (79.1%, 68.9%). NPs foliar application (100 mg/L TiO2 and ZnO-NPs) also substantially reduced malondialdehyde (44.3%, 38.3%), hydrogen peroxide (59.9%, 53.1%), electrolyte leakage (74.8%, 68.3%), and increased peroxidase (93.8%, 89.1%), catalase (91.3%, 84.1%), superoxide dismutase (81.8%, 73.5%) and ascorbate peroxidase (78.5%, 73.7%) thereby reducing Pb accumulation. NPs foliar application (100 mg/L) significantly reduced root Pb (45.7%, 42.3%) and shoot Pb (84.1%, 76.7%) concentration in TiO2 and ZnO-NPs respectively, as compared to control. Importantly, macro and micronutrient analysis showed that foliar application 100 mg/L TiO2 and ZnO-NPs increased shoot zinc (58.4%, 78.7%) iron (79.3%, 89.9%), manganese (62.8%, 68.6%), magnesium (72.1%, 93.7%), calcium (58.2%, 69.9%) and potassium (81.5%, 68.6%) when compared to control without NPs. The same trend was observed for root nutrient concentration. In conclusion, we found that the TiO2 and ZnO-NPs have the greatest efficiency at 100 mg/L concentration to alleviate Pb induced toxicity on growth, photosynthesis, and nutrient content of Brassica napus L. NPs foliar application is a promising strategy to ensure sustainable agriculture and food safety under metal contamination.

Huanglongbing (HLB) is a fatal citrus disease that is currently threatening citrus varieties worldwide. One putative causative agent, Candidatus Liberibacter asiaticus (CLas), is vectored by Diaphorina citri, known as the Asian citrus psyllid (ACP). Understanding the details of CLas infection in HLB disease has been hindered by its Candidatus nature and the inability to confidently detect it in diseased trees during the asymptomatic stage. To identify early changes in citrus metabolism in response to inoculation of CLas using its natural psyllid vector, leaves from Madam Vinous sweet orange (Citrus sinensis (L.) Osbeck) trees were exposed to CLas-positive ACP or CLas-negative ACP and longitudinally analyzed using transcriptomics (RNA sequencing), proteomics (liquid chromatography-tandem mass spectrometry; data available in Dryad: 10.25338/B83H1Z), and metabolomics (proton nuclear magnetic resonance). At 4 weeks postexposure (wpe) to psyllids, the initial HLB plant response was primarily to the ACP and, to a lesser extent, the presence or absence of CLas. Additionally, analysis of 4, 8, 12, and 16 wpe identified 17 genes and one protein as consistently differentially expressed between leaves exposed to CLas-positive ACP versus CLas-negative ACP. This study informs identification of early detection molecular targets and contributes to a broader understanding of vector-transmitted plant pathogen interactions.

Leaf litter microbes collectively degrade plant polysaccharides, influencing land-atmosphere carbon exchange. An open question is how substrate complexity-defined as the structure of the saccharide and the amount of external processing by extracellular enzymes-influences species interactions. We tested the hypothesis that monosaccharides (i.e. xylose) promote negative interactions through resource competition, and polysaccharides (i.e. xylan) promote neutral or positive interactions through resource partitioning or synergism among extracellular enzymes. We assembled a three-species community of leaf litter-degrading bacteria isolated from a grassland site in Southern California. In the polysaccharide xylan, pairs of species stably coexisted and grew equally in coculture and in monoculture. Conversely, in the monosaccharide xylose, competitive exclusion and negative interactions prevailed. These pairwise dynamics remained consistent in a three-species community: all three species coexisted in xylan, while only two species coexisted in xylose, with one species capable of using peptone. A mathematical model showed that in xylose these dynamics could be explained by resource competition. Instead, the model could not predict the coexistence patterns in xylan, suggesting other interactions exist during biopolymer degradation. Overall, our study shows that substrate complexity influences species interactions and patterns of coexistence in a synthetic microbial community of leaf litter degraders.

Background and aimsMany agricultural areas are expected to face hotter, drier conditions from climate change. Understanding the mechanisms that crops use to mitigate these stresses can guide breeding for more tolerant plant material. We tested relationships between traits, physiological function in hot conditions and historical climate associations to evaluate these mechanisms for winegrapes. We expected a more negative leaf osmotic potential at full hydration (πo), which reduces leaf turgor loss during drought, and either a metabolically cheaper or more osmoprotectant leaf chemical composition, to allow cultivars associated with hot, dry regions to maintain greater gas exchange in hot growing conditions.MethodsWe measured πo, gas exchange and leaf chemistry for seven commercially important winegrape cultivars that vary widely in historical climate associations. Vines were grown in common-garden field conditions in a hot wine-growing region (Davis, CA, USA) and measured over the hottest period of the growing season (July-September).Key resultsThe value of πo varied significantly between cultivars, and all cultivars significantly reduced πo (osmotically adjusted) over the study period, although osmotic adjustment did not vary across cultivars. The value of πo was correlated with gas exchange and climate associations, but in the direction opposite to expected. Photosynthesis and πo were higher in the cultivars associated with hotter, less humid regions. Leaf chemical composition varied between cultivars but was not related to climate associations.ConclusionsThese findings suggest that maintenance of leaf turgor is not a primary limitation on grapevine adaptation to hot or atmospherically dry growing conditions. Thus, selecting for a more negative πo or greater osmotic adjustment is not a promising strategy to develop more climate-resilient grape varieties, contrary to findings for other crops. Future work is needed to identify the mechanisms increasing photosynthesis in the cultivars associated with hot, dry regions.

Soil salinity is a major nutritional challenge with poor agriculture production characterized by high sodium (Na+) ions in the soil. Zinc oxide nanoparticles (ZnO NPs) and biochar have received attention as a sustainable strategy to reduce biotic and abiotic stress. However, there is a lack of information regarding the incorporation of ZnO NPs with biochar to ameliorate the salinity stress (0, 50,100 mM). Therefore, the current study aimed to investigate the potentials of ZnO NPs application (priming and foliar) alone and with a combination of biochar on the growth and nutrient availability of spinach plants under salinity stress. Results demonstrated that salinity stress at a higher rate (100 mM) showed maximum growth retardation by inducing oxidative stress, resulted in reduced photosynthetic rate and nutrient availability. ZnO NPs (priming and foliar) alone enhanced growth, chlorophyll contents and gas exchange parameters by improving the antioxidant enzymes activity of spinach under salinity stress. While, a significant and more pronounced effect was observed at combined treatments of ZnO NPs with biochar amendment. More importantly, ZnO NPs foliar application with biochar significantly reduced the Na+ contents in root 57.69%, and leaves 61.27% of spinach as compared to the respective control. Furthermore, higher nutrient contents were also found at the combined treatment of ZnO NPs foliar application with biochar. Overall, ZnO NPs combined application with biochar proved to be an efficient and sustainable strategy to alleviate salinity stress and improve crop nutritional quality under salinity stress. We inferred that ZnO NPs foliar application with a combination of biochar is more effectual in improving crop nutritional status and salinity mitigation than priming treatments with a combination of biochar.

Synthetic promoters may be designed using short cis-regulatory elements (CREs) and core promoter sequences for specific purposes. We identified novel conserved DNA motifs from the promoter sequences of leaf palisade and vascular cell type-specific expressed genes in water-deficit stressed poplar (Populus tremula × Populus alba), collected through low-input RNA-seq analysis using laser capture microdissection. Hexamerized sequences of four conserved 20-base motifs were inserted into each synthetic promoter construct. Two of these synthetic promoters (Syn2 and Syn3) induced GFP in transformed poplar mesophyll protoplasts incubated in 0.5 M mannitol solution. To identify effect of length and sequence from a valuable 20 base motif, 5' and 3' regions from a basic sequence (GTTAACTTCAGGGCCTGTGG) of Syn3 were hexamerized to generate two shorter synthetic promoters, Syn3-10b-1 (5': GTTAACTTCA) and Syn3-10b-2 (3': GGGCCTGTGG). These promoters' activities were compared with Syn3 in plants. Syn3 and Syn3-10b-1 were specifically induced in transient agroinfiltrated Nicotiana benthamiana leaves in water cessation for 3 days. In stable transgenic poplar, Syn3 presented as a constitutive promoter but had the highest activity in leaves. Syn3-10b-1 had stronger induction in green tissues under water-deficit stress conditions than mock control. Therefore, a synthetic promoter containing the 5' sequence of Syn3 endowed both tissue-specificity and water-deficit inducibility in transgenic poplar, whereas the 3' sequence did not. Consequently, we have added two new synthetic promoters to the poplar engineering toolkit: Syn3-10b-1, a green tissue-specific and water-deficit stress-induced promoter, and Syn3, a green tissue-preferential constitutive promoter.

Many insects have evolved the ability to manipulate plant growth to generate extraordinary structures called galls, in which insect larva can develop while being sheltered and feeding on the plant. In particular, cynipid (Hymenoptera: Cynipidae) wasps have evolved to form morphologically complex galls and generate an astonishing array of gall shapes, colors, and sizes. However, the biochemical basis underlying these remarkable cellular and developmental transformations remains poorly understood. A key determinant in plant cellular development is cell wall deposition that dictates the physical form and physiological function of newly developing cells, tissues, and organs. However, it is unclear to what degree cell walls are restructured to initiate and support the formation of new gall tissue. Here, we characterize the molecular alterations underlying gall development using a combination of metabolomic, histological, and biochemical techniques to elucidate how valley oak (Quercus lobata) leaf cells are reprogrammed to form galls. Strikingly, gall development involves an exceptionally coordinated spatial deposition of lignin and xylan to form de novo gall vasculature. Our results highlight how cynipid wasps can radically change the metabolite profile and restructure the cell wall to enable the formation of galls, providing insights into the mechanism of gall induction and the extent to which plants can be entirely reprogrammed to form unique structures and organs.

Non-structural carbohydrates (NSCs) are building blocks for biomass and fuel metabolic processes. However, it remains unclear how tropical forests mobilize, export, and transport NSCs to cope with extreme droughts. We combined drought manipulation and ecosystem 13CO2 pulse-labeling in an enclosed rainforest at Biosphere 2, assessed changes in NSCs, and traced newly assimilated carbohydrates in plant species with diverse hydraulic traits and canopy positions. We show that drought caused a depletion of leaf starch reserves and slowed export and transport of newly assimilated carbohydrates below ground. Drought effects were more pronounced in conservative canopy trees with limited supply of new photosynthates and relatively constant water status than in those with continual photosynthetic supply and deteriorated water status. We provide experimental evidence that local utilization, export, and transport of newly assimilated carbon are closely coupled with plant water use in canopy trees. We highlight that these processes are critical for understanding and predicting tree resistance and ecosystem fluxes in tropical forest under drought.

Plants are essential to human beings because plants are considered most as foods. Plants can be used for food ingredients, medical purposes, and industrial applications. People inspect plants using traditional methods, such as using the naked eye, which can be time-consuming and expensive. Therefore, the effectiveness and high quality of automated crop identification classification systems are needed for adequate crop protection. This study aims to identify and classify nine plant species using different datasets, focusing on transfer learning from models trained on plant leaf datasets. Most research has shown that increasing the dataset size would significantly improve classification accuracy. The accuracy of the first test using the modified N1 classification model was 99.45%. In the second experiment, the accuracy of the N2 model was 99.65%. The accuracy of the N3 model, despite being slightly less accurate than AlexNet, was 99.55%, and it performed better, while the accuracy of AlexNet was 99.73%. Compared to the AlexNet model, the proposed model performed better and required less training time. The N1 model reduced the training time by 34.58%, the N2 model by 18.25%, and the N3 model by 20.23%. The N1 and N3 resulted in the same size, namely 14.8MB, and the compactness was 92.67%. The size of the N2 model was 29.7MB, and the compactness was 85.29% compactness. The proposed models provide more accuracy and efficiency in classifying plant leaves and can be used as a standalone mobile application that benefits farmers. [ABSTRACT FROM AUTHOR]

The plants are attacked from various micro-organisms, bacterial illnesses, and pests. The signs are normally identified via leaves, stem, or fruit inspection. Illnesses that generally appeared on vegetation are from leaves and causes big harm if not managed in the early ranges. To stop this huge harm and manipulate the unfold of disorder this work implements a software system. This research work customs deep neural network to gain knowledge of probable illnesses on leaves within the early phases so it can be stopped early. Deep neural network (DNN) used for image classification. This work mainly focuses a neural network model of leaves ailment detection. The commonly available plant leaves dataset is undertaken with a dataset having special training of disease detection. In this work VGG16, ResNet50, Inception V3 and Inception ResNetV2 architectural techniques are implemented to generate and compare the results. Results are compared on the factors like precision, accuracy, recall and F1-Score. The results lead to the conclusion, that the convolution neural network (CNN) is more impactful technique to perceive and predict plant diseases. [ABSTRACT FROM AUTHOR]

As climate change exacerbates drought stress in many parts of the world, understanding plant physiological mechanisms for drought survival is critical to predicting ecosystem responses. Stem net photosynthesis, which is common in arid environments, may be a drought survival trait, but whether the additional carbon fixed by stems contributes to plant hydraulic function and drought survival in arid land plants is untested. We conducted a stem light-exclusion experiment on saplings of a widespread North American desert tree species, Parkinsonia florida L., and after shading acclimation, we then subjected half of the plants to a drought treatment to test the interaction between light exclusion and water limitation on growth, leaf and stem photosynthetic gas exchange, xylem embolism assessed with micro-computed tomography and gravimetric techniques, and survival. Growth, stem photosynthetic gas exchange, hydraulic function and survival all showed expected reductions in response to light exclusion. However, stem photosynthesis mitigated the drought-induced reductions in gas exchange, xylem embolism (percent loss of conductivity, PLC) and mortality. The highest mortality was in the combined light exclusion and drought treatment, and was related to stem PLC and native sapwood-specific hydraulic conductivity. This research highlights the integration of carbon economy and water transport. Our results show that additional carbon income by photosynthetic stems has an important role in the growth and survival of a widespread desert tree species during drought. This shift in function under conditions of increasing stress underscores the importance of considering stem photosynthesis for predicting drought-induced mortality not only for the additional supply of carbon, but also for its extended benefits for hydraulic function.

Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18 months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested-as a trade-off-a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait-trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.

In many terrestrial habitats, plants experience temporal heterogeneity in water availability both at the intra and inter annual scales, creating dry-wet pulse scenarios. This variability imposes two concomitant challenges for plants: surviving droughts and efficiently utilizing water when it becomes available, whose responses are closely interconnected. To date, most studies have focused on the response to drought following static designs that do not consider consequences of repeated transitions from one state to the other. In principle, different dry-wet pulse scenarios among years may differentially affect species performance, plant strategies, and promote coexistence through temporal niche separation. We predicted that short frequent droughts would disfavor drought-avoidant species, as rapid leaf loss and production could disrupt their carbon balance, whereas tolerant species, which maintain carbon gain during droughts, should thrive in such conditions. Prolonged droughts might harm tolerant species by causing severe cavitation. We assessed the survival and growth responses of seedlings from 19 tropical dry forest tree species to simulated natural dry-wet pulse scenarios, examining their relationships with the continuum of species functional strategies under field conditions, and used greenhouse experiments to accompany the field experiment. As expected, different dry-wet pulse scenarios favored different plant functional strategies. Contrary to predictions, the most tolerant outperformed the most avoiders under all drought scenarios, while rapid water-exploiters thrived under non-drought conditions. The superiority of tolerant over avoider species was reverted in the greenhouse, suggesting that in addition to physiology, the fate of species may depend on extrinsic factors as natural enemies. The interplay between the marked variability of dry-wet pulse scenarios across the years and the diversity of water use strategies may contribute to species coexistence in the tropical dry forests. This research is relevant in predicting changes in dominant tree species under future climate scenarios characterized by increased temporal variation in water availability.

Although primarily studied in relation to photorespiration, serine metabolism in chloroplasts may play a key role in plant CO2 fertilization responses by linking CO2 assimilation with growth. Here, we show that the phosphorylated serine pathway is part of a 'photosynthetic C1 pathway' and demonstrate its high activity in foliage of a C3 tree where it rapidly integrates photosynthesis and C1 metabolism contributing to new biomass via methyl transfer reactions, imparting a large natural 13C-depleted signature. Using 13CO2-labelling, we show that leaf serine, the S-methyl group of leaf methionine, pectin methyl esters, and the associated methanol released during cell wall expansion during growth, are directly produced from photosynthetically-linked C1 metabolism, within minutes of light exposure. We speculate that the photosynthetic C1 pathway is highly conserved across the photosynthetic tree of life, is responsible for synthesis of the greenhouse gas methane, and may have evolved with oxygenic photosynthesis by providing a mechanism of directly linking carbon and ammonia assimilation with growth. Although the rise in atmospheric CO2 inhibits major metabolic pathways like photorespiration, our results suggest that the photosynthetic C1 pathway may accelerate and represents a missing link between enhanced photosynthesis and plant growth rates during CO2 fertilization under a changing climate.

Background: Childhood vitamin A deficiency leads to increased morbidity and mortality. Human milk is the only source of vitamin A for exclusively breastfed infants. Dried Moringa oleifera leaf powder (moringa) is a good food source of provitamin A and other carotenoids. Its effect during lactation on human milk vitamin A and carotenoid content is unclear. Objectives: Our objective was to investigate the effect of maternal moringa consumption on human milk retinol and carotenoid concentrations and maternal and infant vitamin A status. Methods: We conducted a 3-month pilot single-blinded cluster-randomized controlled trial in breastfeeding mother-infant pairs (n = 50) in Kenya. Mothers received corn porridge with (20 g/d) or without moringa with complete breast expressions and maternal and infant serum collected at enrollment (infant

Eucalyptus camaldulensis is a multifunctional tree and is globally used for the reclamation of problematic lands. Eucalyptus camaldulensis is prone to attack by a number of pathogens, but the most important threat is the Fusarium wilt (Fusarium oxysporum). Keeping in view the importance of E. camaldulensis and to manage this disease, five plant activators, i.e., salicylic acid (C7H6O3), benzoic acid (C7H6O2), citric acid (C6H8O7), dipotassium phosphate (K2HPO4), monopotassium phosphate (KH2PO4) and nutritional mixture namely Compound (NPK) and nutriotop (Fe, Zn, Cu, B, Mn) were evaluated in the Fusarium infested field under RCBD in the Research Area, Department of Forestry and Range Management, University of Agriculture, Faisalabad (UAF). Among plant activators, salicylic acid and a combination of compound + nutriotop exhibited the lowest disease incidence and enhanced fresh and dry weight of leaves compared to other treatments and control. Results of the environmental study indicated maximum disease incidence between 35-40 °C (max. T), 6-25 °C (mini. T), 70-80% relative humidity and 1.5-2.5 km/h wind speed while pan evaporation expressed weak correlation with disease development. It was concluded that Fusarium wilt of Eucalyptus camaldulensis could be managed through activation of the basal defense system of the host plant with provision of salicylic acid and balanced nutrition by considering environmental factors. Recent exploration is expected to be helpful for future research efforts on epidemiology and ecologically sound intervention of Fusarium wilt of Eucalyptus camaldulensis.

Kockovaella, in the family Cuniculitremaceae of the order Tremellales, is a globally distributed genus of blastoconidia-forming fungi. Currently, 23 species have been described and accepted as members of the genus. In this study, five yeast strains were isolated from plant leaf surfaces collected in the Fujian and Guizhou Provinces of China and identified through a combination of morphological and molecular methods. The related phenotypic features and molecular phylogenetic analyses based on ITS, LSU, and RPB1 sequences demonstrated that they were members of three novel Kockovaella species: K. iteae sp. nov., K. quanzhouensis sp. nov., and K. sambucuse sp. nov. These species were described in detail and discussed relative to other species. This study demonstrated the novel geographical distribution as well as the high species diversity of Kockovaella in China and offered more data for further studies in fungal systematics and evolution. [ABSTRACT FROM AUTHOR]

Plant hyperspectral images (HSIs) contain valuable information for agricultural disaster prediction, biomass estimation, and other applications. However, they also include a lot of irrelevant background information, which wastes storage resources. In this paper, we propose a novel recursive sub-tensor hyperspectral compressive sensing method for plant leaves. This method uses recursive sub-tensor compressive sensing to compress and reconstruct each arbitrary-shape leaf region, discarding a large amount of background information to achieve the best possible reconstruction performance of the leaf region and significantly reduce storage space. The proposed method involves several key steps. Firstly, the optimal band is determined using the spatial spectral decorrelation criterion, and its corresponding mask image is used to extract the leaf regions from the background. Secondly, the recursive maximum inscribed rectangle algorithm is applied to obtain rectangular sub-tensors of leaves recursively. Each sub-tensor is then individually compressed and reconstructed. Finally, all sub-tensors can be reconstructed to form complete leaf HSIs without background information. Experimental results demonstrate that the proposed method achieves superior image reconstruction quality at extremely low sampling rates compared to other methods. The proposed method can improve average Peak Signal-to-Noise Ratio (PSNR) values by about 3.04% and 0.74% compared to Tensor Compressive Sensing (TCS) at the sampling rate of 2%. In the spectral domain, the proposed method can achieve significantly smaller Spectral Angle Mapper (SAM) values and relatively lower spectral indices errors for Double Difference, Triangular Vegetation Index, Leaf Chlorophyll Index, and Modified Normalized Difference 680 than those of TCS. Therefore, the proposed method achieves better compression performance for reconstructed plant leaf HSIs than the other methods. [ABSTRACT FROM AUTHOR]

Hereditary factor VII (FVII) deficiency is an uncommon autosomal recessive disorder associated with mutations in the F7 gene, and laboratory investigations usually reveal isolated prolongation in prothrombin time (PT)/international normalized ratio (INR). Venom-induced consumptive coagulopathy (VICC) is distinguished by the activation of the coagulation pathway, which is triggered by procoagulant toxins in snake venom. Diagnosing snakebites in patients with hereditary FVII deficiency presents a challenge because prolonged time PT/INR is considered the most valuable diagnostic method for VICC. Therefore, it is possible that certain patients may not promptly receive an accurate diagnosis of hereditary FVII deficiency. We present a pedigree featuring hereditary FVII deficiency, which was diagnosed through Sanger sequencing, following a bamboo leaf green snake bite. [ABSTRACT FROM AUTHOR]

The Polymer Electrolyte Membrane Water Electrolyser (PEMWE) has gained significant interest among various electrolysis methods due to its ability to produce highly purified, compressed hydrogen. The spatial configuration of bipolar plates and their flow channel patterns play a critical role in the efficiency and longevity of the PEM water electrolyser. Optimally designed flow channels ensure uniform pressure and velocity distribution across the stack, enabling high-pressure operation and facilitating high current densities. This study uses flow channel geometry inspired by authentic vine leaf patterns found in biomass, based on various plant leaves, including Soybean, Victoria Amazonica, Water Lily, Nelumbo Nucifera, Kiwi, and Acalypha Hispida leaves, as a novel channel pattern to design a PEM bipolar plate with a circular cross-section area of 13.85 c m 2 . The proposed bipolar design is further analysed with COMSOL Multiphysics to integrate the conservation of mass and momentum, molecular diffusion (Maxwell–Stefan), charge transfer equations, and other fabrication factors into a cohesive single-domain model. The simulation results showed that the novel designs have the most uniform velocity profile, lower pressure drop, superior pressure distribution, and heightened mixture homogeneity compared to the traditional serpentine models. [ABSTRACT FROM AUTHOR]

Mangrove leaves have adapted to effectively manage water conservation and regulate toxic saline conditions through the morphological characteristics of stomatal dimensions. The present study examines the stomatal dimensions of 120 Laguncularia racemosa leaves from both a degraded mangrove ecosystem and a restored mangrove ecosystem located along the Guyana coastline. Datasets were obtained during the wet and dry seasons using the nearest individual sampling method. The nail polish blotting technique, microscopy, and digital photography were used to obtain measurements of various stomatal dimensions, including guard cell length and width, pore length and width, circumference, surface area, stomatal frequency, density, index, and epidermal cell frequency. Our hypothesis is that there is significant variation in the stomatal dimensions of Laguncularia racemosa leaves as a function of mangrove ecosystem type and seasonal change. The results of this study confirmed this hypothesis as significant variations were observed in stomatal dimensions as a function of seasonal changes and mangrove ecosystem type. Statistically significant differences (p < 0.05, R > 0.70) were observed between the degraded ecosystem during the dry season and the restored ecosystem during the wet season, specifically regarding guard cell length and width, pore length and width, area, and circumference. Multiple regression analysis and PCA provide compelling evidence to support the existence of robust correlations between ecosystem types and stomatal dimensions. The results of our study indicate that the leaves of Laguncularia racemosa display certain small-scale adjustments that enable them to manage the stress factors present in different ecosystems and seasons. [ABSTRACT FROM AUTHOR]

BACKGROUND AND AIMS: Drought events have devasting impacts on grape berry production. The aim of this study was to investigate berry growth in the context of leaf stomatal closure under progressive drought stress. METHODS: Potted grapevine plants (varieties Syrah and Cabernet Sauvignon) were evaluated at pre-verasion (30-45 d after anthesis, DAA) and post-veraison (90-107 DAA). Berry diameter, berry absolute growth rate (AGR), leaf stomatal conductance (Gs) at midday, plant water potential at predawn and midday (ΨPD and ΨMD, respectively), and soil relative water content were measured repeatedly. The ΨPD-threshold of 90 % loss in stomatal conductance (Gs10, i.e. complete stomatal closure) was determined. Data were related to plant dehydration phases I, II and III with corresponding boundaries Θ1 and Θ2, using the water potential curve method. KEY RESULTS: At pre-veraison, berry AGR declined together with leaf Gs in response to soil drying in both varieties. Berry AGR transitioned from positive to negative (shrinkage) values when leaf Gs approached zero. The Gs10-threshold was -0.81 MPa in Syrah and -0.74 MPa in Cabernet Sauvignon and was linked to boundary Θ1. At post-veraison, berry AGR was negligible and negative AGR values were not intensified by increasing drought stress in either variety. CONCLUSION: Leaf complete stomatal closure under progressive drought stress coincides with cessation of berry growth followed by shrinkage at pre-veraison (growth stage 1).

Leaves harbor distinct microbial communities that can have an important impact on plant health and microbial ecosystems worldwide. Nevertheless, the ecological processes that shape the composition of leaf microbial communities remain unclear, with previous studies reporting contradictory results regarding the importance of bacterial dispersal versus host selection. This discrepancy could be driven in part because leaf microbiome studies typically consider the upper and lower leaf surfaces as a single entity despite these habitats possessing considerable anatomical differences. We characterized the composition of bacterial phyllosphere communities from the upper and lower leaf surfaces across 24 plant species. Leaf surface pH and stomatal density were found to shape phyllosphere community composition, and the underside of leaves had lower richness and higher abundances of core community members than upper leaf surfaces. We found fewer endemic bacteria on the upper leaf surfaces, suggesting that dispersal is more important in shaping these communities, with host selection being a more important force in microbiome assembly on lower leaf surfaces. Our study illustrates how changing the scale in which we observe microbial communities can impact our ability to resolve and predict microbial community assembly patterns on leaf surfaces. IMPORTANCE Leaves can harbor hundreds of different bacterial species that form unique communities for every plant species. Bacterial communities on leaves are really important because they can, for example, protect their host against plant diseases. Usually, bacteria from the whole leaf are considered when trying to understand these communities; however, this study shows that the upper and lower sides of a leaf have a very different impact on how these communities are shaped. It seems that the bacteria on the lower leaf side are more closely associated with the plant host, and communities on the upper leaf side are more impacted by immigrating bacteria. This can be really important when we want to treat, for example, crops in the field with beneficial bacteria or when trying to understand host-microbe interactions on the leaves.

Persian walnut is a drought-sensitive species with considerable genetic variation in the photosynthesis and water use efficiency of its populations, which is largely unexplored. Here, we aimed to elucidate changes in the efficiency of photosynthesis and water content using a diverse panel of 60 walnut families which were submitted to a progressive drought for 24 days, followed by two weeks of re-watering. Severe water-withholding reduced leaf relative water content (RWC) by 20%, net photosynthetic rate (Pn) by 50%, stomatal conductance (gs) by 60%, intercellular CO2 concentration (Ci) by 30%, and transpiration rate (Tr) by 50%, but improved water use efficiency (WUE) by 25%. Severe water-withholding also inhibited photosystem II functionality as indicated by reduced quantum yield of intersystem electron transport (φEo) and transfer of electrons per reaction center (ET0/RC), also enhanced accumulation of QA (VJ) resulted in the reduction of the photosynthetic performance (PIABS) and maximal quantum yield of PSII (FV/FM); while elevated quantum yield of energy dissipation (φDo), energy fluxes for absorption (ABS/RC) and dissipated energy flux (DI0/RC) in walnut families. Cluster analysis classified families into three main groups (tolerant, moderately tolerant, and sensitive), with the tolerant group from dry climates exhibiting lesser alterations in assessed parameters than the other groups. Multivariate analysis of phenotypic data demonstrated that RWC and biophysical parameters related to the chlorophyll fluorescence such as FV/FM, φEo, φDo, PIABS, ABS/RC, ET0/RC, and DI0/RC represent fast, robust and non-destructive biomarkers for walnut performance under drought stress. Finally, phenotype-environment association analysis showed significant correlation of some photosynthetic traits with geoclimatic factors, suggesting a key role of climate and geography in the adaptation of walnut to its habitat conditions.

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Plant response to pathogen infection varies within a leaf, yet this heterogeneity is not well resolved. We expose Arabidopsis to Pseudomonas syringae or mock treatment and profile >11,000 individual cells using single-cell RNA sequencing. Integrative analysis of cell populations from both treatments identifies distinct pathogen-responsive cell clusters exhibiting transcriptional responses ranging from immunity to susceptibility. Pseudotime analyses through pathogen infection reveals a continuum of disease progression from an immune to a susceptible state. Confocal imaging of promoter-reporter lines for transcripts enriched in immune cell clusters shows expression surrounding substomatal cavities colonized or in close proximity to bacterial colonies, suggesting that cells within immune clusters represent sites of early pathogen invasion. Susceptibility clusters exhibit more general localization and are highly induced at later stages of infection. Overall, our work shows cellular heterogeneity within an infected leaf and provides insight into plant differential response to infection at a single-cell level.

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.

Life on Earth depends on the conversion of solar energy to chemical energy by plants through photosynthesis. A fundamental challenge in optimizing photosynthesis is to adjust leaf angles to efficiently use the intercepted sunlight under the constraints of heat stress, water loss and competition. Despite the importance of leaf angle, until recently, we have lacked data and frameworks to describe and predict leaf angle dynamics and their impacts on leaves to the globe. We review the role of leaf angle in studies of ecophysiology, ecosystem ecology and earth system science, and highlight the essential yet understudied role of leaf angle as an ecological strategy to regulate plant carbon-water-energy nexus and to bridge leaf, canopy and earth system processes. Using two models, we show that leaf angle variations have significant impacts on not only canopy-scale photosynthesis, energy balance and water use efficiency but also light competition within the forest canopy. New techniques to measure leaf angles are emerging, opening opportunities to understand the rarely-measured intraspecific, interspecific, seasonal and interannual variations of leaf angles and their implications to plant biology and earth system science. We conclude by proposing three directions for future research.

In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.

MicroRNAs (miRNAs) play diverse roles in plant development, but whether and how miRNAs participate in thermomorphogenesis remain ambiguous. Here we show that HYPONASTIC LEAVES 1 (HYL1)-a key component of miRNA biogenesis-acts downstream of the thermal regulator PHYTOCHROME INTERACTING FACTOR 4 in the temperature-dependent plasticity of hypocotyl growth in Arabidopsis. A hyl1-2 suppressor screen identified a dominant dicer-like1 allele that rescues hyl1-2's defects in miRNA biogenesis and thermoresponsive hypocotyl elongation. Genome-wide miRNA and transcriptome analysis revealed microRNA156 (miR156) and its target SQUAMOSA PROMOTER-BINDING-PROTEIN-LIKE 9 (SPL9) to be critical regulators of thermomorphogenesis. Surprisingly, perturbation of the miR156/SPL9 module disengages seedling responsiveness to warm temperatures by impeding auxin sensitivity. Moreover, miR156-dependent auxin sensitivity also operates in the shade avoidance response at lower temperatures. Thus, these results unveil the miR156/SPL9 module as a previously uncharacterized genetic circuit that enables plant growth plasticity in response to environmental temperature and light changes.

Nutrient stress can impose significant metabolic strain on plants, resulting in declining agricultural productivity. Nitrogen, phosphorus, and potassium are essential growth-limiting nutrients and are the primary building elements for amino acids, nucleic acids, proteins, and chlorophyll. The absence of these nutrients has observable effects on various plant characteristics, such as leaf size, color, and plant height. However, recent technological advances in imaging have given birth to computer vision-based plant phenomics, which holds great promise for plant research and management. The non-destructive, quick, automated assessments made possible by these imaging techniques are transforming the field of plant nutrient stress research and monitoring. This paper presents a hybrid quantum–classical model (HQCM) for identifying multi-nutrient stress and nutrient stress level quantification (NSLQ) for plant stress level identification by analyzing plant leaf images, utilizing the combined capabilities of classical and quantum computing systems. The HQCM model uses groundnut multi-nutrient stress (private), rice plant nutrient stress (public), and plant village (public) datasets for experimentation. The HQCM model exhibited impressive levels of accuracy, achieving rates of 97.79%, 97.37%, and 98.75% on the groundnut, rice, and plant village datasets, respectively. This performance surpasses conventional models, including Xception, DECM, DWC, and ResNet50V2. The proposed model showed significant advancements in accuracy, reaching the performance of state-of-art algorithms by 3.24%, 4.07%, and 6.73%, thus emphasizing its better performance. [ABSTRACT FROM AUTHOR]

Plant leaves contain multiple cell types which achieve distinct characteristics whilst still coordinating development within the leaf. The bundle sheath possesses larger individual cells and lower chloroplast content than the adjacent mesophyll, but how this morphology is achieved remains unknown. To identify regulatory mechanisms determining bundle sheath cell morphology we tested the effects of perturbing environmental (light) and endogenous signals (hormones) during leaf development of Oryza sativa (rice). Total chloroplast area in bundle sheath cells was found to increase with cell size as in the mesophyll but did not maintain a 'set‐point' relationship, with the longest bundle sheath cells demonstrating the lowest chloroplast content. Application of exogenous cytokinin and gibberellin significantly altered the relationship between cell size and chloroplast biosynthesis in the bundle sheath, increasing chloroplast content of the longest cells. Delayed exposure to light reduced the mean length of bundle sheath cells but increased corresponding leaf length, whereas premature light reduced final leaf length but did not affect bundle sheath cells. This suggests that the plant hormones cytokinin and gibberellin are regulators of the bundle sheath cell‐chloroplast relationship and that final bundle sheath length may potentially be affected by light‐mediated control of exit from the cell cycle. Summary statement: In rice (Oryza sativa) the timing of light exposure during leaf development changes mature bundle sheath morphology, reducing maximum cell length under extended darkness. Bundle sheath chloroplast biogenesis responds to changing cell size, with this relationship influenced by endogenous hormones. [ABSTRACT FROM AUTHOR]

SUMMARY: Next‐generation sequencing (NGS) library construction often involves using restriction enzymes to decrease genome complexity, enabling versatile polymorphism detection in plants. However, plant leaves frequently contain impurities, such as polyphenols, necessitating DNA purification before enzymatic reactions. To overcome this problem, we developed a PCR‐based method for expeditious NGS library preparation, offering flexibility in number of detected polymorphisms. By substituting a segment of the simple sequence repeat sequence in the MIG‐seq primer set (MIG‐seq being a PCR method enabling library construction with low‐quality DNA) with degenerate oligonucleotides, we introduced variability in detectable polymorphisms across various crops. This innovation, named degenerate oligonucleotide primer MIG‐seq (dpMIG‐seq), enabled a streamlined protocol for constructing dpMIG‐seq libraries from unpurified DNA, which was implemented stably in several crop species, including fruit trees. Furthermore, dpMIG‐seq facilitated efficient lineage selection in wheat and enabled linkage map construction and quantitative trait loci analysis in tomato, rice, and soybean without necessitating DNA concentration adjustments. These findings underscore the potential of the dpMIG‐seq protocol for advancing genetic analyses across diverse plant species. Significance Statement: Given that plants contain impurities in their leaves, DNA purification is required to construct NGS libraries with reduced genomic complexity using restriction enzymes, which poses a hinderance to rapid genotyping. We developed degenerate oligonucleotide primer MIG‐seq and its accompanying protocol, a method for constructing NGS libraries with varying degrees of complexity reduction from unpurified plant DNA using PCR, and demonstrated the feasibility of expeditious genetic analysis across various crop species. [ABSTRACT FROM AUTHOR]

Stress experienced during development in organisms with bilateral structures could result in developmental instability, which is expressed as subtle non‐directional deviations from perfect symmetry, known as fluctuating asymmetry (FA). As such, FA has been proposed, and extensively used, as a trait indicating stress for many organisms with bilateral structures and many types of stress. However, while this concept may apply to animals, the evidence for plants' main vegetative structures, that is, leaves, remains equivocal, and a comprehensive synthesis on this topic is still missing.We designed observational field and controlled greenhouse studies, combining different growth and leaf forms across multiple stress gradients, comprising 21 species and 80 populations. We measured FA as the difference between the left and right area of the leaf, an approach that accommodates diverse leaf forms. We used high‐precision, blind, single‐person measurements and tested for other forms of symmetry and the effect of leaf size. We further complemented our study with a systematic literature review of FA in plant leaves, compiling 51 studies comprising 72 species, 23 stress types and 131 unique entries (species × stress type).We consistently found no effect of stress on leaf FA in any of the studied species in both our field and experimental gradients. In the systematic literature review, only 39% of the unique entries showed the expected increase in FA with stress, 53% showed no effect, 9% showed an opposite trend of a decrease in FA with stress and 1% showed a unimodal relationship. Importantly, only 40% of all entries fulfilled the crucial step of controlling for a high‐precision measurement, and of these 49% reported the expected increase in FA with stress.Both the results of our observational and experimental approaches and the systematic literature review failed to support a clear relationship between stress and FA in plant leaves. These results clearly show that FA in plant leaves cannot be used as a reliable trait indicating stress during development. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Plant hyperspectral images (HSIs) contain valuable information for agricultural disaster prediction, biomass estimation, and other applications. However, they also include a lot of irrelevant background information, which wastes storage resources. In this paper, we propose a novel recursive sub-tensor hyperspectral compressive sensing method for plant leaves. This method uses recursive sub-tensor compressive sensing to compress and reconstruct each arbitrary-shape leaf region, discarding a large amount of background information to achieve the best possible reconstruction performance of the leaf region and significantly reduce storage space. The proposed method involves several key steps. Firstly, the optimal band is determined using the spatial spectral decorrelation criterion, and its corresponding mask image is used to extract the leaf regions from the background. Secondly, the recursive maximum inscribed rectangle algorithm is applied to obtain rectangular sub-tensors of leaves recursively. Each sub-tensor is then individually compressed and reconstructed. Finally, all sub-tensors can be reconstructed to form complete leaf HSIs without background information. Experimental results demonstrate that the proposed method achieves superior image reconstruction quality at extremely low sampling rates compared to other methods. The proposed method can improve average Peak Signal-to-Noise Ratio (PSNR) values by about 3.04% and 0.74% compared to Tensor Compressive Sensing (TCS) at the sampling rate of 2%. In the spectral domain, the proposed method can achieve significantly smaller Spectral Angle Mapper (SAM) values and relatively lower spectral indices errors for Double Difference, Triangular Vegetation Index, Leaf Chlorophyll Index, and Modified Normalized Difference 680 than those of TCS. Therefore, the proposed method achieves better compression performance for reconstructed plant leaf HSIs than the other methods.

Water disinfection by copper vessels has been prevalent over thousands of years. Unfortunately, people are still suffering from the bacterial pollution in drinking water. Here we show that, only through steeping with tiny amounts of common plant leaves, the room-temperature water in copper pots has unexpectedly high antibacterial ability. Remarkably, copper ions released from copper pots into water are in concentrations lower than the WHO safety threshold for drinking water, and have effective antibacterial ability when water contains specific leave components (polyphenols and/or lignin). Our computations show that the key to enhance antibacterial ability is the great increase in the proportion of Cu+ induced by aromatic rings in these leave components, which has been demonstrated by our experiments. The findings may disclose the mystery of copper vessels for water disinfection, and more importantly, provide effective antibacterial applications in industries and daily lives, by safely using copper ions together with biocompatible natural substances.

Understanding climate change impacts on the Cape Floristic Region requires improved knowledge of plant physiological responses to the environment. Studies examining physiological responses of mountain fynbos have consisted of campaign-based measurements, capturing snapshots of plant water relations and photosynthesis. We examine conclusions drawn from prior studies by tracking in situ physiological responses of three species, representing dominant growth forms (proteoid, ericoid, restioid), over 2 years using miniature continuous sap flow technology, long-term observations of leaf/culm water potential and gas exchange, and xylem vulnerability to embolism. We observed considerable inter-specific variation in the timing and extent of seasonal declines in productivity. Shallow-rooted Erica monsoniana exhibited steep within-season declines in sap flow and water potentials, and pronounced inter-annual variability in total daily sap flux (Js). Protea repens showed steady reductions in Js across both years, despite deeper roots and less negative water potentials. Cannomois congesta-a shallow-rooted restioid-was least negatively impacted. Following rehydrating rain at the end of summer, gas exchange recovery was lower in the drier year compared with the normal year, but did not differ between species. Loss of function in the drier year was partially accounted for by loss of xylem transport capacity in Erica and Cannomois, but not Protea. Hitherto unseen water use patterns, including inter-annual variability of gas exchange associated with contrasting water uptake properties, reveal that species use different mechanisms to cope with summer dry periods. Revealing physiological responses of key growth forms enhances predictions of plant function within mountain fynbos under future conditions.