Gulnaz Kahar, Yakupjan Haxim, Xuechun Zhang
et al.
Chitinases are enzymes that catalyze the hydrolysis of chitin and play a significant biophysiological role in fungal growth, development, and pathogenesis. <i>Valsa mali</i> is a necrotrophic fungus that is a primary contributor to apple <i>Valsa</i> canker. Our study focused on the identification of chitinase gene families from <i>V. mali</i> and the analysis of their expression profiles during infection and nutritional growth. A phylogenetic analysis and conservation of catalytic domains were used to classify these genes into three classes, and their chromosome distribution was random. The qRT-PCR analysis identified five differentially expressed VmGH18 genes during infection and nutritional growth. GH18 chitinases use glutamate, whereas VmGH18-4 (VM1G_05900) and VmGH18-10 (VM1G_03597) use glutamine as the catalytic motif. To further test whether it can induce cell death in apple, the recombinant protein was produced in <i>E. coli</i>. It showed that the purified VmGH18-4 recombinant protein retained cell-death inducing activity, and it could also induce cell death in apple. But the enzyme activity shows that neither VmGH18-4 nor VmGH18-10 have chitinases enzyme activity. These results suggest that VmGH18-4 can elicit cell death in multiple plant species, while VmGH18-10 cannot.
Imene Djaalab, Samia Haffaf, Hadria Mansour-Djaalab
et al.
Animal Welfare has a significant impact on the dairy cow’s health, behaviour, productivity and milk quality. By implementing husbandry practices that respect the physical, behavioural and emotional needs of dairy cows, the dairy industry can improve the sustainability of its operations and meet rising expectations. The aim of this study is to evaluate the impact of housing systems (free vs. tied) on dairy cow health through musculoskeletal health indicators and lameness scores. The hypothesis that dairy cows reared in free housing have a better quality of health than cows reared in restrained housing is tested. Thus, 300 dairy cows of the Holstein and Montbeliarde breeds were selected from dairy farms in five municipalities of Constantine province (eastern Algeria). The results showed that the frequency of severe lameness did not exceed 12% in stalls with restraints and more than 42% of light lameness are in free-stall housing (<i>p</i> < 0.001). These results reflect a lack of comfort in restricted housing, with an impact on dairy performances. Moreover, the monitoring of lame cows and the functional trimming of their hooves should be frequent. It is also important to implement a cull policy for unproductive cows. Finally, it is very important to provide adequate training to farmers in order to improve the well-being of dairy cows.
<i>Taraxacum kok-saghyz</i> (TKS) is a natural rubber (NR)-producing plant with great development prospects. Accurately understanding the molecular mechanism of natural rubber biosynthesis is of great significance. Cis-prenyltransferase (CPT) and cis-prenyltransferase-like (CPTL) proteins catalyze the elongation of natural rubber molecular chains and play an essential role in rubber biosynthesis. In this study, we performed a genome-wide identification of the <i>TkCPT</i>/<i>CPTL</i> family, with eight <i>CPT</i> and two <i>CPTL</i> members. We analyzed the gene structures, evolutionary relationships and expression patterns, revealing five highly conserved structural domains. Based on systematic evolutionary analysis, CPT/CPTL can be divided into six subclades, among which the family members are most closely related to the orthologous species <i>Taraxacum mongolicum.</i> Collinearity analyses showed that fragment duplications were the primary factor of amplification in the <i>TkCPT/CPTL</i> gene family. Induced by ethylene and methyl jasmonate hormones, the expression levels of most genes increased, with significant increases in the expression levels of <i>TkCPT5</i> and <i>TkCPT6</i>. Our results provide a theoretical basis for elucidating the role of the <i>TkCPT</i>/<i>CPTL</i> gene family in the mechanism of natural rubber synthesis and lay a foundation for molecular breeding of <i>T. kok-saghyz</i> and candidate genes for regulating natural rubber biosynthesis in the future.
Jona Cappelle, Jarne Van Mulders, Sarah Goossens
et al.
Precision agriculture demands non-invasive, energy-efficient, and sustainable plant monitoring solutions. In this work, we present the design and implementation of a lightweight, batteryless plant movement sensor powered solely by RF energy. This sensor targets Controlled Environment Agriculture (CEA) and utilizes inertial measurements units (IMUs) to monitor leaf motion, which correlates with plant physiological responses to environmental stress. By eliminating the battery, we reduce the ecological footprint, weight, and maintenance requirements, transitioning from lifetime-based to operation-based energy storage. Our design minimizes circuit complexity while enabling flexible, adaptive readout scheduling based on energy availability and sensor data. We detail the energy requirements, RF power transfer considerations, integration constraints, and outline future directions, including multi-antenna power delivery and networked sensor synchronization.
Ruchi Bhatt, Shreya Bansal, Amanpreet Chander
et al.
Understanding plant growth dynamics is essential for applications in agriculture and plant phenotyping. We present the Growth Modelling (GroMo) challenge, which is designed for two primary tasks: (1) plant age prediction and (2) leaf count estimation, both essential for crop monitoring and precision agriculture. For this challenge, we introduce GroMo25, a dataset with images of four crops: radish, okra, wheat, and mustard. Each crop consists of multiple plants (p1, p2, ..., pn) captured over different days (d1, d2, ..., dm) and categorized into five levels (L1, L2, L3, L4, L5). Each plant is captured from 24 different angles with a 15-degree gap between images. Participants are required to perform both tasks for all four crops with these multiview images. We proposed a Multiview Vision Transformer (MVVT) model for the GroMo challenge and evaluated the crop-wise performance on GroMo25. MVVT reports an average MAE of 7.74 for age prediction and an MAE of 5.52 for leaf count. The GroMo Challenge aims to advance plant phenotyping research by encouraging innovative solutions for tracking and predicting plant growth. The GitHub repository is publicly available at https://github.com/mriglab/GroMo-Plant-Growth-Modeling-with-Multiview-Images.
Olea europaea L., olive tree, has a very important role in the economy of the Mediterranean region, where 93 % of the world's olive oil is produced. This species is well adapted to the environmental conditions of this area, but the increase in the frequency of extreme climatic events, due to climate change, is affecting the yield and quality of olive products. The use of eco-friendly solutions, like plant-beneficial microorganisms, can be a sustainable agronomic tool to improve plant tolerance to stress and boost agricultural production. We aim to unravel the effects of the pre-treatment of olive plants with the bacterium Pseudomonas reactans Ph3R3 on drought tolerance. Young potted olive plants were treated with a solution of P. reactans (soil inoculation) or with distilled water, and then exposed to two watering conditions (well-watered or water deficit). Plant water status, photosynthesis, pigments, carbohydrates, oxidative stress biomarkers, and total antioxidant capacity were evaluated 61 and 191 days after the beginning of the watering treatments. The pre-treatment with P. reactans improved leaf dry biomass production, and soil C and N availability. Moreover, under drought conditions, P. reactans increased leaf water availability, N levels, and the intercellular CO2, leading to improved net CO2 assimilation rate and carbohydrates production. Also, P. reactans activated stress protective strategies (total antioxidant capacity) that helped to control oxidative stress. These data demonstrated that the benefits triggered by P. reactans pre-treatment promoted olive performance and tolerance to drought and could be a promising strategy to improve olive culture sustainability.
Mayra del C. Fragoso-Medina, Armando Navarrete-Segueda, Eliane Ceccon
et al.
Tropical rainforests offer a diverse array of real or potential forest products (FP). However, the ongoing conversion of these forests to agriculture raises concerns about the future availability and sustainability of FP. In this study, we examined the changes in availability (tree density and above-ground biomass) and species richness of native trees, recognized by local communities as sources of FP, with the forest-to-agriculture conversion in a Mesoamerican tropical rainforest region. Specifically, we tested hypotheses on whether species with FP had a higher, equal, or lower reduction in the availability, diversity, and probability of persistence than species without FP with the forest conversion. We interviewed landowners to identify tree species with FP and documented management practices and regulations for using these species. In fourteen 1 km2 landscapes, encompassing the entire range of forest-to-agriculture conversion (from 0 % to ∼100 % old-growth forest cover), we analyzed changes in the availability and richness of species with and without FP. In each landscape, we randomly established 30 plots (each 706.8 m2, totaling 420 plots and 29.7 ha sampling area) covered by old-growth forest, secondary forest, or agricultural fields (mostly cattle pastures). Over four years, we surveyed all trees with a diameter at breast height ≥ 10 cm in these plots. With the forest conversion, assemblages of tree species with FP exhibited a higher reduction in aboveground biomass than species without FP. However, assemblages of species with FP exhibited a significantly lower reduction in abundance, species richness, and a higher probability of persistence than assemblages of species without FP. Furthermore, we found evidence of implementing forest management practices favoring the preservation of species with FP in agricultural lands. Thus, we conclude that people intentionally foster the persistence of valuable species in their agricultural fields, which could have important implications for the structure and composition of future regenerating forests on abandoned agricultural lands. In the long term, this might lead to an overabundance of locally valuable species, as observed in old-growth tropical rainforests that native people ancestrally managed.
The adoption of agroecological practices will be crucial to address the challenges of climate change and biodiversity loss. Such practices favor the cultivation of plants in complex mixtures with layouts differing from the monoculture approach of conventional agriculture. Inspired by random sequential adsorption processes, we propose a one-dimensional model in which the plants are represented as line segments that start as points and grow at a constant rate until they reach length $σ$ after a time interval $τ$. The planting positions and times are randomly chosen with the constraint that plant overlap is forbidden. We apply an exact, event-driven simulation to investigate the resulting spatiotemporal patterns and yields in both mono- and duocultures. After a transient period, with oscillations in the density and coverage, the field reaches a steady state in which the mean age of plants is one half of the time to maturity. The structure of the active plants is characterized by correlation functions between the fluctuation of the age of a plant and its $k$th neighbour. Nearest neighbours are negatively correlated, while next nearest neighbours tend to have similar ages. The steady state yield increases with the planting rate and approaches a maximum value of 4/3 plants per unit length per unit time. For two species with the same size at maturity but different growth rates, the more slowly growing species is enriched in the harvest compared to the seed mix composition. If two species have the same time to maturity but different sizes, the smaller one is enriched in the harvest and, at a sufficiently high planting rate, the larger species may be completely absent. For two species with the same ratio of $σ/τ$ the selectivity is insensitive to the planting rate. The model may be extended to higher dimensions, more species and other planting strategies.
Kristen Van Gelder, Steffen N. Lindner, Andrew D. Hanson
et al.
Expressing plant metabolic pathways in microbial platforms is an efficient, cost-effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here we first summarize current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labor-intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost-effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data-driven machine learning framework designed to extract 'yeastizing' rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design-build-test-cycle.
Photosynthesis is crucial for sustaining life on this planet and necessary for plant growth and development. Abiotic stresses such as high and low temperatures, and excess, or deficit of water limit the crucial plant processes, thus threatening the global food security. However, recent molecular approaches allowed elucidation of the photosynthetic components/compounds and their efficiency under stress conditions. In the present scenario, these approaches are not enough to reduce the yield penalty due to the reduction in photosynthetic efficiency. Therefore, comprehensive data on plant behavior and stress crosstalk networks could assist in understanding the in-depth mechanism of photosynthesis. In recent years, information regarding crosstalk, signaling characterization of candidate genes, and responses to multiple stressors have advanced our knowledge to understand the mechanism of photosynthesis. Therefore, in this review, we provide a comprehensive overview of various studies conducted on photosynthesis under multiple abiotic stress factors that affect the photosynthetic efficiency of a plant. We also discuss the role of crosstalk signaling compounds (plant growth regulators and micro RNAs) for an in-depth understanding of the photosynthesis mechanism. Finally, based on our gathered data set, the mechanism of damage and adaptive response of photosynthesis under multiple stressors are explained to enhance the scientific community's knowledge toward boosting photosynthesis and to accelerate stress tolerance strategies for crop improvement.
Martin Hessling, Ben Sicks, Anna-Maria Gierke
et al.
(1) Background: Hand hygiene with chemical disinfectants is an important measure to reduce the spread of infections, but frequent use can cause skin irritation. In recent years, it has become widely accepted that visible light can also have an antimicrobial effect, and visible light has even been applied to the disinfection of wounds. The present study aims to evaluate whether hand disinfection with visible light is a realistic alternative to chemical disinfectants. (2) Methods: Human hands were irradiated with a dose of 10 or 33 J/cm<sup>2</sup> of visible violet light (405 nm) for 3 or 10 min, respectively. The reducing effect of the visible violet light was determined by comparing the contact agar plate results of irradiated and non-irradiated hands. Comparative experiments with a conventional hand disinfecting gel were also performed. Applicable standards were consulted to evaluate skin exposure to the irradiation. (3) Results: Irradiation of the hands with 10 and 33 J/cm<sup>2</sup> resulted in an average reduction of microorganisms on the skin of 0.43 and 0.76 log-levels, respectively. These disinfection results with visible violet light are far behind those of the disinfectant gel, which achieved a reduction of 2.17 log-levels. Additionally, due to legal limits, a 3-min irradiation can only be performed five times per day and a 10-min procedure only once. (4) Conclusion: Since the irradiation doses applied up to now have not provided a substantial antimicrobial effect, and since an increase in the dose in a short time period is not arbitrarily possible without heating the hand unpleasantly, visible light of 405 nm seems rather unsuitable for repeated hand disinfection.
All over the world, environmental engineers, environmental biologists, biochemists, and other scientists are concerned about environmental pollution. In particular, different treatment technologies and applications in terms of water and soil health have been investigated for years. Studies show that the bioprocess (biosorption, bioremediation, bioaccumulation, etc.) approach is more advantageous (economical, easy design, and environmentally friendly, etc.) than many treatment methods. Thanks to these advantages, bioprocesses have been preferred for the removal of different pollutants in the receiving environment. Effective microorganisms (EMOs) are defined as mixed cultures of advantageous and naturally occurring microorganisms that can be used as vaccine material. An EMO is a natural fermentation product that is not chemically or genetically modified in the form of a concentrated solution. An EMO consists of 10 species, including photosynthetic (<i>Rhodopseudomonas palustrus</i> and <i>Rhodobacter spaeroides</i>, etc.) and lactic acid (<i>Lactobacillus plantarum</i>, <i>Lactobacillus casei</i> and <i>Streptoccus lactis</i>, etc.) bacterial groups, yeasts (<i>Saccharomyces cerevisiae</i> and <i>Candida utilis</i>, etc.), actinomycetes, and fermenting fungi The main components of an EMO are lactic acid bacteria, yeasts, and photosynthetic bacteria. In a liquid solution, they are in harmony. This article aims to review the literature on “Effective Microorganisms (EMOs)” from different scientific databases and discuss the effectiveness of using EMOs for bioprocess.
Halophiles are microorganisms that inhabit saline and hypersaline environments, requiring salinity to survive in such extreme conditions. These microorganisms are mainly researched for their biotechnological potential. This study aims to investigate the phenology of the studied strain, <i>Idiomarina loihiensis</i>, and to demonstrate its extracellular proteolytic activity, as well as the production of a protease via batch fermentation in halophilic microorganisms. Macroscopic studies revealed small colonies (≤5 mm) with a convex spherical structure, regular outline, smooth surface, and color ranging from beige to opaque cream. Protease production was investigated in high-salinity conditions with a moderately halophilic bacterium using basal media with varying nitrogen sources. This study found that the highest proteolytic activity occurred in media with tryptone and casein peptone as nitrogen sources, at pH 10, a temperature of 70 °C, and 22.5% salt concentration. The results also demonstrated that the studied protease was a thermostable enzyme.
Tilo Henning, Rafael Acuña-Castillo, Xavier Cornejo
et al.
Documentation of plant taxa has long been subject to the temporal and spatial selectivity of professional research expeditions, especially in tropical regions. Therefore, rare and/or narrowly endemic species are sometimes known only from very few and very old herbarium specimens. However, these taxa are very important from a conservation perspective. The lack of observations of living plants and confirmation of the actual occurrence of taxa hinders the planning and implementation of effective conservation measures. Community science networks have recently made tremendous contributions to documenting biodiversity in many regions across the globe. The rediscovery of six species of Nasa (Loasaceae) from Peru and Ecuador primarily via the platform iNaturalist, is reported.
Rhizoctonia root rot of common bean (Phaseolus vulgaris) caused by Rhizoctonia solani is among the most important soil-borne fungal diseases worldwide. In this study, nine arbuscular mycorrhizal fungi (AMF) including Acaulospora longula, Funneliformis mosseae, Gigaspora margarita, Glomus caledonium, G. claroideum, G. etunicatum, G. fasciculatum, G. versiform and Rhizophagus irregularis were evaluated for their effect on some growth traits and inhibition of R. solani in bean plants under greenhouse conditions. Six AMF species (F. mosseae, G. claroideum, G. etunicatum, G. margarita, G. caledonium and G. versiform) significantly reduced the disease severity index and the first four of these also reduced the incidence of disease compared with the infected control. The lowest disease severity and incidence were obtained by F. mosseae and G. claroideum, respectively. Compared with the infected control, the root length was significantly improved by all AMF. The other growth traits were also significantly improved by all AMF species with some exceptions as follows: root wet and dry weights (except G. fasciculatum), shoot wet weight (excep G. versiform), shoot length (except G. claroideum, G. versiform and G. etunicatum) and shoot dry weight (except G. etunicatum, G. fasciculatum, G. caledonium and G. margarita). Glomus fasciculatum had the highest root colonization. According to the results of this study, many AMF fungi improved plant growth and partially compensated for Rhizoctonia root rot on common bean, and they could be considered as good candidates for studying the biological control of this disease under field conditions.
Dynamic changes in DNA methylation regulate the expression of genes and play important roles especially in the flowering processes of higher plants. Methyl-CpG-binding domain protein could specifically recognize hypermethylated regions in the genome, thus MBD sequencing technology and CpG islands analysis of the sequences were used to identify candidate genes that were regulated by DNA methylation, in particular the flowering induction stage of Chrysanthemum lavandulifolium. MBD-seq identified 89 candidate genes which included 49 genes exhibiting changes in DNA methylation status during floral induction. Based on CpG islands analysis of the sequences, 27 candidate genes were selected that may be regulated by DNA methylation. The expression levels of 30 candidate genes and nine key genes were determined by RT-PCR and qRT-PCR during floral induction (7D), four genes (ClFT, ClMET, DFL and ClWRKY21) were similarly up-regulated. Methylation-specific PCR analysis also indicated that there were changes in the DNA methylation status in the DFL and ClWRKY21. The changes in the DNA methylation status during the induction phase of flowering may lead to changes in gene expression. In this study, a set of genes were identified that are proposed to be involved in floral induction and two key genes were identified (DFL, ClWRKY21) that were regulated by DNA methylation during the flowering process of C. lavandulifolium.
Plant ecology, Environmental effects of industries and plants
AbstractThis study characterizes the growth conditions of Cypripedium japonicum Thunb. (Korean lady’s slipper), a rare and endangered plant, across three different sites in its natural habitat. The three natural habitats of C. japonicum had different canopy densities that influenced the relative light intensity and quality (R/FR ratio) on the forest floor, the values of which, decreased with the increase in canopy density. The leaf mass per area of C. japonicum increased with an increase in canopy openness, and the difference in growth due to increased light availability was further confirmed by the chlorophyll content. Higher values of the average daily photosynthetic activity, transpiration rate, and stomatal aperture were recorded in C. japonicum growing in natural habitats that received a higher frequency of sunflecks. The activities of the photosystem and carbon fixation of the plants growing in the three habitats were compared through the light-response and A–Ci curves, and it was found that their photosynthetic capacity decreased in a low light environment. The growth and physiological characteristics of C. japonicum growing in different habitats were dependent on the light conditions in the stand, and therefore, increasing the light availability by control of canopy density may improve the propagation of C. japonicum. We believe that the findings of our study will facilitate the prediction of population dynamics and the long-term conservation and restoration of C. japonicum.
Philip A. White, Michael F. Christensen, Henry Frye
et al.
The investigation of leaf-level traits in response to varying environmental conditions has immense importance for understanding plant ecology. Remote sensing technology enables measurement of the reflectance of plants to make inferences about underlying traits along environmental gradients. While much focus has been placed on understanding how reflectance and traits are related at the leaf-level, the challenge of modelling the dependence of this relationship along environmental gradients has limited this line of inquiry. Here, we take up the problem of jointly modeling traits and reflectance given environment. Our objective is to assess not only response to environmental regressors but also dependence between trait levels and the reflectance spectrum in the context of this regression. This leads to joint modeling of a response vector of traits with reflectance arising as a functional response over the wavelength spectrum. To conduct this investigation, we employ a dataset from a global biodiversity hotspot, the Greater Cape Floristic Region in South Africa.
Polyculture farming has environmental advantages but requires substantially more pruning than monoculture farming. We present novel hardware and algorithms for automated pruning. Using an overhead camera to collect data from a physical scale garden testbed, the autonomous system utilizes a learned Plant Phenotyping convolutional neural network and a Bounding Disk Tracking algorithm to evaluate the individual plant distribution and estimate the state of the garden each day. From this garden state, AlphaGardenSim selects plants to autonomously prune. A trained neural network detects and targets specific prune points on the plant. Two custom-designed pruning tools, compatible with a FarmBot gantry system, are experimentally evaluated and execute autonomous cuts through controlled algorithms. We present results for four 60-day garden cycles. Results suggest the system can autonomously achieve 0.94 normalized plant diversity with pruning shears while maintaining an average canopy coverage of 0.84 by the end of the cycles. For code, videos, and datasets, see https://sites.google.com/berkeley.edu/pruningpolyculture.