Comparative transcriptomic analysis of the nodulation-competent zone and inference of transcription regulatory network in silicon applied Glycine max [L.]-Merr. Roots.

KEY MESSAGE: The study unveils Si's regulatory influence by regulating DEGs, TFs, and TRs. Further bHLH subfamily and auxin transporter pathway elucidates the mechanisms enhancing root development and nodulation. Soybean is a globally important crop serving as a primary source of vegetable protein for millions of individuals. The roots of these plants harbour essential nitrogen fixing structures called nodules. This study investigates the multifaceted impact of silicon (Si) application on soybean, with a focus on root development, and nodulation employing comprehensive transcriptomic analyses and gene regulatory network. RNA sequence analysis was utilised to examine the change in gene expression and identify the noteworthy differentially expressed genes (DEGs) linked to the enhancement of soybean root nodulation and root development. A set of 316 genes involved in diverse biological and molecular pathways are identified, with emphasis on transcription factors (TFs) and transcriptional regulators (TRs). The study uncovers TF and TR genes, categorized into 68 distinct families, highlighting the intricate regulatory landscape influenced by Si in soybeans. Upregulated most important bHLH subfamily and the involvement of the auxin transporter pathway underscore the molecular mechanisms contributing to enhanced root development and nodulation. The study bridges insights from other research, reinforcing Si's impact on stress-response pathways and phenylpropanoid biosynthesis crucial for nodulation. The study reveals significant alterations in gene expression patterns associated with cellular component functions, root development, and nodulation in response to Si.

Chitosan-GSNO Nanoparticles and Silicon Priming Enhance the Germination and Seedling Growth of Soybean (Glycine max L.).

Soybean, a major legume crop, has seen a decline in its production owing to challenges in seed germination and the development of seedlings. Thus, in this study, we systematically investigated the influence of various chitosan-S-nitrosoglutathione (chitosan-GSNO) nanoparticle (0, 25, 50, and 100 µM) and Si (0, 0.5, and 1 mM) priming concentrations on soybean seed germination and seedling growth over five different priming durations (range: 1-5 h at each concentration). Significant differences were observed in all parameters, except seedling diameter, with both treatments. Seed germination was significantly enhanced after 3 h of priming in both treatments. The final germination percentage (FGP), peak germination percentage (PGP), vigor index (VI), seedling biomass (SB), hypocotyl length (HL), and radical length (RL) of 100 µM chitosan-GSNO-nanoparticle-primed seeds increased by 20.3%, 41.3%, 78.9%, 25.2%, 15.7%, and 65.9%, respectively, compared with those of the control; however, the mean germination time (MGT) decreased by 18.43%. Si priming at 0.5 mM increased the FGP, PGP, VI, SB, HL, and RL by 13.9%, 55.17%, 39.2%, 6.5%, 22.5%, and 25.1%, respectively, but reduced the MGT by 12.29% compared with the control treatment. Chitosan-GSNO and Si treatment up-regulated the relative expression of gibberellic acid (GA)-related genes (GmGA3ox3 and GmGA2ox1) and down-regulated that of abscisic acid (ABA)-related genes (GmABA2, GmAAO3, and GmNCED5). Chitosan-GSNO and Si application increased bioactive GA4 levels and simultaneously reduced ABA content. Hence, the use of exogenous chitosan-GSNO nanoparticles and Si as priming agents had a beneficial effect on seed germination and seedling growth because of the up-regulation in the expression of GA and down-regulation in the expression of ABA. Additional research is needed to understand the combined impact of Si and chitosan-GSNO nanoparticles, including their effects on the expression levels of other hormones and genes even in the later growth stage of the crop.

Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data.

Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.

Chitosan-GSNO nanoparticles: a positive modulator of drought stress tolerance in soybean.

BACKGROUND: Chitosan biopolymer is an emerging non-toxic and biodegradable plant elicitor or bio-stimulant. Chitosan nanoparticles (CSNPs) have been used for the enhancement of plant growth and development. On the other hand, NO is an important signaling molecule that regulates several aspects of plant physiology under normal and stress conditions. Here we report the synthesis, characterization, and use of chitosan-GSNO nanoparticles for improving drought stress tolerance in soybean. RESULTS: The CSGSNONPs released NO gas for a significantly longer period and at a much lower rate as compared to free GSNO indicating that incorporation of GSNO in CSNPs can protect the NO-donor from rapid decomposition and ensure optimal NO release. CS-GSNONPs improved drought tolerance in soybean plants reflected by a significant increase in plant height, biomass, root length, root volume, root surface area, number of root tips, forks, and nodules. Further analyses indicated significantly lower electrolyte leakage, higher proline content, higher catalase, and ascorbate peroxidase activity, and reduction in MDA and H2O2 contents after treatment with 50 µM CS-GSNONPs under drought stress conditions. Quantitative real-time PCR analysis indicated that CS-GSNONPs protected against drought-induced stress by regulating the expression of drought stress-related marker genes such as GmDREB1a, GmP5CS, GmDEFENSIN, and NO-related genes GmGSNOR1 and GmNOX1. CONCLUSIONS: This study highlights the potential of nano-technology-based delivery systems for nitric oxide donors to improve plant growth, and development and protect against stresses.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean.

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

Automatic Evaluation of Soybean Seed Traits Using RGB Image Data and a Python Algorithm.

Soybean (Glycine max) is a crucial legume crop known for its nutritional value, as its seeds provide large amounts of plant protein and oil. To ensure maximum productivity in soybean farming, it is essential to carefully choose high-quality seeds that possess desirable characteristics, such as the appropriate size, shape, color, and absence of any damage. By studying the relationship between seed shape and other traits, we can effectively identify different genotypes and improve breeding strategies to develop high-yielding soybean seeds. This study focused on the analysis of seed traits using a Python algorithm. The seed length, width, projected area, and aspect ratio were measured, and the total number of seeds was calculated. The OpenCV library along with the contour detection function were used to measure the seed traits. The seed traits obtained through the algorithm were compared with the values obtained manually and from two software applications (SmartGrain and WinDIAS). The algorithm-derived measurements for the seed length, width, and projected area showed a strong correlation with the measurements obtained using various methods, with R-square values greater than 0.95 (p < 0.0001). Similarly, the error metrics, including the residual standard error, root mean square error, and mean absolute error, were all below 0.5% when comparing the seed length, width, and aspect ratio across different measurement methods. For the projected area, the error was less than 4% when compared with different measurement methods. Furthermore, the algorithm used to count the number of seeds present in the acquired images was highly accurate, and only a few errors were observed. This was a preliminary study that investigated only some morphological traits, and further research is needed to explore more seed attributes.

RDA-Genebank and Digital Phenotyping for Next-Generation Research on Plant Genetic Resources.

The National Agrobiodiversity Center under the Rural Development Administration (RDA) in Jeonju, Republic of Korea stands as the foremost national genebank in the country. Over the years, the National Agrobiodiversity Center has remained committed to enriching its collection with foreign genetic resources, elevating its status to a world-class plant genetic resources (PGR)- holding genebank. Currently, several steps are being undertaken to improve the accessibility of the collection to national as well as international researchers, improve the data available on the resources, and amend the passport information for the accessions. With the implementation of the Nagoya Protocol, the origin of genetic resources is being highlighted as an important input in the passport information. The RDA-Genebank actively responds to the Nagoya Protocol by supplementing passport data for resources lacking information on their origin. In addition, a large number of conserved resources are continuously multiplied, and agronomic traits are investigated concurrently. With the traditional methods of characterization of the germplasm requiring a significant amount of time and effort, we have initiated high-throughput phenotyping using digital techniques to improve our germplasm data. Primarily, we have started adding seed phenotype information followed by measuring root phenotypes which are stored under agronomic traits. This may be the initial step toward using largescale high-throughput techniques for a germplasm. In this study, we aim to provide an introduction to the RDA-Genebank, to adopted international standards, and to the establishment of high-throughput phenotyping techniques for the improvement of passport information.

Spray dried progesterone formulations for carrier free dry powder inhalation.

Low oral absorption and extensive first pass metabolism of progesterone is reported for many oral formulations which warrants investigation into other routes of administration. It is the aim of this study to investigate the generation of inhaled formulations of progesterone though a spray drying approach with a focus on how spray drying impacts the physicochemical properties of progesterone. Formulations of progesterone with L-leucine and hydroxypropyl methylcellulose acetate succinate (HPMCAS) are reported to this aim. X-ray diffraction, spectroscopy and thermal analysis were used to characterise these formulations and confirmed that progesterone crystallises as the Form II polymorph during spray drying regardless of the solvent used. The resultant formulations showed higher aqueous solubility than progesterone Form I starting material and the addition of HPMCAS was shown to temporarily enable a supersaturated state. Thermal analysis was used to show that the Form II polymorph was sensitive to transformation to Form I during heating. The addition of L-leucine to the formulations reduced the temperature for the polymorphic transformation by âˆ¼ 10 °C. However, when HPMCAS was added to the formulation, the Form II polymorph was prevented from transforming to the Form I polymorph. Cascade impaction was used to determine the aerosol performance of the spray dried powders and showed promising lung deposition profiles (mass median aerodynamic diameter 5 µm) with significant variation depending on the organic solvent used and the ratio of organic to aqueous phase in the feedstock. However, further optimisation of formulations was required to direct more progesterone into the alveolar regions. The addition of HPMCAS was seen to increase the alveolar deposition and therefore formed a formulation with a lower fine particle fraction and mass median aerodynamic diameter. The most suitable formulation for inhalation was formed from a 50:50 acetone:water mixture and showed an ED, FPF and FPD of 81.7%, 44.5% and 7.3 mg respectively. Therefore, HPMCAS is suggested as a suitable excipient to increase solubility, prevent polymorphic transformation and improve inhalation properties of spray dried progesterone formulations. This study highlights the use of spray drying to form inhalable progesterone powders with higher solubility which may broaden the application of this medicine.

Evaluating the Effectiveness of Calcium Silicate in Enhancing Soybean Growth and Yield.

The application of silicon (Si) fertilizer positively impacts crop health, yield, and seed quality worldwide. Si is a "quasi-essential" element that is crucial for plant nutrition and stress response but is less associated with growth. This study aimed to investigate the effect of Si on the yield of cultivated soybean (Glycine max L). Two locations, Gyeongsan and Gunwi, in the Republic of Korea were selected, and a land suitability analysis was performed using QGIS version 3.28.1. The experiments at both locations consisted of three treatments: the control, Si fertilizer application at 2.3 kg per plot (9 m × 9 m) (T1), and Si fertilizer application at 4.6 kg per plot (9 m × 9 m) (T2). The agronomic, root, and yield traits, as well as vegetative indices, were analyzed to evaluate the overall impact of Si. The results demonstrated that Si had consistently significant effects on most root and shoot parameters in the two experimental fields, which led to significantly increased crop yield when compared with the control, with T2 (22.8% and 25.6%, representing an output of 2.19 and 2.24 t ha-1 at Gyeongsan and Gunwi, respectively) showing a higher yield than T1 (11% and 14.2%, representing 1.98 and 2.04 t ha-1 at Gyeongsan and Gunwi, respectively). These results demonstrate the positive impact of exogenous Si application on the overall growth, morphological and physiological traits, and yield output of soybeans. However, the application of the optimal concentration of Si according to the crop requirement, soil status, and environmental conditions requires further studies.

Impact of varying food hardness on mastication/swallowing.

The purpose of this study was to analyze mastication and swallowing in the elderly and confirm the association with dysphagia characteristics. A questionnaire was developed to evaluate the masticating and swallowing functions of the elderly. Mastication was analyzed using electromyography, and tongue/lip pressures were measured using Iowa Oral Performance Instrument. The results of the questionnaire showed that statistical difference in the number of teeth between the group without and with, decreased ability to swallow, and there was a correlation with lip pressure. Additionally, the higher number of teeth, the higher muscle activity, and there is a positive correlation between the number of chews and the lip pressure. Consequently, our findings suggested oral health parameters are closely associated with mastication/swallowing ability. Finally, based on the results obtained for different foods tested, we suggested that texture-modified foods are necessary to enhance swallowing ability.

A novel study on bean common mosaic virus accumulation shows disease resistance at the initial stage of infection in Phaseolus vulgaris.

Accurate and early diagnosis of bean common mosaic virus (BCMV) in Phaseolus vulgaris tissues is critical since the pathogen can spread easily and have long-term detrimental effects on bean production. The use of resistant varieties is a key factor in the management activities of BCMV. The study reported here describes the development and application of a novel SYBR Green-based quantitative real-time PCR (qRT-PCR) assay targeting the coat protein gene to determine the host sensitivity to the specific NL-4 strain of BCMV. The technique showed high specificity, validated by melting curve analysis, without cross-reaction. Further, the symptoms development of twenty advanced common bean genotypes after mechanical BCMV-NL-4 infection was evaluated and compared. The results showed that common bean genotypes exhibit varying levels of host susceptibility to this BCMV strain. The YLV-14 and BRS-22 genotypes were determined as the most resistant and susceptible genotypes, respectively, in terms of aggressiveness of symptoms. The accumulation of BCMV was analyzed in the resistant and susceptible genotypes 3, 6, and 9 days following the inoculation by the newly developed qRT-PCR. The mean cycle threshold (Ct) values showed that the viral titer was significantly lower in YLV-14, which was evident in both root and leaf 3 days after the inoculation. The qRT-PCR thus facilitated an accurate, specific, and feasible assessment of BCMV accumulation in bean tissues even in low virus titers, allowing novel clues in selecting resistant genotypes in the early stages of infection, which is critical for disease management. To the best of our knowledge, this is the first study of a successfully performed qRT-PCR to estimate BCMV quantification.

Evaluation of Soybean Wildfire Prediction via Hyperspectral Imaging.

Plant diseases that affect crop production and productivity harm both crop quality and quantity. To minimize loss due to disease, early detection is a prerequisite. Recently, different technologies have been developed for plant disease detection. Hyperspectral imaging (HSI) is a nondestructive method for the early detection of crop disease and is based on the spatial and spectral information of images. Regarding plant disease detection, HSI can predict disease-induced biochemical and physical changes in plants. Bacterial infections, such as Pseudomonas syringae pv. tabaci, are among the most common plant diseases in areas of soybean cultivation, and have been implicated in considerably reducing soybean yield. Thus, in this study, we used a new method based on HSI analysis for the early detection of this disease. We performed the leaf spectral reflectance of soybean with the effect of infected bacterial wildfire during the early growth stage. This study aimed to classify the accuracy of the early detection of bacterial wildfire in soybean leaves. Two varieties of soybean were used for the experiment, Cheongja 3-ho and Daechan, as control (noninoculated) and treatment (bacterial wildfire), respectively. Bacterial inoculation was performed 18 days after planting, and the imagery data were collected 24 h following bacterial inoculation. The leaf reflectance signature revealed a significant difference between the diseased and healthy leaves in the green and near-infrared regions. The two-way analysis of variance analysis results obtained using the Python package algorithm revealed that the disease incidence of the two soybean varieties, Daechan and Cheongja 3-ho, could be classified on the second and third day following inoculation, with accuracy values of 97.19% and 95.69%, respectively, thus proving his to be a useful technique for the early detection of the disease. Therefore, creating a wide range of research platforms for the early detection of various diseases using a nondestructive method such HSI is feasible.

Antioxidant effects and reaction volatiles from heated mixture of soy protein hydrolysates and coconut oil.

Soy protein hydrolysates (SPHs) are prepared from soybean meal using commercially available protease enzymes and acid/alkali treatment. The antioxidant properties of SPHs were evaluated by measuring headspace oxygen consumption and conjugated diene formation in oil-in-water (O/W) emulsions. In addition, volatile profiles were analyzed for the heated mixture of SPHs and the coconut oil (SPHCO). Total amino acid content was the highest in double proteases. SPHs prepared from enzymes acted as better antioxidants than those prepared from acid/alkali treatments in O/W emulsions. SPHs prepared from double proteases generated the highest amounts of total volatiles and nitrogen-containing compounds in SPHCO. 2,3-Dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one, 2-methyl-butanal, benzeneacetaldehyde, and 2,6-dimethylpyrazine were the major volatiles in SPHCO. Enzymatic SPHs act as natural antioxidants in the O/W emulsion matrix, and thermal reaction products from SPHCO may contribute to the production of a unique volatile flavor in plant protein-based foods. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-022-01189-7.

Implication of high variance in germplasm characteristics.

The beauty of conserving germplasm is the securement of genetic resources with numerous important traits, which could be utilized whenever they need to be incorporated into current cultivars. However, it would not be as useful as expected if the proper information was not given to breeders and researchers. In this study, we demonstrated that there is a large variation, both among and within germplasm, using a low-cost image-based phenotyping method; this could be valuable for improving gene banks' screening systems and for crop breeding. Using the image analyses of 507 accessions of buckwheat, we identified a wide range of variations per trait between germplasm accessions and within an accession. Since this implies a similarity with other important agronomic traits, we suggest that the variance of the presented traits should be checked and provided for better germplasm enhancement.

Genome-Wide Association Studies of Seven Root Traits in Soybean (Glycine max L.) Landraces.

Soybean [Glycine max (L.) Merr.], an important oilseed crop, is a low-cost source of protein and oil. In Southeast Asia and Africa, soybeans are widely cultivated for use as traditional food and feed and industrial purposes. Given the ongoing changes in global climate, developing crops that are resistant to climatic extremes and produce viable yields under predicted climatic conditions will be essential in the coming decades. To develop such crops, it will be necessary to gain a thorough understanding of the genetic basis of agronomic and plant root traits. As plant roots generally lie beneath the soil surface, detailed observations and phenotyping throughout plant development present several challenges, and thus the associated traits have tended to be ignored in genomics studies. In this study, we phenotyped 357 soybean landraces at the early vegetative (V2) growth stages and used a 180 K single-nucleotide polymorphism (SNP) soybean array in a genome-wide association study (GWAS) conducted to determine the phenotypic relationships among root traits, elucidate the genetic bases, and identify significant SNPs associated with root trait-controlling genomic regions/loci. A total of 112 significant SNP loci/regions were detected for seven root traits, and we identified 55 putative candidate genes considered to be the most promising. Our findings in this study indicate that a combined approach based on SNP array and GWAS analyses can be applied to unravel the genetic basis of complex root traits in soybean, and may provide an alternative high-resolution marker strategy to traditional bi-parental mapping. In addition, the identified SNPs, candidate genes, and diverse variations in the root traits of soybean landraces will serve as a valuable basis for further application in genetic studies and the breeding of climate-resilient soybeans characterized by improved root traits.

Phosphine gas in the dark induces severe phytotoxicity in Arabidopsis thaliana by increasing a hypoxia stress response and disrupting the energy metabolism: Transcriptomic approaches.

Phosphine (PH3) is an ideal fumigant alternative on methyl bromide (MB) as MB has been classified as an ozone-depleting substance. However, several challenges limit its efficient use in crop production, including the emergence of PH3-resistant insect pests and the incidence of phytotoxic effects on nursery plants. Therefore, this study aims to elucidate the mechanism underlying PH3 phytotoxicity in plants using transcriptomic techniques. Fumigation with 2 g/m3 PH3 induced phytotoxic effects in A. thaliana, as evidenced by a decrease in growth and vegetation indices compared to the control group. Transcriptomic analysis revealed that PH3 fumigation phytotoxicity responses in A. thaliana involve genes related to hypoxia stress and energy metabolism. Additionally, pretreatment with ethylene induced pre-adaptation to hypoxia under light conditions during fumigation effectively suppressed the phytotoxic effects of PH3 in A. thaliana by increasing the expression of hypoxia-adaptive genes. Moreover, the phytotoxicity of PH3 was also confirmed in pumpkin (Cucurbita moschata Duch.), and was dependent on light. Overall, our findings showed that fumigation under light conditions and ethylene pretreatment could be used to minimize PH3-induced phytotoxic effects in plants.

Genome-Wide Identification of Aquaporin Genes in Adzuki Bean (Vigna angularis) and Expression Analysis under Drought Stress.

The adzuki bean Vigna angularis (Wild.) is an important leguminous crop cultivated mainly for food purposes in Asian countries; it represents a source of carbohydrates, digestible proteins, minerals, and vitamins. Aquaporins (AQPs) are crucial membrane proteins involved in the transmembrane diffusion of water and small solutes in all living organisms, including plants. In this study, we used the whole genome sequence of the adzuki bean for in silico analysis to comprehensively identify 40 Vigna angularis aquaporin (VaAQP) genes and reveal how these plants react to drought stress. VaAQPs were compared with AQPs from other closely-related leguminous plants, and the results showed that mustard (Brassica rapa) (59), barrel medic (Medicago truncatula) (46), soybean (Glycine max) (66), and common bean (Phaseolus vulgaris L.) (41) had more AQP genes. Phylogenetic analysis revealed that forty VaAQPs belong to five subfamilies, with the VaPIPs (fifteen) subfamily the largest, followed by the VaNIPs (ten), VaTIPs (ten), VaSIPs (three), and VaXIPs (two) subfamilies. Furthermore, all AQP subcellular locations were found at the plasma membrane, and intron-exon analysis revealed a relationship between the intron number and gene expression, duplication, evolution, and diversity. Among the six motifs identified, motifs one, two, five, and six were prevalent in VaTIP, VaNIP, VaPIP, and VaXIP, while motifs one, three, and four were not observed in VaPIP1-3 and VaPIP1-4. Under drought stress, two of the VaAQPs (VaPIP2-1 and VaPIP2-5) showed significantly higher expression in the root tissue while the other two genes (VaPIP1-1 and VaPIP1-7) displayed variable expression in leaf tissue. This finding revealed that the selected VaAQPs might have unique molecular functions linked with the uptake of water under drought stress or in the exertion of osmoregulation to transport particular substrates rather than water to protect plants from drought. This study presents the first thorough investigation of VaAQPs in adzuki beans, and it reveals the transport mechanisms and related physiological processes that may be utilized for the development of drought-tolerant adzuki bean cultivars.

Physicochemical properties and oxidative stability of corn oil in infrared-based and hot air-circulating cookers.

Corn oil was heated using an infrared cooker, an air fryer, and a cooking oven at similar temperatures, and oxidative stability and physicochemical properties including moisture content, temperature change, the profile of headspace volatiles, formaldehyde and acetaldehyde of the heated oils were compared. Corn oil heated using the air fryer showed the lowest degree of oxidation, followed by that heated using the infrared cooker and the cooking oven. However, the content of headspace volatiles in 120 min heated oil using the infrared cooker was higher by 2.57 and 5.37 times than that in oil heated using the cooking oven and the air fryer, respectively. The profiles of formaldehyde and acetaldehyde in oils showed patterns inconsistent with those of headspace volatile and oxidation parameters. Generally, the air fryer-treated oil underwent slow lipid oxidation, whereas oil from the infrared cooker had more volatiles and imparted odor to foods.

From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry.

Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, 'Suziblue' and 'Star', to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf's position and time, whereas 'Star' did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities.

Utilization of Spectral Indices for High-Throughput Phenotyping.

The conventional plant breeding evaluation of large sets of plant phenotypes with precision and speed is very challenging. Thus, consistent, automated, multifaceted, and high-throughput phenotyping (HTP) technologies are becoming increasingly significant as tools to aid conventional breeding programs to develop genetically improved crops. With rapid technological advancement, various vegetation indices (VIs) have been developed. These VI-based imaging approaches, linked with artificial intelligence and a variety of remote sensing applications, provide high-throughput evaluations, particularly in the field of precision agriculture. VIs can be used to analyze and predict different quantitative and qualitative aspects of vegetation. Here, we provide an overview of the various VIs used in agricultural research, focusing on those that are often employed for crop or vegetation evaluation, because that has a linear relationship to crop output, which is frequently utilized in crop chlorophyll, health, moisture, and production predictions. In addition, the following aspects are here described: the importance of VIs in crop research and precision agriculture, their utilization in HTP, recent photogrammetry technology, mapping, and geographic information system software integrated with unmanned aerial vehicles and its key features. Finally, we discuss the challenges and future perspectives of HTP technologies and propose approaches for the development of new tools to assess plants' agronomic traits and data-driven HTP resolutions for precision breeding.