Plant Growth Stages Research Articles

Recent progress in the role of seed endophytic bacteria as plant growth-promoting microorganisms and biocontrol agents.

The importance of microorganisms residing within the host plant for their growth and health is increasingly acknowledged, yet the significance of microbes associated with seeds, particularly seed endophytic bacteria, remains underestimated. Seeds harbor a wide range of bacteria that can boost the growth and resilience of their host plants against environmental challenges. These endophytic associations also offer advantages for germination and seedling establishment, as seed endophytic bacteria are present during the initial stages of plant growth and development. Furthermore, plants can selectively choose bacteria possessing beneficial traits, which are subsequently transmitted through seeds to confer benefits to future generations. Interestingly, even with the ongoing discovery of endophytes in seeds through high-throughput sequencing methods, certain endophytes remain challenging to isolate and culture from seeds, despite their high abundance. These challenges pose difficulties in studying seed endophytes, making many of their effects on plants unclear. In this article, a framework for understanding the assembly and function of seed endophytes, including their sources and colonization processes was outlined in detail and available research on bacterial endophytes discovered within the seeds of various plant species has also been explored. Thus, this current review aims to provide valuable insights into the mechanism of underlying seed endophytic bacteria-host plant interactions and offers significant recommendations for utilizing the seed endophytic bacteria in sustainable agriculture as plant growth promoters and enhancers of environmental stress tolerance.

Aquaporins: Multifunctional Players in Plant Growth, Development and Stress Responses

Aquaporins are small membrane proteins belonging to the group of Major Intrinsic proteins (MIPs) that facilitate the transport of water and small molecules across biological membranes. They were initially identified as water channels and later it has become clear that they also play important roles in several other physiological processes in plants. Plants have different types of aquaporins in terms of their location, gating properties, and solute specificity and can mainly divide into four major subfamilies. They are tonoplast intrinsic proteins (TIPs), nodulin26-like intrinsic proteins (NIPs), plasma membrane intrinsic proteins (PIPs), and the small basic intrinsic proteins (SIPs). All these aquaporins play a variety of physiological activities at all stages of plant growth and development. Also, they are believed to play a significant part in the plant’s defense mechanisms against biotic and abiotic stresses. This review comprehensively addresses the roles of diverse aquaporin homologs in growth and development and their response to different environmental factors.

Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Collaborative Impact of Inorganic and Organic Fertilizers Coupled with Kappaphycus alvarezii Bio-stimulant on the Quality Characteristics of Wheat (Triticum aestivum L.)

The study investigates the influence of different factors on the nutritional content of wheat grains, focusing on crude protein, nitrogen, phosphorus, and potassium contents in grain. Results indicate that varying combinations of factors such as NPK fertilization, farmyard manure (FYM) application, and bio-stimulant usage significantly affect nutrient concentrations in grain. Crude protein content, a vital indicator of grain quality, showed variability across the different treatments, with the highest levels observed in plots receiving RDF @100% + FYM@16.5 t ha-1 + SWBS@1250 ml ha-1. The crude protein content primarily relies on the nitrogen levels. In the research, the findings indicated that the nitrogen content was significant, which, in turn, led to a significant crude protein content. The levels of nitrogen, phosphorus, and potassium content also exhibited fluctuations, with significant interactions observed among various factors. These fluctuations are attributed to differences in nutrient uptake and utilization during the different growth stages of the wheat plant. All three factors can enhance the nutrient uptake facilities through soil as well as plant body, therefore, notably, interactions between NPK, FYM, and bio-stimulants exhibited significant effects on nutrient content, particularly at the 0.05 significance level. The findings underscore the importance of holistic agricultural management in enhancing the nutritional value of wheat grains, with implications for food security and agricultural sustainability.

Exploring cannabidiol variations, investigation of genetic diversity, population structure and unveiling male-specific genetic marker in industrial hemp (Cannabis sativa L.)

AbstractCannabis sativa played a pivotal role across different industries. Recently, industrial hemp, particularly in the case of Cannabidiol (CBD), gained attention for its therapeutic potential. This study evaluated cannabinoid variability and genetic diversity within 43 industrial hemp individuals, primarily Turkish, across various plant parts and growth stages, and inflorescences of females showed significant CBD content. The highest contents were observed in Turkish landraces (0.55–8.05% with an average of 3.26%), making them valuable genetic resources for high CBD. Genetic structure revealed distinct populations based on gender and influenced by geographical origin. Analysis of Molecular Variance showed 92% of genetic variation observed within populations and indicated a promising source of novel allelic diversity in the Turkish gene pool. Turkish females showed significant genetic diversity [No. of Different Alleles (Na) 1.507, No. of Effective Alleles (Ne) 1.226, Shannon’s Information Index (I) 0.258, and Percentage of Polymorphic Loc (%P) 74.91], exhibiting richer genetic variation than their international peers. Principal Coordinate Analysis unveiled gender-specific genetic differences, and admixture clusters shed light on genetic interactions and historical connections among diverse populations. Unweighted Pair-Group Method with Arithmetic Averaging highlighted unique genetic profiles and distinct genetic lineages. Genome-wide association study revealed a highly significant male-specific genetic marker explained 50% of the phenotypic variation. These findings inform future breeding strategies and conservation efforts and contribute to varietal identification methods, Marker-Assisted Selection, and efficient cultivar development in upcoming programs.

Case study: reducing heating energy consumption in a high tunnel greenhouse with renewable energy and microclimate control by bench-top root-zone heating, bench covers, and under-bench insulation

Appalachian State University's Nexus project designed an efficient greenhouse heating system that integrated renewable energy and root zone heating technology to reduce the greenhouse heating energy burden on local farmers and installed it at local cooperative farms. This study analyzed 5 years of data from 2018 to 2022 to investigate the energy savings and microclimate control effectiveness of the Nexus heating system installed at Springhouse Farm in North Carolina, USA. By varying bench cover materials, bottom insulation, and the number of loops of root zone tubing, the different soil temperatures required for plant types and growth stages were achieved with a single temperature controller. A root zone heating fluid of 32.2 ℃ satisfactorily maintained the germination soil between 20 and 25 ℃ in March 2019 with an average outside temperature of 4.8 ℃ and an average low temperature of − 0.4 ℃. Growing soil maintained an average temperature of 15 ℃ with bottom insulation and an average of 11–12 ℃ without bottom insulation. Compared to the conventional heating system (a forced-air propane unit heater alone), weather-adjusted propane consumption (propane usage divided by heating degree days) was reduced by 65% with the Nexus system alone and 45% with the Nexus system and unit heater together. It shows that the Nexus system has significantly reduced greenhouse heating energy consumption and maintained productive conditions. The renewable energy fraction ranged only 9–13% of the total thermal energy used due to the high inlet temperature entering the solar thermal collector. This can be improved by separating the heat storage and backup heat source.

Seasonal coupling of iron (hydr-) oxides and organic carbon across elevations in Phragmites marshes of Yangtze Estuary

As sea levels rise, coastal tidal wetlands are increasingly threatened by flooding and salt stress, highlighting the importance of iron (Fe) (hydr-) oxides in soil for stabilizing organic carbon (OC). This study focuses on Phragmites australis, common in the Yangtze River Estuary, exploring the interplay between OC and Fe (hydr-) oxides in the rhizosphere of P. australis across various seasons and elevations. It also examines microbial community shifts in the Fe oxidation–reduction cycle. Results show that in the non-growing season (January), Fe (hydr-) oxides and total organic carbon (TOC) levels in the rhizosphere soil of high-tide P. australis are significantly higher than during the growing season (August), with a notable increase in Fe oxide-bound OC (Fe-OC). The content of Fe-OC in tidal wetland soil fluctuates with plant growth stages and elevation. Notably, during the growing season, the Fe-OC content in the rhizosphere of low-tide P. australis is markedly higher than in high-tide areas, reversing in the non-growing season. The presence of P. australis roots is found to significantly enhance the accumulation and coupling of Fe (hydr-) oxides and OC, especially in low-tide areas compared to bare flats. This coupling is affected by the organic matter contributed by roots, microbial metabolism, and redox conditions of the soil. The study also highlights how plant and microbial metabolism regulate the response of rhizosphere Fe-OC across different tidal flat elevations. In low-tide environments during the non-growing season, the prevalence of Fe-reducing bacteria results in decreased Fe-OC content, while in high-tide areas, increased organic matter input boosts complexed Fe-OC formation. Overall, this study emphasizes the significance of plant metabolism in understanding the impact of sea level rise on Fe-OC stores in tidal wetlands, a vital factor for comprehending C cycling mechanisms and assessing C sequestration potential under future climate change scenarios.

Mapping of Leaf Rust Resistance Loci in Two Kenyan Wheats and Development of Linked Markers.

Leaf rust caused by the pathogen Puccinia triticina (Pt) is a destructive fungal disease of wheat that occurs in almost all wheat-growing areas across the globe. Genetic resistance has proven to be the best solution to mitigate the disease. Wheat breeders are continuously seeking new diversified and durable sources of resistance to use in developing new varieties. We developed recombinant inbred line (RIL) populations from two leaf rust-resistant genotypes (Kenya Kudu and AUS12568) introduced from Kenya to identify and characterize resistance to Pt and to develop markers linked closely to the resistance that was found. Our studies detected four QTL conferring adult plant resistance (APR) to leaf rust. Two of these loci are associated with known genes, Lr46 and Lr68, residing on chromosomes 1B and 7B, respectively. The remaining two, QLrKK_2B and QLrAus12568_5A, contributed by Kenya Kudu and AUS12568 respectively, are putatively new loci for Pt resistance. Both QLrKK_2B and QLrAus12568_5A were found to interact additively with Lr46 in significantly reducing the disease severity at adult plant growth stages in the field. We further developed a suite of six closely linked markers within the QLrAus12568_5A locus and four within the QLrKK_2B region. Among these, markers sunKASP_522 and sunKASP_524, flanking QLrAus12568_5A, and sunKASP_536, distal to QLrKK_2B, were identified as the most closely linked and reliable for marker-assisted selection. The markers were validated on a selection of 64 Australian wheat varieties and found to be polymorphic and robust, allowing for clear allelic discrimination. The identified new loci and linked molecular markers will enable rapid adoption by breeders in developing wheat varieties carrying diversified and durable resistance to leaf rust.

TESTING OF WHEAT GENOTYPES FOR SALT TOLERANCE AND LEAF RUST DISEASE CAUSED BY PUCCINIA

Parameters that show a significant genotypic variation and are associated with salt tolerance may be used as rapid and economic screening criteria in breeding programs. The objective of this study was to test growth and yield components for evaluating the salt tolerance of wheat genotypes. Five genotypes of winter wheat (Triticum aestivum L.) were used in this study, that differ from their salt tolerance, which were grown in 28 dS/m saline soil, and irrigated by well water with a salinity 7.5 dS/m. The results showed that salt concentration in the soil was reduced with plant growth stages from 28 dS/m before sowing to 8, 7.5, and 7.6 dS/m for N1, N2, and N3 genotypes, respectively. Whereas approached 16 and 17 dS/m for Tumos2 and Mexipak, cultivars, respectively, at the maturity stage. Concerning germination percentage under saline conditions, wheat genotypes N1, N2, and N3 showed the highest percentages of 89, 90, and 90%, respectively, which was significantly different than wheat cultivars Tumos2 and Mexipak 79 and 83%, respectively. Statistical analysis of the data revealed that genotype N2 required a maximum days for germination 14 days, whereas cultivarTumos2 required less days for germination 12 days. For spikes formation duration growth the genotype N3 was the late 119 days, whereas for physiological maturity N1 genotype was the latest 153 days. The number of spikes per 6 m2, grains spike-1, and grain weight were reduced significantly in sensitive cultivars Tumos2 and Mexipak. Higher grain yield with N2 genotype 2739.43 g with no significant differences with the genotypes N1 and N2, and with significant differences with the rest sensitive cultivars Tumos2 and Mexipak 346.61 and 242.98 g, respectively. Therefore, we conclude that the measurements of growth and yield components may be effective criteria for screening wheat genotypes for salt tolerance. Moreover, N1, N2, and N3 genotypes were identified as the most salt-tolerant genotypes in this study, they can be utilized through appropriate selection and breeding programs for further improvement in salt tolerance of Iraqi wheat genotypes.

Development of a Multiplex PCR Assay for the Detection of Tomato Wilt Caused by Coinfection of Fusarium brachygibbosum, Fusarium oxysporum, and Ralstonia solanacearum Based on Comparative Genomics.

Tomato is consumed worldwide as fresh or processed food products. However, soilborne diseases of tomato plants caused by coinfection of various pathogens result in great economic losses to the tomato industry. It is difficult to accurately identify and diagnose soilborne diseases of tomato plants caused by pathogen complexes. In this study, we investigated field diseases of tomato plants by pathogen isolation and molecular identification and found that tomato wilt was caused by coinfection of Fusarium brachygibbosum, F. oxysporum, and Ralstonia solanacearum. Therefore, developing a method for simultaneous detection of DNA from F. brachygibbosum, F. oxysporum, and R. solanacearum is of great importance to efficiently and accurately monitor disease development at different growth stages of tomato plants. In this study, we performed a comparative genomic analysis of F. brachygibbosum, F. oxysporum, and R. solanacearum and determined the primer sets for simultaneous detection of DNA from these target pathogens. Then, we tested the reagent and condition parameters of multiplex PCR, including primers, dNTP and Mg2+ concentrations, and annealing temperatures, to determine the optimal parameters of a multiplex PCR system. We evaluated the specificity, sensitivity, and stability of the multiplex PCR system based on the optimized reaction conditions. The multiplex PCR system can specifically identify 13 target pathogens from 57 different fungal and bacterial pathogens, at the lower detection limit of the three target pathogens at concentrations of 100 pg/μl. In addition, we can accurately identify the three pathogens in tomato plants using the optimized multiplex PCR method. These results demonstrated that the multiplex PCR method developed in this study can simultaneously detect DNA from F. brachygibbosum, F. oxysporum, and R. solanacearum in a single PCR system to accurately identify and diagnose the pathogen causing tomato wilt.

Drought priming enhances wheat grain starch and protein quality under drought stress during grain filling

The impact of drought stress on crop yield and quality is substantial. Drought priming during the early growth stage of plants has been shown to improve tolerance to drought stress during the reproductive stage, although its effects on grain quality remains elusive. This study aimed to investigate the influence of drought priming on starch and protein levels in grains under drought stress during grain filling. Our results reveal that drought stress results in a reduction in starch content and its constituents, while simultaneously increasing glutenin macropolymers and protein fractons. Notably, drought primed plants under drought stress (PD) exhibit mitigated declines in starch content and its components, leading to improvements in starch swelling power and pasting properties. Additionally, PD results in a slight increase in protein fractions, limiting the overall rise in total protein content compared to drought stress alone. Collectively, our study underscores the efficacyof drought priming as a strategy to counteract the negative effects of drought stress on grain quality, particularly by minimizing starch losses and restraining protein content elevation.

Comparison and Optimal Method of Detecting the Number of Maize Seedlings Based on Deep Learning

Effective agricultural management in maize production operations starts with the early quantification of seedlings. Accurately determining plant presence allows growers to optimize planting density, allocate resources, and detect potential growth issues early on. This study provides a comprehensive analysis of the performance of various object detection models in maize production, with a focus on the effects of planting density, growth stages, and flight altitudes. The findings of this study demonstrate that one-stage models, particularly YOLOv8n and YOLOv5n, demonstrated superior performance with AP50 scores of 0.976 and 0.951, respectively, outperforming two-stage models in terms of resource efficiency and seedling quantification accuracy. YOLOv8n, along with Deformable DETR, Faster R-CNN, and YOLOv3-tiny, were identified for further examination based on their performance metrics and architectural features. The study also highlights the significant impact of plant density and growth stage on detection accuracy. Increased planting density and advanced growth stages (particularly V6) were associated with decreased model accuracy due to increased leaf overlap and image complexity. The V2–V3 growth stages were identified as the optimal periods for detection. Additionally, flight altitude negatively affected image resolution and detection accuracy, with higher altitudes leading to poorer performance. In field applications, YOLOv8n proved highly effective, maintaining robust performance across different agricultural settings and consistently achieving rRMSEs below 1.64% in high-yield fields. The model also demonstrated high reliability, with Recall, Precision, and F1 scores exceeding 99.00%, affirming its suitability for practical agricultural use. These findings suggest that UAV-based image collection systems employing models like YOLOv8n can significantly enhance the accuracy and efficiency of seedling detection in maize production. The research elucidates the critical factors that impact the accuracy of deep learning detection models in the context of corn seedling detection and selects a model suited for this specific task in practical agricultural production. These findings offer valuable insights into the application of object detection technology and lay a foundation for the future development of precision agriculture, particularly in optimizing deep learning models for varying environmental conditions that affect corn seedling detection.

Spatial and agronomic stage distribution dynamics of maize stem borers (Lepidoptera) in the Agricultural development Zone B of Niger State, Nigeria

Maize farmers in Nigeria have been facing challenges as efforts towards the cultivation of maize is seriously hampered by insect pest infestation in maize fields, of which stem borers are a major culprit. The study was carried out to identify the species of stem borers present and their abundance in Agricultural development Zone B of Niger State. Farm sites located in Beji, Chanchaga, Paiko and Shanu, were selected and sampled for stem borers, during vegetative, reproductive and harvest stages of the field maize crops. Identification was done using standard taxonomic keys. The results indicated the presence of three species of stem borer belonging to three families. A species each from Noctuidae, Crambidae and Pyralidae consisting of Busseola fusca (n = 1639, 68.24%), Chilo partellus (n = 160, 6.66%) and Eldana saccharina (n = 603, 25.10%) respectively. Generally, all sites had two species of the stem borer (B. fusca and E. saccharina) present in all growth stages of the maize plant during the destructive sampling with the exception of Chilo partellus that was rarely found; occurring only in one site (Beji), all amounting to a total of 2402 stem borers collected during the study period. Among all the growth stages of the maize plants in all sampled sites the level of infestation varied significantly (p< 0.05), in an increasing order: vegetative stage < reproductive stage < harvest stage of the maize plants. The findings of this study suggest that there is a serious stem borer pest infestation in the maize farms of Agricultural development Zone B of Niger state that could pose threats to maize (Zea mays) production in the area; thus, requiring urgent interventions on the parts of all stakeholders.

Antioxidant Activities in Kenaf (Hibiscus cannabinus) Shoots during Growth Stages and Destination of Chlorogenic Acid and Kaempferol Glycosides.

Apart from being utilized as a commercial fiber at maturity, kenaf shoots have potential as a food and feed source because of their diverse bioactivities. Previous studies have focused on mature stems because of their high biomass, whereas the antioxidant activities (AA) and the destination of AA contributors of kenaf stems and their high-yielding byproduct leaves during the growth stage have rarely been studied. Therefore, we investigated changes in AA and its relative components in kenaf leaves and stems during the four vital growth stages. Higher ABTS radical cation and DPPH radical scavenging abilities and ferric reducing antioxidant power, total phenolic content, total flavonoid content, and total polysaccharide content were observed at all leaf stages and in the late stem stages. Chlorogenic acid (CGA) and kaempferol glycosides, especially kaempferitrin (Kfr), were identified as representative phenolic acids and flavonoids in both kenaf leaves and stems. The content of CGA in both leaves and stems increased corresponding to the plant's growth stage, whereas kaempferol glycosides were enhanced in leaves but declined in stems. The highest correlation was observed between TPC and AA in all organs. Further evaluation of CGA and Kfr verified that CGA was the predominant contributor to AA, surpassing Kfr. These findings suggest that kenaf leaves increase antioxidant levels as they grow and can be a useful source of stem harvesting byproducts.

In vivo profiling of phytocannabinoids in Cannabis spp. varieties via SPME-LC-MS analysis

BackgroundIn vivo solid-phase microextraction (SPME) is a minimally invasive, non-exhaustive sample-preparation technique that facilitates the direct isolation of low molecular weight compounds from biological matrices in living systems. This technique is especially useful for the analysis of phytocannabinoids (PCs) in plant material, both for forensic purposes and for monitoring the PC content in growing Cannabis spp. plants. In contrast to traditional extraction techniques, in vivo SPME enables continuous tracking of the changes in the level of PCs during plant growth without the need for plant material collection. In this study, in vivo SPME utilizing biocompatible C18 probes and liquid-chromatography coupled to quadrupole time-of flight mass spectrometry (LC-Q-TOF-MS) is proposed as a novel strategy for the extraction and analysis of the acidic forms of five PCs in growing medicinal cannabis plants. ResultsThe SPME method was optimized by testing various parameters, including the extraction phase (coating), extraction and desorption times, and the extraction temperature. The proposed method was validated with satisfactory analytical performance regarding linearity (10–3000 ng/mL), limits of quantification, and precision (relative standard deviations below 5.5 %). The proposed method was then successfully applied for the isolation of five acidic forms of PCs, which are main components of growing medicinal cannabis plants. As a proof-of-concept, SPME probes were statically inserted into the inflorescences of two varieties of Cannabis spp. plants (i.e., CBD-dominant and Δ9-THC-dominant) cultivated under controlled conditions for 30 min extraction of tetrahydrocannabinolic acid (Δ9-THCA), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA), cannabiviarinic acid (CBVA), and tetrahydrocannabivarinic acid (THCVA). Significance and noveltyThe results confirmed that the developed SPME-LC-Q-TOF-MS method is a precise and efficient tool that enables direct and rapid isolation and analysis of PCs under in vivo conditions. The proposed methodology is highly appealing option for monitoring the metabolic pathways and compositions of multiple PCs in medicinal cannabis at different stages of plant growth.

Distinct growth patterns in seedling and tillering wheat plants suggests a developmentally restricted role of HYD2 in salt-stress response

Key messageMutants lacking functional HYD2 homoeologs showed improved seedling growth, but comparable or increased susceptibility to salt stress in tillering plants, suggesting a developmentally restricted role of HYD2 in salt response.Salinity stress threatens global food security by reducing the yield of staple crops such as wheat (Triticum ssp.). Understanding how wheat responds to salinity stress is crucial for developing climate resilient varieties. In this study, we examined the interplay between carotenoid metabolism and the response to salt (NaCl) stress, a specific form of salinity stress, in tetraploid wheat plants with mutations in carotenoid β-hydroxylase 1 (HYD1) and HYD2. Our investigation encompassed both the vulnerable seedling stage and the more developed tillering stage of wheat plant growth. Mutant combinations lacking functional HYD2 homoeologs, including hyd-A2 hyd-B2, hyd-A1 hyd-A2 hyd-B2, hyd-B1 hyd-A2 hyd-B2, and hyd-A1 hyd-B1 hyd-A2 hyd-B2, had longer first true leaves and slightly enhanced root growth during germination under salt stress compared to the segregate wild-type (control) plants. Interestingly, these mutant seedlings also showed decreased levels of neoxanthin and violaxanthin (xanthophylls derived from β-carotene) and an increase in β-carotene in roots. However, tillering hyd mutant and segregate wild-type plants generally did not differ in their height, tiller count, and biomass production under acute or prolonged salt stress, except for decreases in these parameters observed in the hyd-A1 hyd-B1 hyd-A2 hyd-B2 mutant that indicate its heightened susceptibility to salt stress. Taken together, these findings suggest a significant, yet developmentally restricted role of HYD2 homoeologs in salt-stress response in tetraploid wheat. They also show that hyd-A2 hyd-B2 mutant plants, previously demonstrated for possessing enriched nutritional (β-carotene) content, maintain an unimpaired ability to withstand salt stress.

The significance of the two cytosolic glutamine synthetase enzymes, GLN1;3 and GLN1;5, in the context of seed development and germination in Arabidopsis thaliana

Glutamine synthetase (GS), an initial enzyme in nitrogen (N) plant metabolism, exists as a group of isoenzymes found in both cytosolic (GS1) and plastids (GS2) and has gathered significant attention for enhancing N use efficiency and crop yield.This work focuses on the A. thaliana GLN1;3 and GLN1;5 genes, the two predicted most expressed genes in seeds, among the five isogenes encoding GS1 in this species. The expression patterns were studied using transgenic marker line plants and qPCR during seed development and germination. The observed patterns highlight distinct functions for the two genes and confirm GLN1;5 as the most highly expressed GS1 gene in seeds. The GLN1;5, expression, oriented towards hypocotyl and cotyledons, suggests a role in protein turnover during germination, while the radicle-oriented expression of GLN1;3 supports a function in early external N uptake.While the single mutants exhibited a normal phenotype, except for a decrease in seed parameters, the double gln1;3/gln1;5 mutant displayed a germination delay, substantial impairment in growth, nitrogen metabolism, and number and quality of the seeds, as well as a diminishing in flowering. Although seed and pollen-specific, GLN1;5 expression is upregulated in the meristems of the gln1;3 mutants, filling the lack of GLN1;3 and ensuring the normal functioning of the gln1;3 mutants.These findings validate earlier in silico data on the expression patterns of GLN1;3 and GL1;5 genes in seeds, explore their different functions, and underscore their essential role in plant growth, seed production, germination, and early stages of plant development.

Influence of Climate and Plant Phenology (Plant Age and Growth Stage) Influence Rhopalosiphum Padi L. Abundance on Wheat Plants in Luxor Governorate, Egypt

Field experiments were conducted at El-Mattana Agricultural Research Station, Luxor Governorate, during two successive wheat growing seasons (2017/18 and 2018/19). This was to study the seasonal abundance of Rhopalosiphum padi (Hemiptera: Aphididae) on wheat plants (Giza 171 cultivar). We also investigated the effects of climate and plant phenology on the R. padi population density. Results indicated that R. padi infested wheat plants from December 17, 2017, until April 8, 2018, within the first growing season (2017/18), and from Jan. 27th, 2019, up to April 13th, 2019, within the second growing season (2018/19). The cumulative counts of R. padi in growing season one was 9486.17, and in growing season two, 3444.00 individuals. The mean population of R. padi per 10 tillers over the whole first season was 80.12 ± 7.90, and for the second season, 42.36 ± 2.96. The first season, December, January, and February, had the most favorable climate for R. padi population growth (measured during weekly inspections). In contrast, February and March were more favorable in the second season. R. padi was not detected on the wheat during the wheat maturation period within both growing seasons. The combined effects of climate and plant phenology strongly correlate with R. padi population density, with explained variance (EV) of 93.86% in the first season and 99.11% in the second season. Daily mean maximum temperature was the most influential variable explaining changes in total R. padi population, with EV 28.37%in the first season and 28.62% in the second season. The data provided here can assist in the design of Integrated Pest Management (IPM) programs for aphid control on wheat plants.

The effects of pre-harvest glyphosate rate and timing on yield and pre-malt quality of malting barley

The production of barley cultivars with malting and brewing quality characteristics is subject to strict grading and technical standards for the end-use market. Environmental and management factors can significantly alter grain quality, and the qualities required for malting. Crop and kernel uniformity are critical factors where variability can exceed the tolerance for meeting malt quality. A practice to address variations in crop maturity is the application of pre-harvest glyphosate. Pre-harvest glyphosate applications can, however, alter malting characteristics in barley, and, if mis-timed, can also reduce yield. A 4-year study at five locations in Alberta and Saskatchewan from 2013 to 2017 was conducted to determine the effects of pre-harvest glyphosate applications on malting barley characteristics. Glyphosate was applied at 900 and 1125 g ae ha−1 on malting barley cultivars ‘CDC Meredith’ and ‘AC Metcalfe’ malting barley at soft dough, hard dough, and physiological maturity growth stages. Yield reductions of up to 12% were observed from glyphosate applications at soft dough, and yield was maximized with applications at physiological maturity. Glyphosate application, at two rates, reduced percentage plump kernels, but did not affect kernel weight or protein concentration. The growth stage of barley plants did not provide an accurate indicator of seed moisture levels at the time of application, which motivated our conclusion that glyphosate applications can be mistimed by inaccurate indicators. The results motivate our questioning of the utility of pre-harvest glyphosate applications, given the adverse effects to barley yield and quality observed, even when applied according to the label instructions.

Application of electronic nose and machine learning used to detect soybean gases under water stress and variability throughout the daytime.

The development of non-invasive methods and accessible tools for application to plant phenotyping is considered a breakthrough. This work presents the preliminary results using an electronic nose (E-Nose) and machine learning (ML) as affordable tools. An E-Nose is an electronic system used for smell global analysis, which emulates the human nose structure. The soybean (Glycine Max) was used to conduct this experiment under water stress. Commercial E-Nose was used, and a chamber was designed and built to conduct the measurement of the gas sample from the soybean. This experiment was conducted for 22 days, observing the stages of plant growth during this period. This chamber is embedded with relative humidity [RH (%)], temperature (°C), and CO2 concentration (ppm) sensors, as well as the natural light intensity, which was monitored. These systems allowed intermittent monitoring of each parameter to create a database. The soil used was the red-yellow dystrophic type and was covered to avoid evapotranspiration effects. The measurement with the electronic nose was done daily, during the morning and afternoon, and in two phenological situations of the plant (with the healthful soy irrigated with deionized water and underwater stress) until the growth V5 stage to obtain the plant gases emissions. Data mining techniques were used, through the software "Weka™" and the decision tree strategy. From the evaluation of the sensors database, a dynamic variation of plant respiration pattern was observed, with the two distinct behaviors observed in the morning (~9:30 am) and afternoon (3:30 pm). With the initial results obtained with the E-Nose signals and ML, it was possible to distinguish the two situations, i.e., the irrigated plant standard and underwater stress, the influence of the two periods of daylight, and influence of temporal variability of the weather. As a result of this investigation, a classifier was developed that, through a non-invasive analysis of gas samples, can accurately determine the absence of water in soybean plants with a rate of 94.4% accuracy. Future investigations should be carried out under controlled conditions that enable early detection of the stress level.