Leaf Samples Research Articles

Identification of Cercospora spp. on corn in North America and baseline flutriafol fungicide sensitivity.

Gray leaf spot (GLS) is an important corn disease reportedly caused by Cercospora zeae-maydis and C. zeina. Recently, flutriafol, a demethylation inhibitor (azole) fungicide received EPA registration as Xyway® LFR®, a product that is applied at planting for management of fungal diseases in corn, including suppression of GLS. In this study, 448 Cercospora spp. isolates were collected in 2020 and 2021 from symptomatic corn leaf samples submitted from the United States and Ontario, Canada. The Cercospora spp. were identified using multi-locus genotyping of the internal transcribe spacer (ITS), elongation factor 1-α (EF1), calmodulin (CAL), histone H3 (HIS), and actin (ACT) gene. Based on the multi-locus phylogenetic analyses, six species were identified; C. cf. flagellaris (n = 77), C. kikuchii (n = 4), C. zeae-maydis (n = 361), Cercospora sp. M (n = 2), Cercospora sp. Q (n = 1), and Cercospora sp. T (n = 3). In subsequent pathogenicity tests using selected isolates from each of these species, only C. zeae-maydis resulted in symptoms on corn with no disease symptoms observed after inoculation with C. cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. Q, and Cercospora sp. T. While disease symptoms were observed on soybean following inoculation with C. cf. flagellaris, C. kikuchii, and Cercospora sp. Q, but not the other three species. Fungicide sensitivity of Cercospora spp. to flutriafol was assessed using a subset of 340 isolates. The minimum inhibitory concentration (MIC) to inhibit the growth of Cercospora spp. completely was determined based on growth of each species on flutriafol-amended clarified V8 agar at nine concentrations. The EC50 was also calculated from the same trial by measuring relative growth as compared to the non-amended control. Cercospora zeae-maydis was sensitive to flutriafol with mean MIC values of 2.5 µg/mL and EC50 values ranging from 0.016 to 1.020 µg/mL with a mean of 0.346 µg/mL. Cercospora cf. flagellaris, C. kikuchii, Cercospora sp. M, Cercospora sp. Q, and Cercospora sp. T had mean EC50 values of 1.25 µg/mL, 7.14 µg/mL, 2.48 µg/mL, 1.81 µg/mL, and 2.24 µg/mL respectively. These findings will assist in monitoring the sensitivity to the flutriafol fungicide in Cercospora spp. populations.

Molecular analysis of St. Augustinegrass cultivar mixtures composition over time and latitude

AbstractSt. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is commonly planted in residential and commercial landscapes as a cultivar monoculture predisposing this lawn to pest invasion and high‐maintenance inputs. Researchers have suggested that increasing genetic diversity by growing cultivars in mixtures may increase turfgrass stress resilience. However, the stability and uniformity of those mixtures has not been studied. The present study was carried out to evaluate the stability of St. Augustinegrass cultivars mixtures over time and across three latitudes. The study was conducted in Citra and Fort Lauderdale, FL, and Jackson Springs, NC. Simple‐sequence repeats markers were used to genotype leaf samples of St. Augustinegrass cultivars planted in two‐ and four‐cultivar mixtures. Leaf samples were collected 1 and 3 years after establishment. In all locations, cultivar richness and evenness declined over time. Similarly, the relative abundance of the least persistent cultivars decreased approximately 50%–100% depending on cultivar and location. Differences in growth patterns among cultivars resulted in cultivar displacement and the predominance of a single cultivar. Cultivars that covered the ground faster or formed dense canopies early after establishment were dominant at the end of the study. Locally developed cultivars tended to be more dominant in their original latitude. The use of cultivar mixtures may help the identification of vigorous, competitive, and stress tolerant cultivars in turfgrass breeding programs. However, their commercial use remains challenging as if the patterns observed here for 3 years are representative of a continuous trend, and they do not persist over time.

Extractable soil silicon in relation to sugarcane yield on mineral soil

Florida sugarcane production is mostly on organic soils, but the cultivation area on mineral soils is also expanding. Silicon (Si) is beneficial for sugarcane growth and development on weathered soil. However, the low solubility and availability of soluble Si is an issue in Florida’s mineral soils. This study aimed to assess soil Si extraction methods based on sugarcane yield response to calcium silicate application. It also examined the relationship between sugarcane yield with extracted plant-available soil Si, alongside plant Si concentrations. The experiment followed a randomized complete block design involving 2 fields, with 24 plots each, and 6 replications. Four rates of calcium silicate (0 control, 2.24, 4.48, and 6.67 Mg ha−1) were applied before planting sugarcane. Soil samples were collected prior to planting and after each harvest. Soil Si was extracted using 0.5 M acetic acid, 0.7 N NH4OAc, Mehlich 3, and 0.01 M CaCl2 extractants. Leaf samples were collected over a three-year sugarcane life cycle (from 2019 to 2022) to evaluate the relationship between soil Si and leaf Si concentrations. The relationships between parameters were analyzed using linear and nonlinear regression models. Results indicated that higher Si application rates increased Si concentrations in sugarcane leaves in both fields. However, only one field showed a yield response to Si, likely due to high pre-plant soil Si in the other field. The best extractant should correlate strongly with either yield or leaf Si content, but no single extractant showed a strong correlation with either, making it infeasible to identify the best extractant.

Genetic Diversity and Relationship of Native Phalaenopsis Orchids: A Case Study of Indonesian Archipelago

The native Phalaenopsis is valuable germplasm for future orchid breeding programs and for its conservation because it provides many beneficial traits or genes. This study aimed to determine and analyze the molecular diversity and phylogeny of Indonesian native Phalaenopsis by a DNA barcoding (matK) marker. A total of 19 samples of Phalaenopsis orchids were used in this study. All leaf samples of orchid were extracted and purified using a commercial DNA isolation kit from Geneaid Biotech Ltd., Taiwan (GP100). The DNAs were then amplified by specific matK primers: Forward (5’-CGTACAGTACTTTTGTGTTTACGAG-3’) and Reverse (5’-ACCCAGTCCATCTGGAAATCTTGGTTC-3’). The DNA targets or products (matK) were purified and sequenced by the Sanger-bidirectional method at 1st Base Ltd., Malaysia. Before further analysis, the matK sequences of Phalaenopsis were edited, reconstructed, and aligned with the assistance of Clustal W in the MEGA 11 software. Its genetic diversity was determined using the nucleotide diversity index (π%), and the phylogenetic analysis was performed using the maximum likelihood (ML) method with a statistical bootstrap. The phylogenetic relationship was also assessed using principal component analysis (PCA). Based on this marker, the native Phalaenopsis has a high genetic diversity (π% = 1.70). In addition, the phylogenetic analysis revealed that this germplasm was separated into seven clades, where P. pantherina has the closest relation to P. cornu-cervi and P. gigantea. Conversely, the highest genetic distance was to P. amabilis from South Kalimantan and to P. celebensis from Sulawesi, at a coefficient divergence of 0.084. Our findings provide an essential foundation for supporting future orchid breeding practices, including conservation, on local and global scales.

First Report of Beet Western Yellows Virus Infecting Vasconcellea x heilbornii (Caricaceae) in Ecuador.

Vasconcellea x heilbornii, known as babaco, is a hybrid native to Ecuador grown in small orchards in sub-tropical highland regions. Over the last decade, several viruses have been identified in babaco using high-throughput sequencing (HTS) (Cornejo-Franco et al. 2020, (Reyes-Proaño et al. 2023). In 2021, total RNA from a babaco plant showing distinctive leaf yellowing was extracted using the PureLink RNA Mini Kit (Thermo Fischer Scientific, USA) and subjected to HTS on an Illumina NovaSeq6000 system as 150 paired-end reads (Macrogen Inc., South Korea). Library construction was done using the TruSeq Stranded Total RNA Sample kit with Plant Ribo-Zero, as described (Villamor et al. 2022). Reads were processed using BBDuk and de novo assembled using SPAdes 3.15. both implemented in Geneious 2022. Contig analysis was done by BLASTx using the NCBI viral sequence database (as of November 2022). HTS generated 54 million reads, of which 12% assembled into contigs corresponding to genomes of previously reported babaco viruses including babaco virus Q (BabVQ), babaco nucleorhabdovirus 1 (BabRV1) and babaco ilarvirus 1 (BabIV1). Interestingly, 144 reads (0.0003%) assembled into seven contigs ranging from 100 to 480 nucleotides (nt) in length. These contigs showed homology, with 97% amino acid (aa) identity (100% query coverage), to regions of the RNA-dependent-RNA-polymerase (RdRp) of beet western yellows virus (BWYV, Acc. No. NC_004756), a member of the Polerovirus genus. To confirm the occurrence of BWYV in babaco, double-stranded RNA (dsRNA) was extracted from 15 g of leaf tissue from the original sample as described (Dodds et al. 1984) and used as template for reverse-transcription (RT)-PCR using overlapping primers designed to span all short contigs. RT-PCR amplified fragments were cloned into a pGEM®T-easy vector (Promega, USA) and sequenced by the Sanger method (Macrogen Inc., South Korea). The sequences were assembled into a single 2.7 kbp BWYV genome fragment comprising the complete protein 1 (P1) and partial RdRp gene (GenBank Acc. No. PP480670). Sequence alignments between the partially sequenced genome of the babaco isolate and its corresponding fragment from the closest BWYV isolate (NC_004756) revealed 94% and 97% identities at the nt and aa levels, respectively. To assess the prevalence of BWYV in babaco, 30 leaf samples showing yellowing symptoms from Pichincha (n=15) and Azuay (n=15) provinces were tested by RT-PCR using total RNA. Total RNA extraction and reverse transcription were done using the methodology described by Halgren et al. (2007). For RT-PCR, the primer set BWYV_Bab_F: 5'-CAGTGTCCTCCAAGTGCAACAT-3' / BWYV_Bab_R: 5'GGTTCCTTCCCAGTTTGGTGGT-3', which amplifies a 235 nt-long P1 region, was used. Three RT-PCR products from each positive sample were purified using the GeneJET PCR clean-up kit (Thermo Scientific, USA) and sequenced. BWYV was confirmed in 9 out of 15 samples (60%) from Pichincha, and in 10 out of 15 samples (64%) from Azuay. Samples were also tested for additional babaco viruses as described (Reyes-Proaño et al. 2023). All BWYV-infected plants turned out positive for papaya ringspot virus (PRSV), babaco mosaic virus (BabMV), BabVQ, and BabIV1. Hence, the impact of BWYV infection on babaco plants in single and mixed infections warrants further investigation. To the best of our knowledge, this is the first report of BWYV in a crop in Ecuador, and the first time it has been found in a Caricaceae species.

First report of potato virus H infecting tomato (Solanum lycopersicum) in China.

Potato virus H (PVH), belonging to the genus Carlavirus in the family Betaflexiviridae, was initially discovered in potato plants in Inner Mongolia, China (Li et al., 2013). Subsequently, it was documented to infect pepino, a perennial shrub of the Solanaceae family like potatoes (Abouelnasr et al., 2014). Tomato (Solanum lycopersicum L.), a major global crop, faces threats from various plant viruses. In an open field survey in Yunnan, China during July 2023, tomatoes (cultivar: Liangsi) showed typical virus symptoms: leaf yellowing, curling, mottling, and fruit with abnormal shape and color. Eleven symptomatic tomato samples were collected for high-throughput sequencing to identify the potential pathogen. RNA sequencing libraries were prepared using the TruSeq RNA sample prep kit (Illumina, San Diego, CA, USA), followed by RNA-seq sequencing on an Illumina HiSeq4000 platform (LC Sciences, USA). Approximately 77,928,560 paired-end reads (150-bp each) were generated. After quality control, 75,808,296 reads were retained and subjected to de novo assembly using Trinity (version 2.8.5). The assembled contigs, ranging from 198 nt to 15865 nt, were used as queries to search against the NCBI non-redundant protein sequence database (NR) or nucleotide sequence database (NT) to detect the potential pathogens using BLASTx and BLASTn program with a cutoff e-value of 10-5. As a consequence, certain contigs were assigned to 3 plant viruses, including PVH (the highest RdRp blastx identity to UAD82396.1: 97.8%), Capsicum chlorosis virus (CaCV, the highest RdRp blastx identity to APQ31267.1: 98.4%), and southern tomato virus (STV, the highest CP-RdRp fusion protein blastx identity to QOW17541.1: 99.74%). The presence of the identified 3 viruses was subsequently screened in the 11 tomato samples originally collected from the corresponding field. Notably, the specific detection primers for the PVH genome was designed from the newly assembled PVH genome (Forward primer: 5'- ATAGTTGTGCACTGTGTGCCTG-3'; Reverse primer: 5'-GCTTAAGGTTCTTAGCGTATTC-3'), targeting ~1.1kb. Consequently, PVH was detected in 3 out of 11 samples: 2 leaf samples and 1 fruit sample, with one leaf sample showing a single infection. The complete genome sequence of PVH in tomatoes (PVH-tomato) was successfully obtained by assembling nine overlapping regions spanning the entire PVH-tomato genome, following the RT-PCR and the 5' RACE and 3' RACE approaches, and deposited in NCBI nucleotide database with accession number OR397130.1Phylogenetic analysis based on the full genome sequences of PVH-tomato and other publicly available PVH isolates revealed that PVH-tomato was closely related to a PVH isolate found in potatoes in Yunnan (blastn similarity: 97.76%) (Fig. S1A). To test PVH-tomato infectivity and pathogenicity, four healthy Nicotiana benthamiana and four healthy tomato plants were mechanically inoculated with PVH-infected leaf sap; controls used sap from healthy plants. Three weeks post-inoculation, all N. benthamiana (4/4) and three tomato plants (3/4) were PVH-positive by RT-PCR. Symptoms were milder in N. benthamiana, and only two tomato plants (2/4) showed leaf curling. No PVH was detected in control samples (Figure S1B, S1C). Sanger sequencing confirmed the amplicons' expected length of 1093 bp. Previously, PVH was documented only in potato and pepino. This is the first report of tomatoes as natural PVH hosts and PVH infecting N. benthamiana under lab conditions.

Tissue-specific accumulation of PIP aquaporins of a particular heteromeric composition is part of the maize response to mycorrhiza and drought

The systemic coordination of accumulation of plasma membrane aquaporins (PIP) was investigated in this study in relation to mycorrhized maize response to a rapid development of severe drought followed by rewatering. In non-mycorrhizal roots, drought led to a drop in PIP abundance, followed by a transient increase under rewatering, whereas leaves showed an opposite pattern. In contrast, mycorrhiza contributed to maintenance of high and stable levels of PIPs in both plant organs after an initial increase, prolonged over the irrigation period. Isoelectric focusing electrophoresis resolved up to 13 aquaporin complexes with highly reproducible pl positions across leaf and root samples, symbiotic and non-symbiotic, stressed or not. Mass spectrometry recognized in leaves and roots a different ratio of PIP1 and PIP2 subunits within 2D spots that accumulated the most. Regardless of symbiotic status, drought regulation of aquaporins in roots was manifested as the prevalence of complexes that comprise almost exclusively PIP2 monomers. In contrast, the leaf response involved enrichment in PIP1s. PIP1s are thought to enhance water transport, facilitate CO2 diffusion but also affect stomatal movements. These features, together with elevated aquaporin levels, might explain a stress tolerance mechanism observed in mycorrhizal plants, resulting in faster recovery of stomatal water conductance and CO2 assimilation rate after drought.

The Barren Berry phenotype: untangling cranberry (Vaccinium macrocarpon Ait.) genetic contamination in central Wisconsin and beyond

Wisconsin is the world’s leading producer of cranberries (Vaccinium macrocarpon Ait.; 2n = 2x = 24). The state produces over twenty-thousand acres that contribute to more than 50% of the global total production, with more than one billion dollars in value. Cranberry growers in the “central sands” of Wisconsin have been experiencing yield decline due to vegetative unproductive genotypes, popularly known as “Barren Berry’’, which consistently remain vegetative and produce no fruit. The purpose of this study was to compare visual inspection in the field to DNA fingerprinting for the early detection of unproductive/barren genotypes. Additionally, the study served as a survey of unproductive genotypes in central Wisconsin, the largest growing region in the world. A total of 839 cranberry leaf samples, from 14 growers representing plantings to four cultivated varieties, were submitted for DNA testing of two visually determined phenotypes: unproductive or barren (n = 646; those that produced little to no fruit), versus productive or fruiting (n = 193). We conducted genetic fingerprinting on the leaf tissue using nine microsatellite markers previously shown to differentiate cranberry genotypes. This study identified a barren berry genotype unique to central Wisconsin, which we denoted “Barren Berry 1”. This genotype accounted for 43% of samples submitted as the barren berry phenotype. Genetic fingerprinting revealed sixty-five different genotypes in beds which were thought to be monocultures of just four cultivated genotypes. Early detection of genetic contamination through visual inspection, genetic testing, and responsible propagation can drastically aid in the management and longevity of cranberry beds, and in turn save time and money to the growers.

Modulation of Antioxidant Properties in Leaves of Betel Vine (Piper betel L.) Influenced by the Fungicide Blitox

The experiment was conducted using a Randomized Block Design with three replications at the Plant Virus Research Station, BCKV, Kalyani, in Boroj. On betel vines, Blitox was sprayed at both double the recommended field dose (dRFD) and the recommended field dose (RFD) (50 WP/ha @ 15gm ai/6 lit). The vines were sprayed five more times at 15-day intervals beginning when they were 11.08.15 days old. Before every spray, leaf samples were taken and subjected to a number of criteria for analysis. Based on statistical analysis, the anti-oxidative characteristics improved most significantly when Blitox was administered at twice the recommended field dose (dRFD) (Blitox 50WP/ha @ 30gm ai/6 lit). Higher levels of free and total phenols, together with enhanced activity of enzymes such polyphenol peroxidase (PPO), superoxide dismutase (SOD), and peroxidase (POD), were indicators of this. Furthermore, testing for ferric reducing antioxidant power (FRAP) and diphenyl picryl hydrazyl (DPPH) revealed increased activity levels in the dRFD therapy in comparison to the RFD and control groups. Overall, these results imply that the larger Blitox dosage strengthens the antioxidant characteristics of betel vine leaves, hence enhancing their health and resistance to fungus-related infections.

Multivariate Analysis and Optimization Scheme of the Relationship between Leaf Nutrients and Fruit Quality in ‘Bingtang’ Sweet Orange Orchards

Citrus trees require a balanced and adequate supply of macronutrient and micronutrient elements for high yield and fruit quality. Foliar nutrient analysis has been widely used in fruit-tree nutrient diagnosis and fertilization calculation. However, there is no information on ways to produce optimal fruit quality in sweet oranges. In the present study, fruit and leaf samples were collected from 120 ‘Bingtang’ sweet orange [Citrus sinensis (L.) Osbeck] orchards during four consecutive years (2019–2022). Parameters of leaf nutrition and fruit quality were analyzed based on these samples. Diagnostic results based on leaf classification standards indicated that the most deficient elements were Ca, Mg, and B, followed by N and Zn. Fruit quality, determined by single fruit weight (SFW), fruit shape index (FSI), total soluble solids (TSS), titratable acidity (TA), vitamin C (Vc), and maturation index (MI = TSS/TA) during fruit maturation, exhibited inconsistent responses to leaf mineral nutrition concentrations. The leaf-nutrient optimum values for high quality of the ‘Bingtang’ sweet orange fruit were ranges of 2.41–4.92% N, 0.10–0.28% P, 1.30–2.11% K, 2.99% Ca, 0.26–0.41% Mg, 340–640 mg/kg S, 89.65–127.46 mg/kg Fe, 13.48–51.93 mg/kg Mn, 2.60–13.84 mg/kg Cu, 15.59–51.48 mg/kg Zn, and 53.95 mg/kg for B. These results suggest the leaf-nutrient optimum values for diagnosis can be used not only to identify the nutrient constraints but also to provide guidance for the establishment of fertilization regimes in citrus cultivation.

Transcriptomic analysis unveils alterations in the genetic expression profile of tree peony (Paeonia suffruticosa Andrews) infected by Alternaria alternata

BackgroundBlack spot disease in tree peony caused by the fungal necrotroph A. alternata, is a primary limiting factor in the production of the tree peony. The intricate molecular mechanisms underlying the tree peony resistance to A. alternata have not been thoroughly investigated.ResultsThe present study utilized high-throughput RNA sequencing (RNA-seq) technology to conduct global expression profiling, revealing an intricate network of genes implicated in the interaction between tree peony and A. alternata. RNA-Seq libraries were constructed from leaf samples and high-throughput sequenced using the BGISEQ-500 sequencing platform. Six distinct libraries were characterized. M1, M2 and M3 were derived from leaves that had undergone mock inoculation, while I1, I2 and I3 originated from leaves that had been inoculated with the pathogen. A range of 10.22–11.80 gigabases (Gb) of clean bases were generated, comprising 68,131,232 − 78,633,602 clean bases and 56,677 − 68,996 Unigenes. A grand total of 99,721 Unigenes were acquired, boasting a mean length of 1,266 base pairs. All these 99,721 Unigenes were annotated in various databases, including NR (Non-Redundant, 61.99%), NT (Nucleotide, 45.50%), SwissProt (46.32%), KEGG (Kyoto Encyclopedia of Genes and Genomes, 49.33%), KOG (clusters of euKaryotic Orthologous Groups, 50.18%), Pfam (Protein family, 47.16%), and GO (Gene Ontology, 34.86%). In total, 66,641 (66.83%) Unigenes had matches in at least one database. By conducting a comparative transcriptome analysis of the mock- and A. alternata-infected sample libraries, we found differentially expressed genes (DEGs) that are related to phytohormone signalling, pathogen recognition, active oxygen generation, and circadian rhythm regulation. Furthermore, multiple different kinds of transcription factors were identified. The expression levels of 10 selected genes were validated employing qRT-PCR (quantitative real-time PCR) to confirm RNA-Seq data.ConclusionsA multitude of transcriptome sequences have been generated, thus offering a valuable genetic repository for further scholarly exploration on the immune mechanisms underlying the tree peony infected by A. alternata. While the expression of most DEGs increased, a few DEGs showed decreased expression.

Flexibility of parental-like or maternal-like gene expression under diverse environments contributes to combined drought avoidance and drought tolerance in a water-savinganddrought-resistance rice hybrid.

The hybrid rice variety (Hanyou73) exhibits the maternal-like (HH7A) gene expression in roots and parental-like (HH3) gene expression in leaves to obtain both advantages of drought avoidance and drought tolerance from its two parents. Rice is one of the most important crops in the world. Rice production consumes lots of water and significantly suffers from the water deficiency and drought stress. The water-saving and drought-resistance rice (WDR) confers good drought resistance and performs well in the water-saving cultivation. A hybrid WDR variety Hanyou73 (HY73) exhibited superior drought resistance compared with its parents Hanhui3 (HH3) and Huhan7A (HH7A). Studies on drought resistance related traits revealed that HY73 performed like HH3 and HH7A on drought tolerance and drought avoidance, respectively. Transcriptomes were analyzed for samples with various phytohormone treatments and abiotic stresses, in which HY73 was closer to HH3 in leaf samples while HH7A in root samples. HY73 and its parents differed largely in DEGs and GO analysis for DEGs suggested the different pathways of drought response in HH3 and HH7A. Parent-like expression analysis revealed that the higher-parent-like expression pattern was prevailing in HY73. In addition, patterns of the parent-like expression significantly transformed between abiotic-stressed/phytohormone-treated and control samples, which might help HY73 to adapt to different environments. WGCNA analysis for those parent-like expression genes revealed some drought resistant genes that should contribute to the superior drought resistance of HY73. Genetic variation on the promotor sequence was confirmed as the reason for the flexible parent-like gene expression in HY73. Our study uncovered the important roles of complementation of beneficial traits from parents and flexible gene expressions in drought resistance of HY73, which could facilitate the development of new WDR varieties.

Comparative Metabolomic Responses of Three Rhododendron Cultivars to the Azalea Lace Bug (Stephanitis pyrioides).

Rhododendron, with its high ornamental value and ecological benefits, is severely impacted by the azalea lace bug (Stephanitis pyrioides), one of its primary pests. This study utilized three Rhododendron cultivars, 'Zihe', 'Yanzhimi', and 'Taile', to conduct a non-targeted metabolomic analysis of leaf samples before and after azalea lace bug stress using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GCMS) and liquid chromatography-mass spectrometry (LCMS). A total of 81 volatile metabolites across 11 categories and 448 nonvolatile metabolites across 55 categories were detected. Significant differences in metabolic profiles were observed among the different cultivars after pest stress. A total of 47 volatile compounds and 49 nonvolatile metabolites were upregulated in the most susceptible cultivar 'Zihe', including terpenes, alcohols, nucleotides, amino acids, and carbohydrates, which are involved in energy production and secondary metabolism. Conversely, 'Yanzhimi' showed a downtrend in both the differential volatiles and metabolites related to purine metabolism and zeatin biosynthesis under pest stress. The resistant cultivar 'Taile' exhibited moderate changes, with 17 volatile compounds and 17 nonvolatile compounds being upregulated and enriched in the biosynthesis of amino acids, pentose, glucuronate interconversions, carbon metabolism, etc. The phenylalanine metabolic pathway played an important role in the pest resistance of different susceptible cultivars, and relevant metabolites such as phenylethyl alcohol, methyl salicylate, and apigenin may be involved in the plant's resistance response. The results of this study provide a new perspective on the metabolomics of Rhododendron-insect interactions and offer references for the development of pest control strategies.

Chemometric classification of Vietnamese green tea (Camellia sinensis) varieties and origins using elemental profiling and FTIR spectroscopy

SummaryThe objective of this study was to employ multi‐elemental analysis and chemometric multivariate data analysis for identifying the geographical origin of Camellia sinensis cultivated in Vietnam's northeastern region. Ninety‐two tea leaf samples encompassing four distinct varieties were sourced from Bac Can and Thai Nguyen provinces. These samples underwent analysis through Fourier transform infrared (FTIR) spectroscopy and chemometrics, while elemental quantification was achieved via inductively coupled plasma mass spectrometry (ICP‐MS), utilising mixed standards for 26 elements. The FTIR spectra exhibited characteristic peaks, denoting the functional groups of the potential compounds present. ICP/MS analysis identified the presence of 14 elements in the tea samples, revealing significant variations in content across the four varieties. principal component analysis (PCA) of the FTIR data illustrated that the initial two principal components accounted for 91.26% of the total variance, effectively segregating the four green tea varieties into distinct clusters. Conversely, PCA of the ICP‐MS spectra also distinguished the four varieties, albeit Trung Du and Hybrid F1 exhibited a proximate distribution. This closeness may be incidental and not indicative of correlation, considering the limited variable set. Our findings ascertain that ICP/MS and FTIR, augmented by chemometric software, serve as efficacious tools for ascertaining the geographical origins of tea.

Isolation and Characterization of Pathogen causing Northern Corn Leaf Blight of Maize in Ri-Bhoi, Meghalaya, India

The present study was carried out to identify and characterize the Exserohilum turcicum causing northern corn leaf blight of maize based on the cultural, morphological and molecular characteristics. Diseased leaf samples from maize fields exhibiting typical cigar shaped symptoms of northern corn leaf blight were collected from the research fields of CPGS-AS (Umiam), College of Agriculture (Kyrdemkulai) and ICAR-RC for NEH region (Umiam) located in Ri-Bhoi district, Meghalaya. Through cultural, morphological, molecular characterization the fungal isolate was identified as Exserohilum sp. Phylogenetic analysis of ITS rDNA gene sequence indicates as Exserohilum turcicum is associated with the disease northern corn leaf blight of maize. The findings underscore the importance of pathogen Exserohilum turcicum causing northern corn leaf blight impact on the maize crop, highlighting potential threat to its production.

A new dataset of leaf optical traits to include biophysical parameters in addition to spectral and biochemical assessment

To enable future improvement on current leaf optical property models, more data incorporating a larger range of measured properties is needed. To this end, a dataset was collected to associate spectral measurements (ultraviolet, visible, and near infrared) with biochemical and biophysical properties of leaves. The leaves represented in this dataset were selected to provide a more comprehensive representation of both tree and agricultural species as well as leaves with a wide variety of color (pigment) expression, surface characteristics, and stages in a leaf lifecycle. Extensive data were collected for each of the 290 leaf samples studied in this project including multiple spectral measurement orientations and ranges, biochemical assessment, and biophysical assessment of that has not previously been a focus in other leaf datasets. The methods and results associated with this dataset are described in this work.

Allelopathic potential of invasive alien plant species, Xanthium strumarium L., water and methanol extracts on germination and seedling growth of Guizotia abyssinica (L.f.) Cass., and Linum usitatissimum L.

The objective of this study was to investigate the allelopathic impact of Xanthium strumarium on the seedling growth and germination of Guizotia abyssinica and Linum usitatissimum. Plant specimens and samples of Xanthium strumarium were collected from the Minjar-Shenkora district in Ethiopia. In the laboratory, a series of dilutions of extracts from the leaves and roots of Xanthium strumarium were prepared using distilled water and methanol (99.85%) as solvents. Twenty-five grams of root and leaf samples were soaked separately in 250 mL of the specified solvent to create the stock solution. The experiment was carried out using Petri dishes in a completely random manner, with three replications repeated twice. Various concentrations of the extracts (25, 50, 75, and 100%) were applied as treatments, while distilled water served as the control. Each petri dish contained 25 seeds of each test crop and 5 mL of the corresponding extract. The number of Linum usitatissimum and Guizotia abyssinica seeds germinating was recorded every 24 hours until 12 and 14 days, respectively. Both descriptive and inferential analyses were conducted. When Guizotia abyssinica and Linum usitatissimum seeds were treated with 100% concentrations of water extract from leaf samples, germination percentages were inhibited by 72 and 77.4%, respectively. In methanol extracts, the entire inhibition of germination was observed in both test plant species at ≥ 50% and ≥ 75% concentrations of leaf and root samples, respectively. Therefore, the inhibitory effect of water and methanol extracts showed a concentration-dependent pattern, with increasing concentrations resulting in greater inhibition. The inhibitory effect of leaf extracts was more pronounced compared to root extracts, suggesting the presence of herbicidal activities. Further phytochemical and molecular studies are recommended to identify the active compounds in Xanthium strumarium. Additionally, utilizing isolated allelopathic substances as a means of controlling invasive alien species is suggested.

Plant-Leaf Recognition Based on Sample Standardization and Transfer Learning

In recent years, deep-learning methods have significantly improved the classification results in the field of plant-leaf recognition. However, limited by the model input, the original image needs to be compressed to a certain size before it can be input into the convolutional neural network. This results in great changes in the shape and texture information of some samples, thus affecting the classification accuracy of the model to a certain extent. Therefore, a minimum enclosing quadrate (MEQ) method is proposed to standardize the sample datasets. First, the minimum enclosing rectangle (MER) of the leaf is obtained in the original image, and the target area is clipped. Then, the minimum enclosing quadrate of the leaf is obtained by extending the short side of the rectangle. Finally, the sample is compressed to fit the input requirements of the model. In addition, in order to further improve the classification accuracy of plant-leaf recognition, an EC-ResNet50 model based on transfer-learning strategy is proposed and further combined with the MEQ method. The Swedish leaf, Flavia leaf, and MEW2012 leaf datasets are used to test the performance of the proposed methods, respectively. The experimental results show that using the MEQ method to standardize datasets can significantly improve the classification accuracy of neural networks. The Grad-CAM visual analysis reveals that the convolutional neural network exhibits a higher degree of attention towards the leaf surface features and utilizes more comprehensive feature regions during recognition of the leaf samples processed by MEQ method. In addition, the proposed MEQ + EC-ResNet50 method also achieved the best classification results among all the compared methods. This experiment provides a widely applicable sample standardization method for leaf recognition research, which can avoid the problem of sample deformation caused by compression processing and reduce the interference of redundant information in the image to the classification results to a certain degree.

Identification of pancreatin inhibitors from Thai medicinal Piper plants for antidiabetic and anti-obesity activities using high-performance thin-layer chromatography-bioautographic assay

Exploring the potential of natural products against diabetes and obesity is in demand nowadays. Pancreatic α-amylase and pancreatic lipase are the drug targets to minimize the absorption of glucose from starch and fatty acids from lipids, respectively. In this study, five Piper species, namely P. sarmentosum (Ps), P. wallichii (Pw), P. retrofractum (Pr), P. nigrum (Pn), and P. betle (Pb), which are commonly used as food ingredients and traditional medicines, were evaluated for their inhibitory activities against pancreatin using the microtiter plate method. Additionally, pancreatin inhibitors were identified through a cost-effective high-performance thin-layer chromatography (HPTLC)-bioautography developed using red starch and p-nitrophenyl palmitate, corresponding to anti-amylase and -lipase activities, respectively. Of the 15 samples tested, leaf samples from Pb, which had the highest total phenolic and total flavonoid contents, exhibited remarkable inhibitory activity against pancreatin, with a relative amylase inhibitory capacity (RAIC) ranging between 4.260 × 10−5 and 4.861 × 10−5 and a reciprocal half-maximal inhibitory concentration (1/IC50, PTL) of 0.390–0.510 (mg/mL)−1. Additionally, Ps samples demonstrated the second-ranked anti-pancreatin activity. Principal component analysis indicated that total phenolic content contributed to the anti-pancreatin activities of Pb samples. The anti-pancreatin bands were isolated and identified as caffeic acid, myricetin, genistein, piperine, and eugenol. Myricetin, in the roots of Ps samples, showed notable anti-pancreatin activity, which was consistent with results from the in silico prediction toward pancreatic α-amylase and pancreatic lipase. Caffeic acid and eugenol were present in Pb samples. In conclusion, the developed cost-effective pancreatin HPTLC-bioautography efficiently identified amylase and lipase inhibitors from Piper herbs, which supported the use of these plants for antidiabetes and anti-obesity.

Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy

The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients.