Plant Level Research Articles

An automatic 3D tomato plant stemwork phenotyping pipeline at internode level based on tree quantitative structural modelling algorithm

Phenotypic traits of stemwork are important indicators of plant growing status, contributing to multiple research domains including yield estimation, breeding engineering, and disease control. Traditional plant phenotyping with human work faces serious bottlenecks on labour intensity and time consumption. In recent years, the application of Quantitative Structural Modeling (QSM) together with three-dimensional (3D) sensor-based data acquisition techniques provides a feasible solution towards the automatic stemwork phenotyping. Nevertheless, existing QSM-based pipelines are sensitive towards the point cloud quality, and mostly focus on the phenotyping at plant or organ level. Information at internode level which are closely related to photosynthesis and light absorption was generally overlooked. To this end, a 3D automatic stemwork phenotyping pipeline is developed for tomato plants at both plant and internode level. Coloured point clouds are taken as the sensor input of the pipeline. A semantic segmentation based on PointNet++ was used to detect and localise the stemwork points. To improve the quality of the segmented stemwork point clouds, a density-based refining pipeline is proposed containing three main processes: non-replacement resampling, interference branch removal, and noise removal. A Tree Quantitative Structural Modeling (TreeQSM) algorithm was then applied to the stemwork point cloud to construct a digital reconstruction. The target phenotypic traits were finally calculated from the digital model by employing an internode association process. The proposed phenotyping pipeline was evaluated with a test dataset containing three tomato plant cultivars: Merlice, Brioso, and Gardener Delight. The related rooted mean squared errors of calculated internode length, internode diameters, leaf branching angle, leaf phyllotactic angle, and stem length range from 4.8 to 64.4%. Considering the time consuming manual phenotyping process, the proposed work provides a feasible solution towards the high throughput plant phenotyping, from which facilitates the related research on plant breeding and crop management.

Student Attendance, Study Activities, Major, and Midterm Grades as Predictors of Final Course Grades of Undergraduate and Graduate Plant Materials Courses during the Eras before and after COVID-19

Data were collected from four plant materials courses over the span of 20 years. Two classes were at the undergraduate level, Trees and Shrubs for Sustainable Built Environments (HORT 306) and Plants for Sustainable Landscapes (HORT 308), and two classes were at the graduate level, Plants for Landscape Design (HORT 608) and Plants for Landscape Design II (HORT 609). Data from these courses were analyzed to determine trends in student performance and benchmarks that might be associated with student success. Data included student enrollment, midterm course grades, final course grades, number of unexcused absences, student-reported study times for various activities, student major, student experience (class rank), whether the courses were required, and perceived difficulty levels of the courses. Trends in grade distributions were fairly stable until the last 3 to 4 years before COVID-19, when mean final grades and the frequencies of A or B grades increased. Midterm grades were strongly positively correlated with final course grades across majors in all four courses before COVID-19 (R2 = 0.90, 0.74, 0.72, and 0.54 for HORT 306, HORT 308, HORT 608, and HORT 609, respectively; P ≤ 0.001) and continued to be positively correlated after COVID-19. The number of unexcused absences was negatively significantly correlated with final course grades across majors (R2 = −0.69, −0.63, −0.21, and −0.45 for HORT 306, HORT 308, HORT 608, and HORT 609, respectively) before COVID-19 (P ≤ 0.001) and continued to be similarly correlated after COVID-19. Fewer reductions from midterm to final grades were observed for fall courses than for spring courses, particularly for seniors. Self-reported time spent studying all aspects of the courses was either not significantly correlated (P ≤ 0.05) or surprisingly slightly negatively correlated with the final course grades for all four courses. Perceptions of courses as moderately difficult (range, 7.0–8.0 out of 10.0) were remarkably stable overall but varied considerably by major (range, 5.0–8.3) and experience (range, 7.5 for seniors to 8.1 for freshman). More than 96% of enrollment in the graduate courses both before and after COVID-19 comprised Horticulture and Landscape Architecture majors, whereas undergraduate enrollment included a wide diversity of majors; however, the majority of those students were horticulture or landscape architecture majors. Biological science students or students who were architectural design majors were the top-performing students in both undergraduate courses, whereas undeclared majors, social science majors, and those in probationary major categories were among the lower-performing students in both undergraduate courses.

Identifying climate-ready plant for urban environment: Integrating machine learning with traditional plant selection tools

Climate change has intensified the urban heat island effect and increased extreme weather conditions, posing risks to public health and urban vegetation. To address these challenges, selecting climate-ready urban plant species is crucial. Traditional climate niche-based methods often fall short in urban contexts due to neglecting anthropogenic factors. Our study addresses this research gap by introducing an innovative urban plant selection method that integrates vulnerability metrics, expert consensus, and plant introduction records through machine learning.We identified eight climatic variables essential for the survival of urban plants in Beijing, China, and established safety margins for eight climate variables of 1,070 urban plant species across two periods: the baseline (1981-2010) and the future (2041-2070). Based on existing assessment data, expert consensus and plant introduction records, 247 plant species were classified into three levels of adaptability: backbone (highly adaptable, prevalent in Beijing), general (moderately adaptable, requiring specific care), and maladapted (poorly adaptable). Subsequently, we investigated the dynamic relationship between safety margins for eight climate variables across two time periods and the adaptability levels of plants by constructing an optimal machine learning model to predict urban plant adaptability levels, enhancing its accuracy through model comparisons and hyperparameter tuning.Our findings indicate that nearly half (49.0%) of the plant species in Beijing may face reduced adaptability to future climate conditions. However, a majority (75.9%) perform well under baseline climate conditions and are expected to adapt to future climate conditions. The results reaffirm that the species can grow well out of the niche limit, suggesting that the traditional climate niche-based method may be limited in urban contexts. Our approach overcomes the limitations of binary classification of traditional niche-based methods and the neglect of anthropogenic factors by incorporating an urban plant adaptability classification schema and ground truth derived from expert consensus and records of plant introductions through machine learning methods. This study provides a method for selecting climate-ready plant species for urban environments and supports evidence-based urban forestry management amidst climate change.

Impact of Cow Urine and Substrate Composition on Germination and Early Growth of Papaya (Carica papaya L.) Seedlings

Aim: This study evaluates the impact of cow urine and substrate composition on the germination and early growth of papaya (Carica papaya L.) seedlings, a critical phase for successful crop establishment. Study Design and Methodology: Conducted as a factorial experiment, it assessed eleven substrate or growing media combinations with and without cow urine treatment. Results: Results reveal that cow urine significantly reduces the time to 90 percent germination (T90) and enhances the germination index, indicating its stimulatory effect on seed metabolic activity. Treatments combining cow urine with substrates like soil, sand, vermiculite, cocopeat, and perlite (T10) showed the shortest T90 and highest germination index, suggesting cow urine accelerates germination. Additionally, cow urine application improved growth metrics such as relative growth rate (RGR) and total biomass accumulation, with T10 and T8 treatments yielding the highest values. Enhanced leaf relative water content (LRWC) and elevated proline levels in cow urine-treated plants indicate better water retention and stress resilience. Strong positive correlations were observed among proline content, RGR, and biomass accumulation, highlighting cow urine’s contribution to vigorous seedling growth and stress adaptation. Conclusion: The findings suggest that cow urine, in combination with optimized substrates, is a sustainable growth enhancer that promotes robust seedling development, suitable for organic farming practices aimed at papaya cultivation.

The biosynthesis and impacts of cytokinins on growth of the oyster mushroom, Pleurotus ostreatus

ABSTRACT While a lot is known about cytokinins (CKs) and their actions at the molecular and cellular levels in plants, much less is known about the function of CKs in other kingdoms such as fungi. CKs have been detected in a wide range of fungal species where they play roles ranging from enhancing the virulence of phytopathogens to fortifying plant growth when secreted from fungal symbionts. However, the role of CKs where they concern fungal physiology, apart from plant associations, remains largely uncharacterized. Profiling by UHPLC-HRMS/MS (ultrahigh-performance liquid chromatography–high-resolution tandem mass spectrometry) revealed that Pleurotus ostreatus (oyster mushroom) produces CKs in vitro in both liquid and solid cultures. During fungal growth, CK profiling patterns were consistent with previous suggestions that tRNA degradation products might play a role in the physiological development of fungi. It confirms that those products are CKs that act as fungal growth regulators. Moreover, P. ostreatus was shown to respond to exogenous applications of aromatic and isoprenoid CKs, and their effects were dependent on the dose and CK type in a biphasic manner consistent with hormone action. N 6-benzyladenine (BAP), kinetin (KIN), N 6-isopentenyladenine (iP), and trans-zeatin (tZ) bioassays all revealed hormesis-type responses. Accordingly, at low doses, mycelium colony diameter, biomass accumulation, and changes in morphology were stimulated, whereas at high doses only inhibitory effects were observed. Thus, CKs may act as “mycohormones” and consequently have potential for applications in fungal agriculture and medicinal compound production.

Optimization of crop tissue culture technology and its impact on biomolecular characteristics

Modern agriculture relies on crop tissue culture technology for fast propagation, genetic improvement, and protection of plant species. Conventional media like Murashige and Skoog (MS) usually lack optimal conditions for embryogenesis, necessitating the development of improved media tailored to specific crop requirements. In this article, we introduce an Efficient Grid Identified-Deep Feedforward Neurons (EGI-DFFN) to identify the ideal nutrient and vitamin levels of the crop plants for improving crop tissue culture aimed to improve crop plant growth in a lab setting by predicting callogenesis rate (CGR), embryogenesis rate (EGR), and somatic embryo number (SEN), shoot regeneration rate (SRR), rooting rate (RR).Different concentrations of ionic macronutrients, bio-molecular, and vitamins of the crop plant are the input to the predictive model, which is collected through the laboratory Callus Induction Experiment (CIE). Z-score normalization is used to preprocessing the CIE data to ensure consistent scales across different input features and improve model training performance. DFFN used discriminates to predict complex relationships and interactions between CGR, EGR, SEN, SRR, and RR with EGI tuning. The EGI-DFFN model has significantly improved crop tissue culture growth by accurately predicting the CGR, EGR, SEN, SRR, and RR respectively. The EGI-DFFN model enhances understanding of how ionic macronutrients and vitamins impact plant growth. It identifies optimal concentrations of the biomolecular to enhance somatic embryo formation and plantlet development, providing insights for optimizing crop tissue culture conditions for optimal growth outcomes.

ABSORPTION REFRIGERATION SYSTEMS FOR WASTE HEAT RECOVERY AT THE SILICATE INDUSTRY

The glass, ceramic and cement plants are energy intensive industrial systems, releasing high amounts of greenhouse gases. The dissipation of the waste heat reduces their profitability, energy and ecological efficiency. The absorption refrigeration systems are successful solutions for the recovery of thermal energy at different temperature levels to obtain useful cooling and heating powers for technological needs, and for air conditioning of administrative and industrial buildings. Although the absorption units in a heat pump and refrigeration cycle are currently used in building and industrial systems, they have not yet penetrated widely into the silicate factories. This paper discusses possibilities for the applications of basic types of absorption cycles at heat pump and refrigeration modes to utilize waste energy at different temperature levels in glass, ceramic and cement plants. The examined variants are demonstrated via examples, diagrams and analyses of the possible energy saving.

SlMIPS2, a myo-inositol phosphate synthase gene, regulates phosphate homeostasis by influencing SlPHL1 and SlSPX2 levels in tomato seedlings.

Phosphorus (P) is a quintessential macronutrient utilized by plants to support various metabolic processes during growth and development. Recent studies have revealed the pivotal role of inositol hexa-kis/pyrophosphate (InsP6-8), the derivatives of Myo-inositol (MI), in facilitating the interaction between SYG1/PHO81/XPR1 (SPX) and Phosphate starvation response (PHR) proteins. Myo-inositol phosphate synthase (MIPS) catalyzes the first committed step in MI biosynthesis. Although the role of MIPS genes in mediating stress responses in plants is well elucidated, its role in phosphate (Pi) deficiency remains largely unexplored. This study demonstrates that out of the five MIPS genes encoded by the tomato genome, only SlMIPS2 is sharply induced at an early stage of Pi starvation in tomato seedlings. Silencing of SlMIPS2 led to improved seedling growth with enhanced total soluble Pi and total P levels in the silenced plants under high Pi availability. SlMIPS2 silencing also caused a significant reduction in MI and InsP6 content in the tomato seedlings. These seedlings with depleted InsP6 levels accumulated lower levels of SlSPX2 protein. In contrast, stabilized SlPHL1 levels were noticed in these plants, directly implicating this transcription factor in activating phosphate starvation inducible (PSI) genes in the SlMIPS2-silenced seedlings, even under high Pi conditions. The results assign a novel role to SlMIPS2 in regulating cellular InsP6 levels and SPX-PHR interactions to control Pi homeostasis in tomato seedlings.

Nitrogen Stress Memory in Quinoa: Maternal Effects on Seed Metabolism and Offspring Growth and Physiology.

Plants have developed various strategies to deal with abiotic stresses throughout their lifetimes. However, environmental stresses can have long-lasting effects, positively modifying plant physiological responses to subsequent stress episodes, a phenomenon known as preconditioning or stress memory. Intriguingly, this memory can even be transmitted to offspring, referred to as "inter- or transgenerational memory". Chenopodium quinoa is a pseudocereal that can withstand several abiotic stresses, including nitrogen (N) limitation. This research highlights the critical role of maternal N conditions in shaping the physiological and metabolic responses of their offspring. Mother quinoa plants (F0) were grown under High N (HN) or Low N (LN) conditions. LNF0 plants exhibited lower panicle biomass, net photosynthesis, and yield compared to HNF0 plants. Seeds from LNF0 retained proteins, reduced amino acids' levels, and increased lipids (such as PI 34:2), especially phosphatidylcholines, and their unsaturation level, which was associated with faster germination compared to HNF0 seeds. Offsprings seedlings (F1) grown under either HN or LN had similar proteins and amino acid proportions of their seeds. However, LNF0LNF1 seedlings displayed significantly higher biomass and number of root tips. These changes were significantly correlated with transpiration, net photosynthesis, and stomatal conductance, as well as with starch content, suggesting higher CO2 fixation at the whole plant level in LNF0LNF1 plants. Our findings suggest that quinoa transmits maternal environmental stress information to its offspring, modulating their resilience. This work underscores the potential of utilizing maternal environmental conditions as a natural priming tool to enhance crop resilience against nutritional stress.

Developing and applying a virus-induced gene silencing system for functional genomics in walnut (Juglans regia L.) mediated by tobacco rattle virus.

Walnut (Juglans regia L.) is a high-value tree species planted worldwide, but the incomplete less developed genetic transformation system limits its gene function analysis. In this study, virus-induced gene silencing (VIGS) mediated by tobacco rattle virus (TRV) technology was applied to walnut seedlings to degrade the transcript of target gene. Different infiltration methods were used to explore the effects of infection mode, Agrobacterium cell density, silencing fragment length, and walnut cultivars. The results showed that spray infiltration of seedlings resulted in a photobleaching phenotype of the whole plant. Leaf injection was a more effective way of infiltration. The optimal combination was the Agrobacterium cell density at OD600 = 1.1 with target fragment = 255 bp for the treatment of walnut early-fruiting cultivar 'Xiangling.' This combination can reach up to 48 % of gene silencing efficiency. Based on this optimized VIGS system, silencing a walnut chlorophyll synthesis-related gene, JrPOR (Protochlorophyllide reductase), to further validate the system's effect. The results showed that the expression of JrPOR was significantly repressed, and the chlorophyll level of the silenced plants was significantly decreased compared with the control. The above results indicate that the walnut TRV-VIGS system has been successfully established and can be used for reverse genetic studies, providing an option for verifying gene function in walnut.

Optimizing spatial distribution of wastewater-based disease surveillance to advance health equity

In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based epidemiology (WBE) beyond COVID-19. WBE is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion from this initiative is the critical importance of maintaining equity and expanding access to fully realize the benefits of wastewater surveillance for marginalized communities. To address this need, we propose an optimization framework that strategically allocates wastewater monitoring resources at the wastewater treatment plant (WWTP) level, ensuring more effective and equitable distribution of surveillance efforts to serve underserved populations.The purpose of the framework is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of disadvantaged groups in the allocation of resources for WBE. Furthermore, the framework concentrates on areas with high population density and gives priority to vulnerable regions, as well as identifying signals that display significant variations from other monitored sources. The optimization objective is to maximize a weighted combination of these critical factors. This problem is formulated as an integer optimization problem and solved using simulated annealing. We evaluate various scenarios, considering different weighting factors, to optimize the allocation of WWTPs with monitoring systems. This optimization framework provides an opportunity to enhance WBE by providing customized monitoring strategies created to address specific priorities and situations, thus enhancing the decision-making processes in public health responses.

Mechanized Transplanting Improves Yield and Reduces Pyricularia oryzae Incidence of Paddies in Calasparra Rice of Origin in Spain

The rice variety Bomba is grown in Calasparra—a rice of origin in southeast Spain—resulting in a product with excellent cooking quality, although its profitability has declined in recent years due to low grain yields and susceptibility to rice blast disease (Pyricularia oryzae Cavara). An innovation project to test the efficacy of mechanized transplanting against traditional direct seed sowing was conducted in 2022 and 2023 at four locations for the first time. A lower plant density (67–82 plants m−2) and shorter plants with higher leaf nitrogen content were observed in transplanted plots compared with seed sowing (130–137 plants m−2) in the first year. The optimal climatic conditions for P. oryzae symptom appearance were determined as temperatures of 25–29 °C and a 50–77% relative humidity. The most-affected sowing plots presented 3–20% leaf area damage and a reduction in yield to values of 1.5 t ha−1 in the first year and 2.12 t ha−1 in the second year. In transplanted plots, there was generally less humidity at the plant level and therefore, disease incidence was low in both seasons. Grain yields did not significantly differ among the treatments studied; however, there were differences in the yield components of panicle density and the number of grains for panicles. Principal component analysis revealed two principal components that explained 81% of the variability. Variables related to yield contributed positively to the first component, while plant biomass variables contributed to the second component. Plant density, tiller density, and panicle density were found to be positively correlated (r > 0.81 ***). Overall, transplanting (frame of 30 × 15–18 cm2) resulted in uniform crop growth with less rice blast disease, as well as higher grain yields (2.92–3.89 t ha−1), in comparison with the average for the whole D.O. Calasparra (2.3–2.5 t ha−1) in both seasons and a good percentage of whole grains at milling. This is novel knowledge which can be considered useful for farmers operating in the region.

Zinc oxide nanoparticles at low dose mitigate lead toxicity in pea (Pisum sativum L.) seeds during germination by modulating metabolic and cellular defense systems

Addressing lead (Pb) pollution and contamination in soil and agriculture is urgent due to its widespread and long-lasting impacts on human health, food safety, and the environment. In the current study, we assessed the potential use of Zinc oxide nanoparticles (ZnONPs) in alleviating Pb toxicity in germinating seedlings. Pea (Pisum sativum L.) seedlings were exposed to Pb (83 mg/L) over a 7-day period, without and with ZnONPs amendment. Our results showed that the application of ZnONPs at 10 mg/L restored the morphological parameters affected by Pb, 34 %, 26 % and 23 %, for the length, fresh, and dry biomass of embryonic axis, respectively. ZnONPs decreased the activities of antioxidative enzymes of catalase (87.5 %), guaiacol peroxidase (60 %), and glutathione peroxidase (25 %), but increased the activities of ascorbate peroxidase (60 %) and glutathione reductase (25 %). These changes were associated with the increase (7 %) in the thiol groups, and reductions in the malondialdehyde (23 %), hydrogen peroxide (33 %), and carbonyl group levels (78 %), in addition to the stimulation of the activities of ROS-associated enzymes, including glycolate oxidase (40 %) and NADPH oxidase (by 89 %). Consequently, cell viability was increased by 66 %, while cellular death was reduced by 10 %, with ZnONPs, relative to the Pb-stressed seedlings. These findings highlight the mechanisms surrounding the ability of nanosized ZnO to mitigate the harmful effects of Pb on the growth and physiology of plants. Further investigation is needed to understand the mitigating effects of ZnONPs on Pb on the molecular and genomic levels in seedlings and plants, and ensure the sustainability of agricultural practices and food safety. Besides, site and source-specific integrated approaches must be practiced to formulate suitable remediation strategies.

Precision crop mapping: within plant canopy discrimination of crop and soil using multi-sensor hyperspectral imagery

Leveraging diverse optomechanical and imaging technologies for precision agriculture applications is gaining attention in emerging economies. The precise spatial detection of plant objects in farms is crucial for optimizing plant-level nutrition and managing pests and diseases. High-resolution remote sensors mounted on drones have been increasingly deployed for large-scale crop mapping and field variability characterization. While field-level crop identification and crop-soil discrimination have been studied extensively, within-plant canopy discrimination of crop and soil has not been explored in real agricultural farms. The objectives of this study are: (i) adoption and assessment of spectral unmixing for discriminating crop and soil at within-plant canopy level, and (ii) generation of benchmark terrestrial and drone-based hyperspectral datasets for plant or sub-plant level discrimination using various spectral mixture modelling approaches and sources of endmembers. We acquired hyperspectral imagery of vegetable crops using a frame-based sensor mounted on a drone flying at different heights. Further, several linear, non-linear, and sparse-based spectral unmixing methods were used to discriminate plant and soil based on spectral signatures (endmembers) extracted from different spectral libraries prepared using in situ or field, ground-based, and drone-based hyperspectral imagery. The results, validated against pixel-to-pixel ground truth data, indicate an overall crop-soil discrimination accuracy of 99–100%, subject to a combination of endmember source and flying height. The influences of different endmember sources, spatial resolution as indicated by flying height, and inversion algorithms on the quality of estimated abundances are assessed from a verifiable and functionally relevant perspective. The generated hyperspectral datasets and ground truth data can be used for developing and testing new methods for sub-canopy level soil-crop discrimination in various agricultural applications of remote sensing.

Evaluating the effects of rice husk derived nanosilica on growth, photosynthesis, and antioxidant activity in hybrid maize

Drought stress was exacerbated by changing climatic conditions and impact the plant water relations from the cellular to whole plant level, thereby reducing the crop productivity and causing economic losses in agriculture. The present study was aimed to explore the potentials of nanosilica synthesized from rice husk in improving growth and drought stress tolerance in maize. Synthesized nanosilica from rice husk has spherical morphology, amorphous structure, siloxane bonding and higher purity (99.1 %). Soil application of varied levels of synthesized nanosilica (0, 5, 10, 15, 20, 30 and 40 mg kg−1) was tested with hybrid maize plants grown under irrigated and drought stress (100 and 50 % field capacity, respectively). The results of the study revealed that, drought stress has adverse effect on plant growth, biomass production and physiological parameters. However soil application of nanosilica has significantly improved growth, physiological and biochemical attributes of both irrigated and drought stressed plants. Nanosilica application at 20 mg kg−1 for irrigated and 30 mg kg−1 for drought stressed hybrid maize plants has recorded higher plant height, biomass, chlorophyll a, chlorophyll b, superoxide dismutase, peroxidase, phenols, soluble proteins and considerably decreased the proline, electrolyte leakage and melondialdehyde content in hybrid maize. In contrary, higher doses of nanosilica (>30 mg kg−1) caused a slight reduction in plant growth and antioxidant activity under both the water regimes. Hence, we conclude that, soil application of 20 and 30 mg kg−1 nanosilica synthesized from rice husk had a positive effect on plant growth and development besides aided in mitigating drought stress.

Agrophysiological responses of bread wheat to raised-bed planting and irrigation level

ABSTRACT To investigate the response of wheat to drought stress under different plantation systems, two field experiments were carried out in 2021/22 and 2022/23 in Arsanjan. The main plot was three different plantation systems (flat planting, 60-cm raised beds, and 120-cm raised beds) and the subplots were irrigation levels at 100% (control), 80% (medium stress), and 60% (severe stress) of crop evapotranspiration. The results showed that the raised-bed planting increased grain yield by 22.1 and 25.9% compared to flat cultivation in the first and second years, respectively. This increase in the biological yield was about 17%, the number of ears was 7%, and the number of seeds per ear was 21%. Drought stress caused a significant decrease in grain yield (46.4%), number of ears (20.5%), seed number (30.3%), biological yield (45.9%), chlorophyll a (31.8%), chlorophyll b (28.1%) and relative water content (5.3%) and increased, proline content (24.3%), and ion leakage (147.3%). The decrease in yield due to drought stress was moderated in the raised-bed system and therefore cultivation on the raised-bed is suggested as a suitable planting pattern to improve the yield and water efficiency in wheat under conditions similar to the experimental area, especially under water shortage conditions.

Root-specific theanine metabolism and regulation at the single-cell level in tea plants (Camellia sinensis)

Root-synthesized secondary metabolites are critical quality-conferring compounds of foods, plant-derived medicines, and beverages. However, information at a single-cell level on root-specific secondary metabolism remains largely unexplored. L-Theanine, an important quality component of tea, is primarily synthesized in roots, from which it is then transported to new shoots of tea plant. In this study, we present a single-cell RNA sequencing (scRNA-seq)-derived map for the tea plant root, which enabled cell-type-specific analysis of glutamate and ethylamine (two precursors of theanine biosynthesis) metabolism, and theanine biosynthesis, storage, and transport. Our findings support a model in which the theanine biosynthesis pathway occurs via multicellular compartmentation and does not require high co-expression levels of transcription factors and their target genes within the same cell cluster. This study provides novel insights into theanine metabolism and regulation, at the single-cell level, and offers an example for studying root-specific secondary metabolism in other plant systems.

Transcription factor PdMYB118 in poplar regulates lignin deposition and xylem differentiation in addition to anthocyanin synthesis through suppressing the expression of PagKNAT2/6b gene

R2R3-MYB transcription factors function as the master regulators of the phenylpropanoid pathway in which both lignin and anthocyanin are produced. In poplar, R2R3-MYB transcription factor PdMYB118 positively regulates anthocyanin production to change leaf color. However, the molecular mechanism by which it controls different branches of the phenylpropanoid pathway still remains poorly understood. Here, we reported that in addition to anthocyanin synthesis, lignin deposition and xylem differentiation were regulated by PdMYB118 through inhibiting PagKNAT2/6b gene expression. The transgenic poplar plants overexpressing PdMYB118 accumulated more xylem, lignin and anthocyanin. Transcriptome and reverse transcription quantitative PCR analyses revealed that the expression of PagKNAT2/6b gene which inhibited lignin deposition and xylem differentiation was significantly down-regulated in transgenic poplar plants. Subsequent dual-luciferase reporter and yeast-one-hybrid assays demonstrated that PdMYB118 directly inhibited the transcription of PagKNAT2/6b by binding to the AC elements in its promoter region. Further experiments with transgenic poplar plants overexpressing PagKNAT2/6b demonstrated that overexpression of PagKNAT2/6b in the PdMYB118 overexpression background rescued lignin accumulation and xylem width to the same level of wild type plants. The findings in this work suggest that PdMYB118 is involved in the lignin deposition and xylem differentiation via modulating the expression of PagKNAT2/6b, and the PdMYB118- PagKNAT2/6b model can be used for the genetic breeding of new woody tree with high lignin production.

How Do Short-Term Incentives Affect Long-Term Productivity?

Abstract Previous research shows that incentives to meet short-term earnings targets can cause firms to increase share buybacks, leading to cuts in investments and employment. Using plant-level census data, we find that incentives to engage in earnings-per-sharemotivated buybacks result in lower productivity at both the plant and firm level. We attribute this productivity drop to two mechanisms: reduced investment in productivityaugmenting technology, and inefficient allocation of resources across a firm’s plants. We identify multiple frictions—including labor unions, financial constraints, agency problems, and adjustment costs—that can constrain efficient reallocations across plants and thus exacerbate the consequences of firms’ short-term incentives. (JEL G32, G35, J23).

The Effect of Plant Growth-Promoting Bacteria Bacillus subtilis IB-22 on the Hydraulic Conductivity and Abundance of PIP2 Aquaporins in the Roots of an Abscisic Acid-Deficient Barley Mutant.

Little information is available on how rhizosphere bacteria affect abscisic acid (ABA) levels in plants and whether these bacterial effects are associated with improved plant water status. In this study, we tested the hypothesis that the stimulation of plant growth may be associated with the ability of ABA to increase the hydraulic conductivity of roots through the up-regulation of aquaporin. To do this, we studied the effect of bacteria capable of producing ABA on a barley mutant deficient in this hormone. Measurements of hydraulic conductivity of the ABA-deficient barley mutant Az34 showed that its tissues exhibited a reduced ability to conduct water, which correlated with lower ABA content in plants. The inoculation of Bacillus subtilis IB-22 stimulated the growth of both the mutant and its parent variety. Also, under the influence of bacteria, the ABA content in plants increased, and the increase was more significant in the mutant. This effect was accompanied by an increase in hydraulic conductivity in the roots of the ABA-deficient mutant, and immunolocalization using antibodies against PIP2;1 and PIP2;2 aquaporins revealed an increase in their abundance. Thus, the results obtained support the hypothesis about the importance of a sufficiently high ABA content in plants to maintain the abundance of aquaporins, hydraulic conductivity and the growth of barley plants.