Electrochemical sensors for plant signaling molecules.

Plant signaling molecules can be divided into plant messenger signaling molecules (such as calcium ions, hydrogen peroxide, Nitric oxide) and plant hormone signaling molecules (such as auxin (mainly indole-3-acetic acid or IAA), salicylic acid, abscisic acid, cytokinin, jasmonic acid or methyl jasmonate, gibberellins, brassinosteroids, strigolactone, and ethylene), which play crucial roles in regulating plant growth and development, and response to the environment. Due to the important roles of the plant signaling molecules in the plants, many methods were developed to detect them. The development of in-situ and real-time detection of plant signaling molecules and field-deployable sensors will be a key breakthrough for botanical research and agricultural technology. Electrochemical methods provide convenient methods for in-situ and real-time detection of plant signaling molecules in plants because of their easy operation, high sensitivity, and high selectivity. This article comprehensively reviews the research on electrochemical detection of plant signaling molecules reported in the past decade, which summarizes the various types electrodes of electrochemical sensors and the applications of multiple nanomaterials to enhance electrode detection selectivity and sensitivity. This review also provides examples to introduce the current research trends in electrochemical detection, and highlights the applicability and innovation of electrochemical sensors such as miniaturization, non-invasive, long-term stability, integration, automation, and intelligence in the future. In all, the electrochemical sensors can realize in-situ, real-time and intelligent acquisition of dynamic changes in plant signaling molecules in plants, which is of great significance for promoting basic research in botany and the development of intelligent agriculture.

Sod farms drive habitat selection of a migratory grassland shorebird during a critical stopover period.

Migratory shorebirds are one of the fastest declining groups of North American avifauna. Yet, relatively little is known about how these species select habitat during migration. We explored the habitat selection of Buff-breasted Sandpipers (Calidris subruficollis) during spring and fall migration through the Texas Coastal Plain, a major stopover region for this species. Using tracking data from 118 birds compiled over 4 years, we found Buff-breasted Sandpipers selected intensively managed crops such as sod and short-stature crop fields, but generally avoided rangeland and areas near trees and shrubs. This work supports prior studies that also indicate the importance of short-stature vegetation for this species. Use of sod and corn varied by season, with birds preferring sod in spring, and avoiding corn when it is tall, but selecting for corn in fall after harvest. This dependence on cropland in the Texas Coastal Plain is contrary to habitat use observed in other parts of their non-breeding range, where rangelands are used extensively. The species' almost complete reliance on a highly specialized crop, sod, at this critical stopover site raises concerns about potential exposure to contaminants as well as questions about whether current management practices are providing suitable conditions for migratory grassland birds.

Novel centromeric repetitive DNA elements reveal karyotype dynamics in polyploid sainfoin (Onobrychis viciifolia).

Polyploidy is a common feature in eukaryotes with one of paramount consequences leading to better environmental adaptation. Heterochromatin is often located at telomeres and centromeres and contains repetitive DNA sequences. Sainfoin (Onobrychis viciifolia) is an important perennial forage legume for sustainable agriculture. However, there are only a few studies on the sainfoin genome and chromosomes. In this study, novel tandem repetitive DNA sequences of the sainfoin genome (OnVi180, OnVi169, OnVi176 and OnVidimer) were characterized using bioinformatics, molecular and cytogenetic approaches. The OnVi180 and OnVi169 elements colocalized within functional centromeres. The OnVi176 and OnVidimer elements were localized in centromeric, subtelomeric and interstitial regions. We constructed a sainfoin karyotype that distinguishes the seven basic chromosome groups. Our study provides the first detailed description of heterochromatin and chromosome structure of sainfoin and proposes an origin of heterozygous ancestral genomes, possibly from the same ancestral diploid species, not necessarily from different species, or for chromosome rearrangements after polyploidy. Overall, we discuss our novel and complementary findings in a polyploid crop with unique and complex chromosomal features.

Preliminary Evaluation of New Wearable Sensors to Study Incongruous Postures Held by Employees in Viticulture.

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers' hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers' hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand-wrist-forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity.

Physiological and Molecular Mechanisms of Rice Tolerance to Salt and Drought Stress: Advances and Future Directions.

Rice, a globally important food crop, faces significant challenges due to salt and drought stress. These abiotic stresses severely impact rice growth and yield, manifesting as reduced plant height, decreased tillering, reduced biomass, and poor leaf development. Recent advances in molecular biology and genomics have uncovered key physiological and molecular mechanisms that rice employs to cope with these stresses, including osmotic regulation, ion balance, antioxidant responses, signal transduction, and gene expression regulation. Transcription factors such as DREB, NAC, and bZIP, as well as plant hormones like ABA and GA, have been identified as crucial regulators. Utilizing CRISPR/Cas9 technology for gene editing holds promise for significantly enhancing rice stress tolerance. Future research should integrate multi-omics approaches and smart agriculture technologies to develop rice varieties with enhanced stress resistance, ensuring food security and sustainable agriculture in the face of global environmental changes.

Water hyacinth: Prospects for biochar-based, nano-enabled biofertilizer development.

The widespread proliferation of water hyacinth (Eichhornia crassipes) in aquatic ecosystems has raised significant ecological, environmental, and socioeconomic concerns globally. These concerns include reduced biodiversity, impeded water transportation and recreational activities, damage to marine infrastructure, and obstructions in power generation dams and irrigation systems. This review critically evaluates the challenges posed by water hyacinth (WH) and investigates potential strategies for converting its biomass into value-added agricultural products, specifically nanonutrients-fortified, biochar-based, green fertilizer. The review examines various methods for producing functional nanobiochar and green fertilizer to enhance plant nutrient uptake and improve soil nutrient retention. These methods include slow or fast pyrolysis, gasification, laser ablation, arc discharge, or chemical precipitation used for producing biochar which can then be further reduced to nano-sized biochar through ball milling, a top-down approach. Through these means, utilization of WH-derived biomass in economically viable, eco-friendly, sustainable, precision-driven, and smart agricultural practices can be achieved. The positive socioeconomic impacts of repurposing this invasive aquatic plant are also discussed, including the prospects of a circular economy, job creation, reduced agricultural input costs, increased agricultural productivity, and sustainable environmental management. Utilizing WH for nanobiochar (or nano-enabled biochar) for green fertilizer production offers a promising strategy for waste management, environmental remediation, improvement of waterway transportation infrastructure, and agricultural sustainability. To underscore the importance of this work, a metadata analysis of literature carried out reveals that an insignificant section of the body of research on WH and biochar have focused on the nano-fortification of WH biochar for fertilizer development. Therefore, this review aims to expand knowledge on the upcycling of non-food crop biomass, particularly using WH as feedstock, and provides crucial insights into a viable solution for mitigating the ecological impacts of this invasive species while enhancing agricultural productivity.

A review of appropriate mechanisation systems for sustainable traditional grain production by smallholder farmers in sub-Saharan Africa with particular reference to Zimbabwe.

Climate change and variability is affecting the production of maize, a staple food in Zimbabwe, leading to the advocacy for production of traditional grains (sorghum, pearl millet and finger millet) as complementary crops for food and nutrition security; mainly because of their drought tolerance. Adoption of traditional grains as a climate change adaptation strategy is, however, limited by lack of appropriate field mechanisation technologies, inter alia. The specific objective of this review was to examine the field mechanisation technologies being used in different farming systems across the globe for their appropriateness in smallholder traditional grain production systems in developing countries, using Zimbabwe as an example, and focusing on the prevailing technical, socio-economic and environmental factors which influence sustainable adoption. The review was conducted by searching ScienceDirect, Researchgate, JSTOR, Springer, AGORA and Google Scholar databases for mechanisation strategies, policies, machinery and equipment used in cereal production systems across the globe. The review revealed that the mechanisation of traditional grain production operations is lagging behind that of other cereals and that there is need to work on developing appropriate mechanisation systems for smallholder farmers in developing countries. Various farm power options were analysed and the use of two-wheel tractors under service-provision was identified as the most suitable option. Conservation agriculture-based direct seeders and use of mowers or bio-pesticides are the best-suited technologies for crop establishment and weed control, respectively. In terms of harvesting, no available equipment can be recommended for smallholder use as yet. Further research is required to optimize the practical application of mowers and bio-pesticides as well as develop scale-based direct seeders and harvesting equipment. Policy issues were identified and recommendations for improvement made. The findings of the current study can be adapted by other sub-Sahara Africa countries where farming systems, priorities and challenges are similar to that of Zimbabwe.

Unveiling temporal and spatial research trends in precision agriculture: A BERTopic text mining approach.

This study leverages the BERTopic algorithm to analyze the evolution of research within precision agriculture, identifying 37 distinct topics categorized into eight subfields: Data Analysis, IoT, UAVs, Soil and Water Management, Crop and Pest Management, Livestock, Sustainable Agriculture, and Technology Innovation. By employing BERTopic, based on a transformer architecture, this research enhances topic refinement and diversity, distinguishing it from traditional reviews. The findings highlight a significant shift towards IoT innovations, such as security and privacy, reflecting the integration of smart technologies with traditional agricultural practices. Notably, this study introduces a comprehensive popularity index that integrates trend intensity with topic proportion, providing nuanced insights into topic dynamics across countries and journals. The analysis shows that regions with robust research and development, such as the USA and Germany, are advancing in technologies like Machine Learning and IoT, while the diversity in research topics, assessed through information entropy, indicates a varied global research scope. These insights assist scholars and research institutions in selecting research directions and provide newcomers with an understanding of the field's dynamics.

Deep learning for mango leaf disease identification: A vision transformer perspective.

Over the last decade, the use of machine learning in smart agriculture has surged in popularity. Deep learning, particularly Convolutional Neural Networks (CNNs), has been useful in identifying diseases in plants at an early stage. Recently, Vision Transformers (ViTs) have proven to be effective in image classification tasks. These architectures often outperform most state-of-the-art CNN models. However, the adoption of vision transformers in agriculture is still in its infancy. In this paper, we evaluated the performance of vision transformers in identification of mango leaf diseases and compare them with popular CNNs. We proposed an optimized model based on a pretrained Data-efficient Image Transformer (DeiT) architecture that achieves 99.75% accuracy, better than many popular CNNs including SqueezeNet, ShuffleNet, EfficientNet, DenseNet121, and MobileNet. We also demonstrated that vision transformers can have a shorter training time than CNNs, as they require fewer epochs to achieve optimal results. We also proposed a mobile app that uses the model as a backend to identify mango leaf diseases in real-time.

Metabonomic analysis to identify exometabolome changes underlying antifungal and growth promotion mechanisms of endophytic Actinobacterium Streptomyces albidoflavus for sustainable agriculture practice.

In recent years, there has been an increasing focus on microbial ecology and its possible impact on agricultural production, owing to its eco-friendly nature and sustainable use. The current study employs metabolomics technologies and bioinformatics approaches to identify changes in the exometabolome of Streptomyces albidoflavus B24. This research aims to shed light on the mechanisms and metabolites responsible for the antifungal and growth promotion strategies, with potential applications in sustainable agriculture. Metabolomic analysis was conducted using Q Exactive UPLC-MS/MS. Our findings indicate that a total of 3,840 metabolites were identified, with 137 metabolites exhibiting significant differences divided into 61 up and 75 downregulated metabolites based on VIP >1, |FC| >1, and p < 0.01. The interaction of S. albidoflavus B24 monoculture with the co-culture demonstrated a stronger correlation coefficient. The Principal Component Analysis (PCA) demonstrates that PCA1 accounted for 23.36%, while PCA2 accounted for 20.28% distinction. OPLS-DA score plots indicate significant separation among different groups representing (t1) 24% as the predicted component (to1) depicts 14% as the orthogonal component. According to the findings of this comprehensive study, crude extracts from S. albidoflavus demonstrated varying abilities to impede phytopathogen growth and enhance root and shoot length in tested plants. Through untargeted metabolomics, we discovered numerous potential molecules with antagonistic activity against fungal phytopathogens among the top 10 significant metabolites with the highest absolute log2FC values. These include Tetrangulol, 4-Hydroxybenzaldehyde, and Cyclohexane. Additionally, we identified plant growth-regulating metabolites such as N-Succinyl-L-glutamate, Nicotinic acid, L-Aspartate, and Indole-3-acetamide. The KEGG pathway analysis has highlighted these compounds as potential sources of antimicrobial properties. The inhibitory effect of S. albidoflavus crude extracts on pathogen growth is primarily attributed to the presence of specific gene clusters responsible for producing cyclic peptides such as ansamycins, porphyrin, alkaloid derivatives, and neomycin. Overall, it is apparent that crude extracts from S. albidoflavus exhibited varying abilities to inhibit the growth of three phytopathogens and enhancement in both root and shoot length of tested plants. This research enhances our understanding of how secondary metabolites contribute to growth promotion and biocontrol, supporting ecosystem sustainability and resilience while boosting productivity in sustainable agriculture.

Data from a survey of coffee cultivation in lowland and highland areas to support agriculture during climate change.

This survey aimed to acquire and generate significant information on coffee cultivation in high and low elevations to support agriculture during climate change. This survey dataset helps understand coffee cultivation in highland and lowland areas with diverse climates and environmental conditions for coffee researchers to use this data to improve cultivation and production techniques. In the business scope, this dataset provides a critical vision on the value proposition of the coffee business to maintain conservation and wealth creation of the coffee chain. Similarly, coffee chains can use this data as an example to assess sustainability and carbon literacy. The structured interviews and field trips were conducted at coffee plantations in southern and northern Thailand. The transcript results were manually coded for thematic analysis. This dataset offers insights into anthropogenic plant migration and plant distribution for researchers and academics to use as a valuable resource and good reference in agricultural and biodiversity research. Today, agriculture faces many challenges, such as climate change, water shortage, and improper land management. This information on coffee cultivation at high and low altitudes may help others grow crops in ever-changing climates.

Disparities in COVID-19 vaccine uptake, attitudes, and experiences between food system and non-food system essential workers.

The COVID-19 pandemic has disproportionately affected the health of food system (FS) essential workers compared with other essential and non-essential workers. Even greater disparity exists for workers in certain FS work settings and for certain FS worker subpopulations. We analyzed essential worker respondents (n = 151,789) in May-November 2021 data from the National Immunization Survey Adult COVID Module (NIS-ACM) to assess and characterize COVID-19 vaccination uptake (≥1 dose) and intent (reachable, reluctant), attitudes about COVID-19 and the vaccine, and experiences and difficulties getting the vaccine. We compared rates, overall and by certain characteristics, between workers of the same group, and between FS (n = 17,414) and non-food system (NFS) worker groups (n = 134,375), to determine if differences exist. FS worker groups were classified as "agriculture, forestry, fishing, or hunting" (AFFH; n = 2,730); "food manufacturing facility" (FMF; n = 3,495); and "food and beverage store" (FBS; n = 11,189). Compared with NFS workers, significantly lower percentages of FS workers reported ≥1 dose of COVID-19 vaccine or vaccine requirements at work or school, but overall vaccine experiences and difficulties among vaccinated FS workers were statistically similar to NFS workers. When we examined intent regarding COVID-19 vaccination among unvaccinated FS workers compared with NFS counterparts, we found a higher percentage of FMF and FBS workers were reachable whereas a higher percentage of AFFH workers were reluctant about vaccination, with differences by sociodemographic characteristics. Overall, results showed differences in uptake, intent, and attitudes between worker groups and by some sociodemographic characteristics. The findings reflect the diversity of FS workers and underscore the importance of collecting occupational data to assess health inequalities and of tailoring efforts to worker groups to improve confidence and uptake of vaccinations for infectious diseases such as COVID-19. The findings can inform future research, adult infectious disease interventions, and emergency management planning.

An improved agricultural household margin insurance scheme with insured-insurer risk protection: a time-varying copula approach.

Agricultural household margin insurance (AHMI) is a crop insurance scheme that considers a farmer's trading capability. The scheme examines farmers' losses in terms of both agricultural input and output using the farmer exchange rate index. In this article, we improve the previous design of the AHMI [A. Ahdika, D. Rosadi, A.R. Effendie, and Gunardi, Household margin insurance of agricultural sector in Indonesia using a farmer exchange rate index, Agric. Finance Rev. 81 (2020), pp. 169-188.] proposed to be implemented in Indonesia - which only provided risk protection for companies - by broadening the formula of losses so that risk protection covers both farmers and companies. We also provide premium payment scenarios, both seasonally and non-seasonally. We employ a time-varying Student-t copula with the extended dynamic parameter to identify the dynamic dependency between the indexes involved in determining the loss variable. We also determine the premium rate for the insurance scheme with various payment scenarios and investigate the implications for farmer survival and company management. Examining the farmer exchange rate index data of Indonesia, the empirical results show that the improved AHMI using a time-varying copula approach produces more reasonable loss estimates and various premium payment options with low premium rates for farmers, compared to either the previous AHMI design or the current crop insurance program in Indonesia.

Conservation agriculture practices impact on biological and microbial diversity in earthworm cast under maize-wheat system.

Soil degradation is a major global concern due to its negative impact on soil quality and the sustainability of agricultural resources. The conservation agriculture (CA) approach, which includes three key principles such as zero tillage, retention of crop residue and crop rotation has gained widespread adoption to help mitigate the climate change effects on agricultural soils and meet the growing demand for increased production. Earthworm communities, along with microbial activity and diversity, are highly sensitive to tillage practices. Additionally, microbial activity and diversity quickly respond to different cropping systems, making them effective indicators for detecting short-term changes in soil functioning. We therefore, assess the effects of CA innovative approached after 6-years on biological and microbial diversity within earthworm cast in maize-wheat system (MWS). The treatments consist of PBM-RN0/ZTW-RN0 (permanent beds No-N control-both residues removed and wheat with zero tillage); PBM+RN0/ZTW+RN0 (permanent beds No-N control-both residues retained)-50% of maize stover and 25% of wheat residue retained; PBM-RN120/ZTW- RN120 (permanent beds with 120 kg N ha-1 both residues removed wheat with zero tillage); PBM+RN120/ZTW+RN120 (permanent beds with 120 kg N ha-1 both residues retained and wheat with zero tillage) and FBM-RN120/CTW-RN120 (fresh beds in maize/CT in wheat with 120 kg N ha-1 both residues removed). The result of present study showed that activities of carbon (C) cycle-related enzymes in the cast soils viz., dehydrogenase (DHA), ß-glucosidase (ß-glu), cellulase, and xylanase were significantly higher under PBM+RN120/ ZTW+RN120 than under PBM-RN0/ZTW-RN0. Specifically, the activities of these enzymes were 21.5, 26.8, and 76.5% higher under the PBM+RN120/ZTW+RN120 treatment, respectively. Moreover, the Alk-P activity was found to be 1.3 times higher in the PBM+RN120/ZTW+RN120 treatment than in the PBM-RN0/ZTW-RN0 treatment. The bacterial, fungal, and actinomycete counts in the cast soil ranged from 6.87 to 7.47 CFU (colony forming units) x 106 g-1 soil, 3.87-3.30 CFU x 104 g-1 soil, and 5.09-5.67 CFU x 104 g-1 soil, respectively. Total organic carbon (TOC) showed significant increases of 34.6% under PBM+RN120/ZTW+RN120 as compared to PBM-RN0/ZTW-RN0. The less labile C (Frac. 3), total carbohydrate carbon (TCHO), phenol oxidase (PHE) and peroxidase (PER) were observed as the sensitive indicators under different tillage, rate of nitrogen and residue management practices. This study suggests that permanent beds with crop residue retention with balance fertilization practices can be recommended and popularized to the overall improvement of soil biological pools within earthworm casts in MWS.

Knowledge and perception of antibiotic resistance and stewardship among pre-health and agriculture undergraduate students.

The global threat of antibiotic-resistant infections has resulted in health organizations compiling an Antibiotic Stewardship Program (ASP), in which the education of current and future medical prescribers and farmers is central to the preservation of current and future antimicrobial treatments. The purpose of this study was to assess and compare the knowledge and perceived threat of antibiotics and antibiotic resistance, as well as the perceived benefit of antibiotic stewardship education, among undergraduate students majoring in Biology and Agriculture at Fort Hays State University. I hypothesized that the difference in knowledge and perceptions between Biology and Agriculture students would be significantly different because of differences in curriculum requirements. Framed by the health belief model (HBM), a quantitative cross-sectional study was conducted using a structured online survey of 136 undergraduate student participants. A χ2 analysis was used to assess differences between the respondents in their knowledge and perceptions of antibiotics, antibiotic resistance, and antibiotic stewardship education at the undergraduate level. Results showed that, although Agriculture students perceived antibiotic resistance as less threatening than Biology/pre-health students, both undergraduate groups were knowledgeable about the problem and wanted more academic education on the issue. These findings create a solid foundation to initiate a conversation on the curriculum development to meet ASP goals and objectives at the undergraduate level while contributing to an ongoing international effort to educate future prescribers and farmers on the importance of antibiotics in medicine and farming and to reduce antibiotic resistance.

Tracing scientific and technological development in genetically modified crops.

Genetically Modified (GM) Organisms have been used in various domains since their introduction in the 1980s. According to ISAAA data, the use of GM crops in agriculture has also increased significantly in the past 30 years. However, even after 3 decades of commercialisation, GM crops are still surrounded with controversies with different countries adopting varying approaches to their introduction in the consumer markets, owing to different stances of various stakeholders. Motivated by this multitude of opinions, and absence of knowledge mapping, this study has undertaken scientometric analysis of the publication (Web of Science) and patent (Lens.org) data about genetically modified technology use in agriculture to explore the changing knowledge patterns and technological advancements in the area. It explores both scientific and technological perspectives regarding the use of Genetically Modified Crops, by using publication as well as patent data. The findings of this study highlight the major domains of research, technology development, and leading actors in the ecosystem. These findings can be helpful in taking effective policy decisions, and furthering the research activities. It presents a composite picture using both publications and patent data. Further, it will be of utility to explore the other technologies which are replacing GM technology in agriculture in future studies.

Integration of Diffusion Transformer and Knowledge Graph for Efficient Cucumber Disease Detection in Agriculture.

In this study, a deep learning method combining knowledge graph and diffusion Transformer has been proposed for cucumber disease detection. By incorporating the diffusion attention mechanism and diffusion loss function, the research aims to enhance the model's ability to recognize complex agricultural disease features and to address the issue of sample imbalance efficiently. Experimental results demonstrate that the proposed method outperforms existing deep learning models in cucumber disease detection tasks. Specifically, the method achieved a precision of 93%, a recall of 89%, an accuracy of 92%, and a mean average precision (mAP) of 91%, with a frame rate of 57 frames per second (FPS). Additionally, the study successfully implemented model lightweighting, enabling effective operation on mobile devices, which supports rapid on-site diagnosis of cucumber diseases. The research not only optimizes the performance of cucumber disease detection, but also opens new possibilities for the application of deep learning in the field of agricultural disease detection.

Ergothioneine Improves Seed Yield and Flower Number through FLOWERING LOCUS T Gene Expression in Arabidopsis thaliana.

Biostimulants are a new category of materials that improve crop productivity by maximizing their natural abilities. Out of these biostimulants, those that increase seed production are considered to be particularly important as they contribute directly to the increase in the yield of cereals and legumes. Ergothioneine (EGT) is a natural, non-protein amino acid with antioxidant effects that is used in pharmaceuticals, cosmetics, and foods. However, EGT has not been used in agriculture. This study investigated the effect of EGT on seed productivity in Arabidopsis thaliana. Compared with an untreated control, the application of EGT increased the seed yield by 66%. However, EGT had no effect on seed yield when applied during or after bolting and did not promote the growth of vegetative organs. On the other hand, both the number of flowers and the transcript levels of FLOWERING LOCUS T (FT), a key gene involved in flowering, were increased significantly by the application of EGT. The results suggest that EGT improves seed productivity by increasing flower number through the physiological effects of the FT protein. Furthermore, the beneficial effect of EGT on flower number is expected to make it a potentially useful biostimulant not only in crops where seeds are harvested, but also in horticultural crops such as ornamental flowering plants, fruits, vegetables.