Institute of Agricultural Sciences
Recent publications
An alternative food production system using hydroponics is proposed to grow vegetables in a controlled environment that is implementable in space. The proposed system is an autonomous, modular, scalable, and soilless food production platform (ASFP) that can be installed in a spacecraft by meeting requirements and constraints set by the National Aeronautics and Space Administration (NASA). A suite of Internet of Things (IoT) sensors was used to monitor indoor climate as well as water quality in ASFP. Average values of air temperature and relative humidity in the environmentally-controlled room are maintained between 20–24 °C and 48–62 %, while water quality components, including dissolved oxygen (DO, ppm), electrical conductivity (EC, µS/m), pH, and water temperature (WT, Celsius) are monitored by the IoT sensor in real-time during the growing period. Repeated measure analysis is also performed to evaluate the plant growth performance. The result indicates that plant growth is attributed significantly to pH and EC values. A real-time data visualization and sharing platform is another avenue for the space farming ecosystem in the years to come.
Acer okamotoanum, a medicinally significant endemic plant of Korea, has seen limited genomic research. To address this gap, we conducted a comprehensive sequencing and analysis of its chloroplast genome. The assembled genome is 156,242 bp in length, with typical quadripartite structure, consisting of a large single-copy region, a small single-copy region, and two inverted repeat regions. It contains 130 genes, including 85 protein-coding, 37 tRNA, and 8 rRNA genes. Sixteen genes have a single intron, while clpP and ycf3 possess two introns each. Additionally, 17 genes are duplicated within the inverted repeat regions. The genome analysis revealed 92 Simple Sequence Repeats (SSRs), predominantly located in intergenic regions, with a bias toward A/T-rich codons. Comparative analysis with five closely related Acer species highlighted a highly conserved genomic structure, but also revealed differences in SSRs and repeat sequences. Hypervariable regions, such as rpl32-trnL and ycf1, were identified as potential molecular markers for phylogenetic and population studies. Phylogenetic analysis involving 37 chloroplast genomes confirmed the monophyly of the Acer genus and placed A. okamotoanum within the Platanoidea section, closely related to A. truncatum. This study improves the understanding of A. okamotoanum’s genomic structure, offering insights for phylogenetic analysis, marker development, and conservation efforts.
Erwinia amylovora, first identified in 1793 in Hudson Valley (New York, USA), has a genome size of 3.7-4.0 Mb. E. amylovora bacterial strains are classified based on the infecting hosts: the Amygdaloideae-infecting (AI) group, targeting apple and pear trees, and the Rubus-infecting group, affecting berry trees. Since the AI-group strains display high genetic similarity (˃99.7%), it is challenging to characterize their genotypes. This study investigated the genetic diversity of E. amylovora isolates in Korea and the regional distribution patterns of genotypes using a multilocus variable number of tandem repeat analysis (MLVA). Four specific primers were used to amplify and sequence tandem repeats in the E. amylovora genome, and a distribution map of E. amylovora was created using MLVA genotypes. Thirty-two types of MLVA patterns were identified in Korean strains, and RV19 was the dominant type identified in all South Korean regions. According to the minimal spanning tree, genotypes were differentiated into RV7, RV14, RV20, RV22, and RV27 types, originating from the RV19 type. This finding suggests that the RV19 type, introduced to Korea for the first time, spread to other regions from Anseong-si, Cheonan-si, Chungju-si, and Jecheon-si, depending on the type. We determined the MLVA genotypes of E. amylovora isolates and distribution patterns by region from 2019 to 2023. The distribution of these genotypes by year and region provides basic information for the genetic diversity and spread of E. amylovora in Korea.
Nitrogen loss during the composting process is a great challenge that can lead to environmental pollution and reduce compost quality. Lime is often added to the composting mixture to increase the pH, speed-up the decomposition process, and lower the release of toxic gases like ammonia. However, the specific effects of lime on nitrogen dynamics, particularly ammoniacal nitrogen and nitrate nitrogen levels, as well as CO2 emissions, remain areas of active investigation. This study investigates the influence of hydrated lime on nitrogen conservation when added to poultry manure and agricultural waste. To evaluate the level of nitrogen retention and overall compost stability, poultry waste and agricultural waste were co-composted with and without hydrated lime amendment under controlled environmental conditions. The results showed that, in comparison to the control, the lime-treated compost had higher nitrate nitrogen levels (1800 mg/kg) and lower ammoniacal nitrogen levels (100 mg/kg), indicating improved nitrogen retention. Furthermore, CO2 emissions in the compost treated with hydrated lime were higher in the early phases, however substantially dropped as the compost matured, indicating a faster stabilization process. The findings of 16 S rRNA sequencing showed that lime-treated composting was dominated by Thermobifida, Thermobacillus, and Saccharomonospora, all of which were known as cellulolytic bacteria and involved in organic matter degradation. Also, significant bacterial shifts were observed during the thermophilic phase. The Pseudomonas population, which is often associated with the denitrification process, was lower than the control, thus, promoting nitrogen retention. The results imply that lime amendment improves composting stability and quality by increasing nitrogen content while reducing organic matter. This work advances the understanding and knowledge on the influence of lime in composting by providing useful insights into the microbial community that can be used for improving the process.
Background The analysis of changes in subcellular water distribution during mushroom fruiting is essential for elucidating the movement of water molecules within subcellular compartments. However, prior research on mushrooms has predominantly concentrated on alterations in water status during drying and postharvest processes in the food processing sector. Knowledge regarding subcellular water compartments throughout mushroom growth and fruiting remains limited. In the present study, the dynamics of subcellular water status across various growth stages of Agaricus bisporus were investigated using LF-NMR relaxometry. Results Three components were resolved from transverse relaxation curves, assigned to cell wall, cytoplasmic and vacuolar water, in both whole mushroom and mushroom tissues (stalk and Pileus). As fruiting body developed, the proton degree of freedom of three water fractions determined by T2 measurement all increased. The T2 values of three water fractions in stalk were higher than those in pileus during the first three stages, whereas they became lower compared to those in pileus from somewhere between the two stages of 2–3 and 3–4. Apparently different patterns of change in three water contents were observed, indicating the variations in water distribution at subcellular level. Furthermore, relative humidities caused obvious changes in water status. In addition, highly significant correlations were observed between T2 and textural parameters, indicating that the dynamics of water status exert a substantial influence on the formation of mushroom quality. Conclusions A consistent increase in the transverse proton degree of freedom of three distinct water fractions, accompanied by markedly divergent patterns in the variations of the three water contents, was observed across different growth stages of fruiting bodies. Subsequently, highly significant correlations between T2 and textural parameters were established. This study would contribute to reveal macroscopic water transport within mushroom tissues and provide theoretical insights for optimizing high-quality mushroom cultivation. Graphical Abstract
We report the whole genome sequences of Paenibacillus kyungheensis KACC 18744 T , Sphingomonas naphthae KACC 18716 T , and Novosphingobium humi KACC 19094 T , to investigate the genomic diversity of bacterial type strains distributed in Korea.
This study presents the fabrication of a sustainable flexible humidity sensor utilizing chitosan derived from mealworm biomass as the primary sensing material. The chitosan-based humidity sensor was fabricated by casting chitosan and polyvinyl alcohol (PVA) films with interdigitated copper electrodes, forming a laminate composite suitable for real-time, resistive-type humidity detection. Comprehensive characterization of the chitosan film was performed using Fourier-transform infrared (FTIR) spectroscopy, contact angle measurements, and tensile testing, which confirmed its chemical structure, wettability, and mechanical stability. The developed sensor exhibited a broad range of measurements from 6% to 97% relative humidity (RH), a high sensitivity of 2.43 kΩ/%RH, and a rapid response time of 18.22 s with a corresponding recovery time of 22.39 s. Moreover, the chitosan-based humidity sensor also demonstrated high selectivity for water vapor when tested against various volatile organic compounds (VOCs). The superior performance of the sensor is attributed to the structural properties of chitosan, particularly its ability to form reversible hydrogen bonds with water molecules. This mechanism was further elucidated through molecular dynamics simulations, revealing that the conductivity in the sensor is modulated by proton mobility, which operates via the Grotthuss mechanism under high-humidity and the packed-acid mechanism under low-humidity conditions. Additionally, the chitosan-based humidity sensor was further seamlessly integrated into an Internet of Things (IoT) framework, enabling wireless humidity monitoring and real-time data visualization on a mobile device. Comparative analysis with existing polymer-based resistive-type sensors further highlighted the superior sensing range, rapid dynamic response, and environmental sustainability of the developed sensor. This eco-friendly, biomass-derived, eco-friendly sensor shows potential for applications in environmental monitoring, smart agriculture, and industrial process control.
Carbonic anhydrases (CAs) are ubiquitous enzymes that catalyze reversibly both the hydration and dehydration reactions of CO2 and HCO3-, respectively. Higher plants contain many different isoforms of CAs that can be classified into α-, β- and γ-type subfamilies. β-type CAs play a key role in the CO2-concentrating mechanism, thereby contributing to efficient photosynthesis in the C4 plants in addition to many other biochemical reactions in plant metabolism. Here, we characterized at the molecular, cellular and biochemical levels two β-type CAs in Bienertia sinuspersici, a plant that operates a C4 carbon concentrating mechanism within individual cells without the Kranz anatomy. These two β-type CAs (BsCAβs), named BsCAβ1 and BsCAβ2, in Bienertia were strongly induced along with maturation of leaves. Both BsCAβ1 and BsCAβ2 existed as a dimeric form in vivo but showed differential localization. BsCAβ2 was localized exclusively to the plasma membrane in Bienertia and when expressed heterologously in the C3 Arabidopsis. In contrast, BsCAβ1 largely localized to the cytosol together with a portion to the plasma membrane (PM) in both plants. BsCAβ2 had two cysteine residues at the N-terminal region for palmitoylation and their substitution with serine residues led to a change in the localization from the plasma membrane (PM) to the cytosol. Thus, we propose that BsCAβ2 localizes to the PM using a lipid moiety added posttranslationally plays a role in conversion of cytosolic CO2 into HCO3- as part of the CO2-concentrating mechanism, thereby contributing to the single-cell C4 photosynthesis in Bienertia.
Global agricultural challenges, especially soil degradation caused by abiotic stresses, significantly reduce crop productivity and require innovative solutions. Biochar (BC), a biodegradable product derived from agricultural and forestry residues, has been proven to significantly enhance soil quality. Although its benefits for improving soil properties are well-documented, the potential of BC to mitigate various abiotic stresses-such as drought, salinity, and heavy metal toxicity-and its effect on plant traits need further exploration. This review aims to elucidate BC production by highlighting primary feedstock’s and synthesis techniques, and examining its role in boosting soil decomposition efficiency and fertility, which are pivotal for sustainable crop growth. This review also discuss how BC can enhance the nutritional and chemical properties of soil under different abiotic stress conditions, emphasizing its capacity to foster crop growth and development in adverse environments. Furthermore, this article serves as a comprehensive resource for agricultural researchers in understanding the importance of BC in promoting sustainable agriculture, and addressing environmental challenges. Ultimately, this review highlights critical knowledge gaps and proposes future research avenues on the bio-protective properties of BC against various abiotic stresses, paving the way for the commercialization of BC applications on a large scale with cutting-edge technologies.
One of the problems brought by that biological control has become one of the important ways to overcome soil borne plant diseases in green tobacco production. Which ensuring the safety of tobacco production. There are many advantages on that microbial technology is a key factor in green tobacco prevention and control. The main novelty of this work is that the current research status of important pests and diseases in the green production process of tobacco, as well as the research status of important green prevention and control technologies for tobacco, which appears to provide guidance for the research and development of low-carbon inputs for green tobacco production, as well as high quality production throughout the process. Therefore, it is more meaningful to explore the occurrence patterns of that comprehensive biological control measures can effectively prevent and control the occurrence of major tobacco pests and diseases, significantly improve the yield and output value of tobacco, and effectively improve the soil microbial community, with good prospects for promotion and application. This has been demonstrated in a number of studies that showed that tobacco diseases and pests are influenced by host varieties, climate conditions, human factors, and other factors, and their occurrence has a certain regularity. Previous studies have focused on the fact that tobacco diseases and pests are not only limited to affecting the quantity and quality of tobacco but also affect the economic benefits of the tobacco industry. Therefore, the main aim of the present study was to study the biological control mechanisms of different tobacco pests and diseases, as well as the main limiting factors in tobacco production.
In this study, anthocyanin glycosides from nine cultivars of highbush blueberries grown in Korea were characterized using UPLC-DAD-QToF/MS and UPLC-Qtrap-MS/MS. A total of twenty-two derivatives were identified, consisting of mono-glycosides and acetyl-glycosides attached to aglycones, such as cyanidin, peonidin, delphinidin, petunidin, and malvidin. Among them, seven acetylated glycosides were tentatively determined by comparing the related authentic standards and previous reports and presented mass fragmentation, in which the acetyl group remained as the form attached to the sugar without de-esterification in positive ionization mode. The mid-season cultivar ‘New Hanover’ showed the highest total anthocyanin content (1011.7 mg/100 g dry weight) with predominant malvidin and delphinidin glycosides. Particularly, the ‘Patriot’ (early season) recorded the highest proportion of acetylated glycosides (19.7%). Multivariate analysis showed a distinct separation between early and mid-seasons with Draper. Especially, delphinidin 3-O-galactoside (VIP = 1.94) was identified as a marker for mid-season, and malvidin 3-O-glucoside (VIP = 1.79) was identified as a marker for early season. These comprehensive anthocyanin profiles of Korean blueberries will serve as fundamental data for breeding superior cultivars, evaluating and developing related products as well as clinical and metabolomic research.
Information and communication technology (ICT) components, especially actuators in automated irrigation systems, are essential for managing precise irrigation and optimal soil moisture, enhancing orchard growth and yield. However, actuator malfunctions can lead to inefficient irrigation, resulting in water imbalances that impact crop health and reduce productivity. The objective of this study was to develop a signal processing technique to detect potential malfunctions based on the power consumption level and operating status of actuators for an automated orchard irrigation system. A demonstration orchard with four apple trees was set up in a 3 m × 3 m soil test bench inside a greenhouse, divided into two sections to enable independent irrigation schedules and management. The irrigation system consisted of a single pump and two solenoid valves controlled by a Python-programmed microcontroller. The microcontroller managed the pump cycling ‘On’ and ‘Off’ states every 60 s and solenoid valves while storing and transmitting sensor data to a smartphone application for remote monitoring. Commercial current sensors measured actuator power consumption, enabling the identification of normal and abnormal operations by applying threshold values to distinguish activation and deactivation states. Analysis of power consumption, control commands, and operating states effectively detected actuator operations, confirming reliability in identifying pump and solenoid valve failures. For the second solenoid valve in channel 2, with 333 actual instances of normal operation and 60 actual instances of abnormal operation, the model accurately detected 316 normal and 58 abnormal instances. The proposed method achieved a mean average precision of 99.9% for detecting abnormal control operation of the pump and solenoid valve of channel 1 and a precision of 99.7% for the solenoid valve of channel 2. The proposed approach effectively detects actuator malfunctions, demonstrating the potential to enhance irrigation management and crop productivity. Future research will integrate advanced machine learning with signal processing to improve fault detection accuracy and evaluate the scalability and adaptability of the system for larger orchards and diverse agricultural applications.
The close genetic resemblance between Listeria monocytogenes and Listeria innocua, combined with their presence in similar environments, poses challenges for species-specific detection in food products. Ensuring food safety through microbiological standards necessitates reliable detection of pathogens like L. monocytogenes and L. innocua throughout the food chain using appropriate analytical techniques. This study aims to develop, identify, and validate a SYBR Green qPCR-based genetic marker designed to detect L. monocytogenes and L. innocua. By performing a comparative analysis of the complete genome sequences of L. monocytogenes (ATCC 12392) and L. innocua (CFSAN044836), a unique gene region encoding a hypothetical protein with an LPXTG cell wall anchor domain (GCF_003031895.1) in L. monocytogenes and leucine-rich repeats (GCF_009648575.1) in L. innocua was identified. Primers targeting these specific region were designed and validated for their effectiveness in detecting L. monocytogenes/L. innocua using both conventional PCR and qPCR techniques. These primers exhibited high sensitivity and specificity in amplifying L. monocytogenes and L. innocua among different Listeria species. The sensitivity and specificity of the primers were further confirmed through standard curve analysis using three different templates: cloned DNA (as a positive control), genomic DNA, and bacterial cell suspension. Additionally, the primers were rigorously tested and validated for their accuracy in directly detecting the targeted strains in live enoki mushroom samples. This direct qPCR method offers significant advantages for the rapid and precise detection of L. monocytogenes and L. innocua, potentially enhancing the efficiency of diagnostic and monitoring processes within food and vegetable distribution systems. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-81508-6.
Continuous cropping obstacles are significant factors that limit the yield and quality of tobacco. Thus, the selection and breeding of varieties is a crucial strategy for mitigating these challenges. However, the effects and mechanisms by which different tobacco varieties influence the structural composition of soil microbial remain unclear. To address this, we conducted a field experiment involving five tobacco varieties (K326, K394, XL, Y87, and Y97) and two types of soil (continuous cropping obstacle soil and normal soil). We examined microbial responses to different tobacco varieties in each soil type. Our results revealed that soil available nutrients and organic matter were decreased in obstacle soil compared to normal soil. The fresh biomass decreased by 18.05–27.92% in obstacle soil (except K394 and Y97). The microbial community composition in the rhizosphere soil remained consistent in various tobacco varieties in obstacle soil. The connections between soil fertility nutrients and microbial communities were reduced in obstacle soil compared to normal soil. The alteration of bacterial community composition was a stochastic process, whereas the modification of fungal community composition was a deterministic process in obstacle soil. Furthermore, the abundance of differential fungi (Zoopagomycota) was notably higher in obstacle soil. Overall, our results revealed that the disturbance of microbial communities and soil degradation in the obstacle soil are primary factors contributing to reduced crop yields. Therefore, it is an economical strategy for overcoming continuous cropping obstacles by utilizing rhizosphere microecology through multi-variety planting.
Unmanned aerial vehicle (UAV) imaging provides the ability to obtain high-resolution images at a lower cost than satellite imagery and aerial photography. However, multiple UAV images need to be mosaicked to obtain images of large areas, and the resulting UAV multispectral image mosaics typically contain seam lines. To address this problem, we applied irradiance, vignette, and bidirectional reflectance distribution function (BRDF) filters and performed field work using a DJI Mavic 3 Multispectral (M3M) camera to collect data. We installed a calibrated reference tarp (CRT) in the center of the collection area and conducted three types of flights (BRDF, vignette, and validation) to measure the irradiance, radiance, and reflectance—which are essential for irradiance correction—using a custom reflectance box (ROX). A vignette filter was generated from the vignette parameter, and the anisotropy factor (ANIF) was calculated by measuring the radiance at the nadir, following which the BRDF model parameters were calculated. The calibration approaches were divided into the following categories: a vignette-only process, which solely applied vignette and irradiance corrections, and the full process, which included irradiance, vignette, and BRDF. The accuracy was verified through a validation flight. The radiance uncertainty at the seam line ranged from 3.00 to 5.26% in the 80% lap mode when using nine images around the CRT, and from 4.06 to 6.93% in the 50% lap mode when using all images with the CRT. The term ‘lap’ in ‘lap mode’ refers to both overlap and sidelap. The images that were subjected to the vignette-only process had a radiance difference of 4.48–6.98%, while that of the full process images was 1.44–2.40%, indicating that the seam lines were difficult to find with the naked eye and that the process was successful.
Apple cultivation is expected to shift from low latitude to high latitude regions of Korea due to climate change. However, there is a lack of research on selecting suitable apple cultivars for high-latitude regions in Korea. Therefore, the objective of this study was to investigate the effect of genotype × environment interactions (GEI) on apple fruit quality and to identify stable apple genotypes that performed well in these regions. The fruit quality characteristics of eight apple genotypes cultivated in two locations over 2 years were analyzed using additive main effects and multiplicative interaction (AMMI), genotype × genotype environment (GGE) biplot, and multi-trait stability index (MTSI). The results showed significant difference among the genotypes, environment, and their interaction for all fruit quality characteristics. Genotypes had the greatest contribution to the total variance for fruit weight, total phenolic content, soluble solid content, and radical scavenging activity, whereas the environment contributed more to fruit firmness, total flavonoid content, and vitamin C at varying levels. The GEI was also found to be significant for all traits with medium to high contributions. The AMMI and GGE biplots were divided GEI into two interaction principal component analysis (IPCA), and explained significant variation for all traits, respectively. Based on combined multiple traits, ‘Shinano Gold’, ‘Fuji’, ‘Picnic’, and ‘Hongro’ were selected as stable genotypes by the MTSI model. These results offer opportunities for sustainable apple production in Korea.
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213 members
Ramesh Chand
  • Mycology and Plant Pathology
Kartikeya Srivastava
  • Genetics & Plant Breeding
Jai Prakash Srivastava
  • Department of Plant Physiology
Akansha Jain
  • Department of Plant Pathology
Harikesh Bahadur Singh
  • Department of Mycology and Plant Pathology
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Varanasi, India