Individual Plants Research Articles

Temporal Image Sandwiches Enable Link between Functional Data Analysis and Deep Learning for Single-Plant Cotton Senescence

Abstract Senescence is a highly ordered biological process involving resource redistribution away from aging tissues that affects yield and quality in annuals and perennials. Images from 14 unmanned / unoccupied / uncrewed aerial system (UAS, UAV, drone) flights captured the senescence window across two experiments while functional principal component analysis (FPCA) effectively reduced the dimensionality of temporal visual senescence ratings (VSRs) and two vegetation indices: the red chromatic coordinate index (RCC) and transformed normalized difference green and red index (TNDGR). Convolutional neural networks (CNNs) trained on temporally concatenated, or “sandwiched,” UAS images of individual cotton plants (Gossypium hirsutum L.), allowed single-plant analysis (SPA). The first functional principal component scores (FPC1) served as the regression target across six CNN models (M1-M6). Model performance was strongest for FPC1 scores from VSRs (R2 = 0.857 and 0.886 for M1 and M4), strong for TNDGR (R2 = 0.743 and 0.745 for M3 and M6), and strong-to-moderate for RCC (R2 = 0.619 and 0.435 for M2 and M5), with deep learning attention of each model confirmed by activation of plant pixels within saliency maps. Single-plant UAS image analysis across time enabled translatable implementations of high-throughput phenotyping by linking deep learning with functional data analysis (FDA). This has applications for fundamental plant biology, monitoring orchards or other spaced plantings, plant breeding, and genetic research.

Impact of Microtopography and Neighborhood Effects on Individual Survival Across Life History Stages

Understanding drivers of plant community assembly and individual survival in forest ecosystems is crucial for effective conservation and management. While macro-scale factors influencing vegetation patterns are well documented, the combined impact of microtopographic variations and neighborhood effects at neighborhood scales, particularly in subtropical forests, requires further study. To contribute to this area of research, we established a 9.6 ha dynamic plot in a subtropical evergreen broad-leaved forest to examine the interplay between microtopographic factors and neighborhood effects on individual plant survival across different life stages. We conducted a comprehensive analysis of microtopographic variables and neighborhood effects, with individual plant survival censused through repeated surveys at 5-year intervals. Mixed-effects models were employed to assess the combined influence of these factors across life stages. Our results reveal that both microtopographic factors and neighborhood effects significantly influence plant survival, with their impacts varying across life stages. Water availability, represented by flow direction, emerged as a consistently critical factor throughout all life stages. Elevation and the topographic position index showed significant positive effects on survival, particularly in later life stages, possibly reflecting adaptations to light acquisition and water drainage. The influence of topographic factors intensified with succession, while the impact of neighborhood effects, particularly asymmetric competition and conspecific negative density dependence, changed as plants matured. This study enhances our understanding of forest community assembly, emphasizing the importance of considering abiotic and biotic factors across multiple scales for effective forest conservation and management. It provides insights into mechanisms driving spatial variation in community composition, crucial for preserving biodiversity in heterogeneous forest landscapes.

Changes in Farm Supply Voltage Caused by Switching Operations at a Wind Turbine

Renewable electricity sources are now widely used worldwide. Currently, the most common sources are those that use energy contained in biomass, water, sun, and wind. When connected to a medium-voltage grid, individual wind power plants must meet specific conditions to maintain electricity quality. This article presents field study results on the impact of switching operations (turning the power plant on and off) at a 2 MW Vestas V90 wind turbine on the voltage parameters at the connection point of a farm located 450 m from the source. The analysis showed that the wind turbine under study significantly affects customers’ voltage near the source, causing it to increase by approximately 2.5%. Sudden cessation of generation during the afternoon peak causes a 3% voltage fluctuation, potentially affecting equipment sensitive to rapid voltage changes.

Reprogramming of flagellin receptor responses with surrogate ligands.

Receptor kinase (RK) families process information from small molecules, short peptides, or glycan ligands to regulate core cellular pathways in plants. To date, whether individual plant RKs are capable of processing signals from distinct types of ligands remains largely unexplored. Addressing this requires the discovery of structurally unrelated ligands that engage the same receptor. Here, we focus on FLAGELLIN-SENSING 2 (FLS2), an RK that senses a peptide of bacterial flagellin to activate antibacterial immunity in Arabidopsis. We interrogate >20,000 potential interactions between small molecules and the sensory domain of FLS2 using a large-scale reverse chemical screen. We discover two small molecules that interact with FLS2 in atypical ways. The surrogate ligands weakly activate the receptor to drive a functional antibacterial response channeled via unusual gene expression programs. Thus, chemical probes acting as biased ligands can be exploited to discover unexpected levels of output flexibility in RKs signal transduction.

Masting ontogeny: the largest masting benefits accrue to the largest trees.

Both plants and animals display considerable variation in their phe- notypic traits as they grow. This variation helps organisms to adapt to specific challenges at different stages of development. Masting, the variable and synchronized seed production across years by a population of plants, is a common reproductive strategy in perennial plants that can enhance reproductive efficiency through increasing pollination efficiency and decreasing seed predation. Masting represents a population-level phenomenon generated from individual plant behaviors. While the developmental trajectory of individual plants influences their masting be- havior, the translation of such changes into benefits derived from masting remains unexplored. We used 43 years of seed production monitoring in European beech (Fagus sylvatica) to address that gap. The largest improvements in reproductive efficiency from masting happen in the largest trees. Masting leads to a 48-fold reduction in seed predation in large, compared to 28-fold in small trees. Masting yields an 6-fold increase in pollination efficiency in large, compared to 2.5-fold in small trees. Paradoxically, although the largest trees show the biggest reproductive efficiency benefits from masting, large trees mast less strongly than small trees. That apparently suboptimal allocation of effort across years by large plants may be a consequence of anatomical constraints or bet-hedging. Ontogenetic shifts in individual mast- ing behavior and associated variable benefits have implications for the reproductive potential of plant populations as their age distribution changes, with applications in plant conservation and management.

Chemical Variability of the Leaf Essential Oil of Two Subspecies of Juniperus oxycedrus L. From Northwestern Algeria.

Thirty-seven essential oil samples have been isolated from leaves of individual plants of Juniperus oxycedrus (subspecies oxycedrus and macrocarpa) growing wild in Tlemcen and Aïn Témouchent provinces (Northwestern Algeria). Analysis of eight selected oil samples by GC(RI), GC/MS and 13C NMR, allowed the identification of 88 components that accounted for 84.4-99.5 % of the whole compositions. The 37 compositions were subjected to statistical analysis which suggested the existence of groups and sub-groups I, IIA and IIB. Group I, the most important group with 24 oil samples out of 37, differed from sub-groups IIA and IIB, essentially by the high content of α-pinene (mean value, 69.2 %; SD 6.24). Sub-groups IIA and IIB were differentiated by their content of α-pinene (Mean values, 49.7 % and 27.3 %, respectively) as well as δ-3-carene (10.3 %, sub-group IIA), sabinene and (Z)-6-pentadecen-2-one (8.7 % and 4.9 %, respectively, sub-group IIB).

Optimizing sunflower yield: Understanding pollinator contribution to inform agri-environmental strategies

ContextThe agricultural intensification due to global increased food demand has harmed pollinator communities worldwide. However, some of the economically most important oilseed crops, such as the sunflower, depend on pollinators to produce seeds. While self-fertile varieties have undergone genetic selection to guarantee productivity, the pollinator-dependence levels and the economic contribution of pollinators have not been fully estimated. ObjectiveHere, we aimed to explore floral and pollinator constraints limiting the agricultural yield of sunflower varieties most frequently used in the Iberian Peninsula. MethodsPollination experiments were undertaken to analyse the pollinator-dependence level of 12 varieties under controlled conditions and also under natural conditions in 23 fields of two Spanish agricultural regions. The selfing ability and economic contribution of pollinators were estimated by comparing bagged and open-pollination treatments. ResultsOur results showed that the degree of pollinator-dependence is highly dependent on sunflower variety, with impacts on production and productivity outcomes, e.g. individual plant yield values varied between 0.188 and 0.692. Several varieties could self-fertilize and produce seeds regardless of pollinators. However, outcrossing significantly increased seed set in most varieties with increments up to 0.341. Overall, a trade-off between the number and weight of seeds was observed. Under natural field conditions, pollinators significantly increased overall sunflower production, although differences were observed among regions (increment of 275 kg/ha in Burgos and 382 kg/ha in Cuenca), with an associated economic outcome. ConclusionsThe self-fertilization ability and the level of pollinator-dependence vary according to the intrinsic reproductive traits of the variety analysed. Although some varieties are able to produce seeds despite the absence of pollinators, the sunflower clearly benefits from insect pollination. The landscape context and the availability of pollinator communities influenced the final crop yield and the economic outcome. SignificanceCombining landscape-restoring interventions with the cultivation of self-compatible varieties during at least the first years of implementation may be a solid additional agri-environmental strategy to maintain production levels and economic outcomes, which may particularly mitigate effects of pollinator and biodiversity losses mainly in highly simplified agroecosystems.

Biodiversity Assessment of Trees and Shrubs at Tirunelveli’s Science Centre in Southern India: A Conservation Perspective

A comprehensive taxonomical floristic survey conducted at the District Science Centre in Tirunelveli identified 84 species of trees and shrubs, documenting each plant species with detailed information on medicinal uses, family classification, commercial importance, and population count of individual plants. The survey identified 33 families and 68 genera, with Fabaceae being the most dominant family, followed by Rubiaceae, Arecaceae, and Malvaceae. Additionally, the survey highlighted a list of vulnerable, threatened, and endangered tree species such as Cycas beddomei Dyer., Santalum album L., emphasizing the need for conservation efforts based on their spatial reach and anthropogenic pressures. These species face various threats, including loss of habitat, agriculture, pollution load, and recreational disturbances, and were assessed according to the IUCN Red List criteria. This study provides valuable insights for botanists, conservationists, and policymakers, promoting sustainable management and protection of plant biodiversity in the region.

The alien and invasive plant species that may be a future conservation threat to the Lesotho Afro-alpine Drakensberg area

In this study, we documented and compared similarities of the alien plant species richness between South Africa represented by three provinces: Free State (FS), Eastern Cape (EC), and KwaZulu-Natal (KZN), and Lesotho—an important water source area for southern Africa. We tested the prediction that alien plant species in Lesotho are a subset of South Africa’s species partly because of the short geographical distances between the provinces and Lesotho, and environmental similarity. Overall, 7124 records containing 1040 individual alien plant species belonging to 147 families were documented. South Africa had significantly greater alien plant species records than Lesotho. Of 147 plant families, 44 were represented in both countries, and 101 families did not occur in Lesotho. Against the study prediction, the Geraniaceae and Orobanchaceae families occurred in Lesotho but not in three provinces. KwaZulu-Natal had a significantly greater number of species than Lesotho but not the other provinces, and 49% of species in three provinces originated from the Americas (i.e. South and North), Europe, and Asia. A similar pattern was observed in Lesotho. Woody and herbaceous alien plants, habitat transformers, dominated three provinces, while herbaceous species dominated Lesotho. The 62% of 1040 alien species were not listed in the South African national regulations, indicating their negative impacts are also unknown in the study region. Plant nurseries were a dominant species dispersal pathway in South Africa, while home gardens were prominent in Lesotho. We conclude that invasive plant species constitute a future threat to the Lesotho Drakensberg highlands water catchments and recommend prioritising their management and improving cross-border biosecurity between Lesotho and South Africa.

Harvesting Light: The Interrelation of Spectrum, Plant Density, Secondary Metabolites, and Cannabis sativa L. Yield

The approaching legalisation and associated increasing demand for medicinal and recreational Cannabis sativa L. will lead to a growing relevance for lighting systems designed for Cannabis sativa L. The interplay between plant density, light spectrum, light distribution, yield, and secondary metabolite distribution within the plant has not yet been studied. To fill this knowledge gap, a CBD-dominant Cannabis sativa L. strain was grown in a greenhouse experiment with two plant densities (2.66 and 12 plants −1 m−2) under two different light spectra. The chosen light spectra were two LED fixtures, Solray385 (SOL) and AP67, with an R: FR ratio of 12.9 and 3.7, respectively. The results indicated that light-induced effects on individual plants can be transferred to the plant stock. A low R: FR ratio induced a 16% increase in dry flower yield in the last ten days of flowering, while a change in the light spectrum could increase the potential maximum plant density per square metre. The two spectra did not affect (CBD + CBDA) yield, as a lower flower yield compensated for a higher concentration. CBDA concentration was not significantly affected by plant density. In contrast, the higher density led to an increased total cannabidiol concentration (CBD + CBDA) and altered the distribution of terpenes. Here, the light distribution over the plant stock is particularly decisive, as a more homogenous illumination led to an increased terpene concentration of up to 41%. A Photon Conversion Efficacy (PCE) of 0.05 g mol−1 under SOL and 0.06 g mol−1 under AP67 was achieved. Plants in the centre under the highest light intensity of 1200 PAR showed up to 48% reduced efficacy. These results strongly suggest that light intensity needs to be fine-tuned to the cultivation system to prevent a reduction in efficacy, resulting in yield and quality losses.

Functional ecology of plant communities as a guide for vegetation management

Plant functional traits determine how individual plants cope with varying environmental conditions, and extensive literature supports their role in influencing ecosystem properties. The study of plant functional traits could help the prediction of species responses to disturbances and environmental change, thus providing invaluable knowledge to refine conservation strategies of species and vegetation. However, applications of functional ecology for vegetation management are still underrepresented.The articles in this Special Issue of FLORA offer cutting-edge insights on the variation of plant traits and ecological strategies in response to environmental drivers, such as anthropogenic disturbance, climate and land use change. The results demonstrate how trait-based approaches can be used for the prediction of climate and land use change impacts on vulnerable sets of species or on biogeochemical cycles, reinforcing the concept that functional plant ecology can help identify the most effective procedures for vegetation management, such as the choice of mowing intensity in grasslands or planning vegetation recovery after wildfires.Our knowledge of plant trait coordination at the community level is still undefined, especially concerning the integration of above- and belowground traits. This represents a missed opportunity for vegetation management, especially considering that a complete understanding of the dynamics of the entire ecosystem is crucial for complete understanding of ecosystem properties. Since plant functional traits can represent a straightforward tool for monitoring changes in ecosystem structure and functions, their use could support vegetation monitoring as required by different programs of nature conservation. It would be useful to embrace a perspective that integrates plant traits with systematic conservation planning, ensuring effective and sustainable conservation efforts.

Historical increases of maize leaf area index in the US Corn Belt due primarily to plant density increases

ContextLeaf area index (LAI) and leaf area distribution within the maize plant are important traits used to explain and predict light interception and thus crop productivity. ObjectivesHere we investigate breeding and plant density effects of leaf area traits. Our objectives are to 1) quantify maize breeding impacts on leaf area distribution and determine bell-shape coefficients used in crop modeling, 2) dissect the contribution of breeding from plant density, and 3) explore the relationship between LAI and crop yields. MethodsWe studied 18 hybrids released between 1983 and 2017 at two density treatments: current (8.5 pl m-2) and historical increasing density (from 4.6 to 8.5 pl m-2) in Iowa, USA. ResultsResults indicated that concurrent changes in hybrids and increases in plant density have increased LAI from 3.4 (in 1983) to 5.9 m2 m-2 (in 2017), with the highest LAI increases (>50%) to be realized in the middle canopy. At historical increasing in plant density treatment, the LAI increased by 1.6% year-1, but the individual plant leaf area decreased by 0.33% year-1 from 1983 to 2017. This trade-off indicates that new hybrids are more tolerant to higher plant populations than old hybrids. At current plant density treatment, the year of hybrid release did not affect LAI or individual plant leaf area. New hybrids had 5% narrower leaf area distributions, 23% higher optimum LAI values (5.2 vs 4.2 m2 m-2) and 19% higher grain yields compared to old hybrids. ConclusionsThe main reason for the increase in maize LAI in the US Corn Belt is plant density. However, an increase in LAI does not necessarily translate to higher grain yields as new hybrids had significantly higher grain yields than older hybrids at similar LAI values. Present results contribute to our understanding of maize canopy architecture and allow us to better calibrate crop models to accurately estimate LAI and grain yield.

Drought and heat stress interactions: Unveiling the molecular and physiological responses of Persian walnut

While numerous studies explored the response of walnut plants to drought stress (DS), there remains a significant gap in the knowledge regarding the impact of heat stress (HS) and the combined effects of DS and HS on the recovery capacity of walnut trees. This study aimed to investigate the mechanism of Persian walnut (cv. Chandler) response to the combined DS and HS, focusing on various aspects including photosynthesis, water relations, and osmotic regulation. The treatments involved subjecting plants to DS (through a withholding method for 24 d), HS (gradually up to 40 °C for 8 d), and a combined DS and HS, which were compared to a control group (no stress) during the stress and recovery phases. The results showed that DS had significantly more negative effects on chlorophyll content, relative water content (RWC), leaf water potential (WP), osmotic potential (OP) compared to HS. Involvement of osmoregulation mechanism was detected more in DS and HS plants through the accumulation of proline, glycine Betaine and total soluble carbohydrates. The functionality of photosynthesis was significantly impacted by both HS and DS, respectively. While the HS accelerated the change of the abovementioned physiological processes in drought-stressed seedlings. Consistently, more pronounced damage was found in leaves under the combined stress, alongside the decrease RWC, chlorophyll content and fluorescence ratios. Based on the analysis of the linear mixed-effect model, the effects of combined stress and HS on photosynthesis parameters were detected in the early stages of stress compared to DS. Within a range of stresses, the abovementioned physiological processes of individual and combined-stressed plants recovered to levels comparable to those of the control. Our results also showed a substantial reduction in the expression of the photosynthetic genes (Fd, Cyt b6f, and PsbB) in Persian walnut saplings under abiotic stress conditions indicating significant damage to their photosynthetic apparatus. This study highlights that, under scenarios of aggravating drought occurring with heat, walnut seedlings could face a high risk of damage to physiological structures in relation to the synergistically increased hydraulic and thermal impairments.

Variance investigation on the microstructural characteristics of vessels among three lignocellulosic biomasses

Especially, the processing and utilization of biomass-based material is closely related to the vessel, e.g. the flow of vapour and additive. It is conventional that vessels in most plants can influence on water and nutrients transport between adjacent cells, which could just infer to be important in the wood-based panel industries. In this work, a complete characterization of vessels and pits is presented for three conventional biomasses in wood-based panel: poplar (Populus deltoides) (P), moso bamboo (Phyllostachys edulis) (B), and the fruit shell of oil camellia (Camellia Oleifera) (FS_OC). Every material is analyzed by combining several techniques including: light microscopy, scanning electron microscopy and surveying calculations from resin casting. The results show that among the three biomass materials, B has a significantly larger vessel width (164.8 ± 6.0 μm for B, 2.2 ± 6.2 μm for P, 10.0 ± 0.8 μm for FS_OC) and smaller inclination angle of the perforation plates (6.8° for B, 44.7° for P), which is more conductive to improving moisture transfer between the vessels. The vessel length of P varies widely from 676.8 μm to 1025.2 μm, which is related to its seasonal growth. By resin casting analysis, more differences in the morphology and distribution of pits in the vessel walls were observed between the three species. Such as, For B, there are numerous pits between vessel cells, while very few to none between vessel and parenchyma cells or fiber. In addition to pits, B and FS_OC also have spiral thickening structures on their vessel walls. The pit membrane is an elliptical shape in P, while slit-like shape in FS_OC and a combination of both elliptical and slit-like shape in bamboo. The unique microstructural characteristics of vessels is related to the individual plant growth traits, which is the basis for biomass-based material processing and utilization.

EPSPS gene amplification in a glyphosate-resistant population of Italian ryegrass (Lolium multiflorum) from Oregon.

Lolium multiflorum Lam. (Italian ryegrass, annual ryegrass) is both a weed and a crop in Oregon. Because it is commonly managed using chemical controls, herbicide-resistant populations have evolved within the seed production region. A glyphosate-resistant population was identified in Yamhill County, Oregon, in a fallow field previously cropped with perennial ryegrass. Dose-response studies showed that the glyphosate-resistant population, OR12, was nine-fold more resistant to glyphosate than the susceptible population. No EPSPS amino acid substitutions known to confer glyphosate resistance were observed via gene sequencing. Quantitative polymerase chain reaction (qPCR) of genomic DNA revealed a mean 30-fold increase in EPSPS gene copies in the OR12 population. Biomass after glyphosate treatment was correlated with EPSPS gene copy number of individual plants. This is the first known report of glyphosate resistance associated with EPSPS gene amplification to arise in L. multiflorum populations in Oregon. © 2024 Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Seed Oil Contents, Fatty Acid Compositions, and Gossypol Concentrations of Some Okra Landraces

ABSTRACTOkra has recently attracted attention owing to its superior tolerance to high temperatures, greater adaptation to poor soil conditions, and having a robust plant structure. The plant contains a high amount of oil and valuable fatty acids; however, the main restriction of using okra seeds as an oil crop results from its gossypol contents. The aim of this study was to determine the oil content of okra landraces and to evaluate its potential as an oil crop. For this aim, seed oil content, fatty acid compositions of cold‐pressed seed oil, and gossypol concentrations of fruit, oil cake, and seed oil were investigated in a core collection of 26 okra landraces, lines, and cultivars. Individual plants were harvested at the full maturity stage, and seeds were harvested and dried under 35°C for 2 days prior to oil extraction. Oil content, fatty acid composition, and gossypol content were analyzed by NMR, GC‐FID, and HPLC, respectively. The calibration coefficients (r2) of all the methods were determined to be > 0.99. The seed oil content of the samples ranged between 12.15% and 18.83%. Linoleic (42.01%), palmitic (31.65%), oleic (18.39%), and stearic acids (3.20%) were found to be the largest fraction of the fatty acids. The data matrix from 19 fatty acids and oil content was subjected to Principle Component Analysis (PCA). As a result, 6 principal components (PCs, eigenvalues > 1) explained 83.84% of total variance in the data set, with PC1 contributing 32.69% of the total. Gossypol contents of the fruit, oil cake, and seed oil fractions ranged between LOQ‐2.12, < LOQ‐7.01, and < LOQ‐62.46 mg/kg, respectively. In conclusion, okra may have the potential to be an alternative oil crop for food/feed purposes due to the presence of reasonable oil content, high‐quality fatty acid variations, and very low amounts of toxic gossypols, warranting further breeding and agronomic studies.

Deep learning modeling of RNA ac4C deposition reveals the importance of plant alternative splicing.

The N4-acetylcytidine (ac4C) modification has recently been characterized as a noncanonical RNA marker in plants. While the precise installation of ac4C sites in individual plant transcripts continues to present challenges, the biological roles of ac4C in specific plant species are gradually being deciphered. Herein, we utilized a deep learning technique called iac4C (intelligent ac4C) to predict ac4C sites in mRNA. ac4C deposition was effectively forecasted by the iac4C model (AUROC = 0.948), revealing a reliable distribution pattern primarily situated in the transcribing area as opposed to regions that are not translated. The iac4C deep learning approach using a combination of BiGRU and self-attention mechanisms both validates previous studies showing a positive correlation between ac4C and RNA splicing in plant species and reveals new examples of other splicing events associated with ac4C. Our advanced deep learning algorithm for analyzing ac4C enables swift identification of important biological phenomena that would otherwise be challenging to uncover through traditional experimental approaches. These findings provide insight into the essential regulatory function of site-specific ac4C deposition in alternative splicing processes. The source code and datasets for iac4C are available at https://github.com/xlwei507/iac4C .

Salt Tolerance in Sugar Beet: From Impact Analysis to Adaptive Mechanisms and Future Research.

The continuous global escalation of soil salinization areas presents severe challenges to the stability and growth of agricultural development across the world. In-depth research on sugar beet (Beta vulgaris L.), an important economic and sugar crop with salt tolerance characteristics, is crucial for to determine its salt-tolerance mechanisms, which has important practical implications for production. This review summarizes the multifaceted effects of salt stress on sugar beet, ranging from individual plant responses to cellular and molecular adaptations. Sugar beet exhibits robust salt-tolerance mechanisms, including osmotic regulation, ion balance management, and the compartmentalization of toxic ions. Omics technologies, including genomics, transcriptomics, proteomics, post-translational modification omics and metabolomics, have played crucial roles in elucidating these mechanisms. Key genes and pathways involved in salt tolerance in sugar beet have been identified, paving the way for targeted breeding strategies and biotechnological advancements. Understanding these mechanisms not only enhances our knowledge of sugar beet's adaptation strategies but also provides insights for improving salt tolerance in other crops. Future studies should focus on analyzing gene expression changes in sugar beet under salt stress to gain insight into the molecular aspects of its salt-tolerance mechanisms. Meanwhile, the effects of different environmental conditions on sugar beet adaptation strategies should also be investigated to improve their growth potential in salinized soils.

Exploring the Diversity, Root Colonization, and Morphology of Arbuscular Mycorrhizal Fungi in Lamiaceae.

This study aimed to explore the diversity, root morphology, and colonization of arbuscular mycorrhizal fungi (AMF) associated with eight medicinal plants of the Lamiaceae family. Rhizospheric soil and root samples were collected from eight species of Lamiaceae plants for AMF analysis. The results indicate that root colonization was not directly related to the number of AMF spores in the rhizosphere. However, a significant correlation was found between the percentage of root colonization and the number of AMF species present in the individual plants. The highest percentage of colonization (86.67 ± 1.92%) and the greatest number of AMF species were observed in Micromeria fructicosa, while the lowest colonization (27.67 ± 6.22%) was recorded in Mentha arvensis. The highest spore count was recorded in Thymus vulgaris (120 ± 27.01), whereas the lowest was found in Melissa officinalis (84 ± 17.20). Among the identified AMF species, Glomus was the most dominant, representing 35.7% of all AMF species across the eight medicinal plants. The maximum AMF spore density was observed in M. fructicosa and lowest in M. arvensis. The study suggests that AMF can significantly enhance medicinal plant growth by ensuring a consistent supply of nutrients and water, thereby supporting the sustainable cultivation of medicinal plants to meet the growing demand.

Maize plants can recover from fall armyworm damage under optimum crop production conditions in humid tropical agro-ecologies.

Farmers in Africa perceive the impact of fall armyworm (FAW) on maize to be significant, but field assessments have shown that yield losses are not significant enough to warrant pesticide interventions. This suggests that relationships between the crop stages, time, and duration of attack can affect the yield. Therefore, assessing the plant's recovery from damage using individual plants based on defoliation levels could guide whether and when pesticides should be applied. To study this, we selected 120 labeled maize plants corresponding to six levels of FAW defoliation, replicated 20 times, based on an initial damage rating. The rating scale ranged from 1 (no defoliation) to 5 (>75% defoliation) during four planting seasons. Plants with a rating scale of 1 were replicated and treated with a chemical insecticide to keep them undefoliated, and that served as a control. Damage severity was recorded weekly on all plants, starting from emergence until maturity, using the same damage rating scale. Results showed that damage severity varied significantly among different defoliation levels during all seasons. Higher levels of defoliation during dry seasons resulted in significant yield loss only for plants with damage levels 4 and 5, with damage severity ranging from 38.7% to 57.5%. These results indicate that FAW control is unnecessary in the rainy season. In contrast, pesticide interventions should be envisaged in seasons of erratic rainfall, with a significant defoliation threshold level of around 50%, occurring at 8 and 5wk after planting weeks after planting, respectively for the early and late dry season.