Major Cultivation Areas Research Articles

벼, 팥, 들깨, 땅콩 작물 재배 농가 조사를 위한 표본설계

In this paper, as part of the Rural Development Administration's “Statistical Research on Cultivation Status by Crop Breed for Development of Consumer-Customized Breed Support Technology,” which is being carried out from 2022, we focused on the scientific estimation of statistics related to the cultivation area and households engaged in cultivating four food crops including rice, red beans, perilla seeds, and peanuts. In the 2023 survey, we deal with four major crops among the total of 15 subjects, which are considered key food crops. By the 2022 agricultural management database (DB) as the population, we selected major cultivation areas based on the scale of cultivation households for each crop. For each crop, we distinguished between the entire stratum and the sample stratum concerning the cultivation area. The sample size, approximately 1,500 households, was allocated using proportional allocation, Neyman allocation, and, notably, employing a power allocation method that ensured stable expected target error values for each stratum, known as power allocation. Subsequently, for the calculation of crop-specific statistics, we conducted a weight adjustment based on the population of households in the database. The results include estimates for the total and average quantities for each crop and variety.

Correlation analysis of phenolic compounds, antioxidant potential, oxygen radical scavenging capacity, and alkaloid content in ripe and unripe Areca catechu from major cultivation areas in Sri Lanka

This study was conducted to compare the correlation between phenolic compounds, antioxidant potential, and the total alkaloid content in Sri Lankan areca nuts based on the maturity stage and varying conditions in growing areas including, climate, altitude, temperature, and soil conditions. The total polyphenol content (TPC), total flavonoid content (TFC), total tannin content (TTC), and the total alkaloid content (TAC) of ripe areca nuts from selected five major growing areas (Kalutara, Kandy, Kegalle, Kurunegala, and Badulla) ranged from 113.24 ± 0.92 to 224.40 ± 26.50 mg GAE/g, 60.25 ± 7.04 to 180.90 ± 15.71 mg QE/g, 73.11 ± 3.77 to 120.78 ± 2.16 mg TE/g, 4.47 ± 0.31 to 18.27 ± 0.02 mg/g respectively. Whereas, TPC, TFC, TTC, and TAC content of unripe areca nuts ranged between 121.59 ± 6.01 to 349.10 ± 29.70 mg GAE/g, 35.81 ± 4.73 to 88.41 ± 1.79 mg QE/g, 54.89 ± 2.25, 75.33 ± 3.22 mg TE/g, and 27.22 ± 0.19 to 52.72 ± 0.36 mg/g respectively. The IC50 DPPH, IC50 ABTS, IC50 FRAP, EC50 hydroxyl radicals, and EC50 nitric oxide radicals of ripe areca nuts of five major growing areas ranged from 73.86 ± 1.06 to 197.46 ± 8.66 mg GAE/g, 50.52 ± 2.12 to 94.24 ± 2.67 mmol TEAC/ml, 195.26 ± 7.22 to 275.00 ± 7.01 mg TEAC/g, 73.00 ± 14.80 to 98.51 ± 37.80 mg/ml, and 62.99 ± 11.25 to 87.70 ± 1.65 mg/ml respectively. The IC50 DPPH, IC50 ABTS, IC50 FRAP, EC50 hydroxyl radicals, and EC50 nitric oxide radicals of ripe areca nuts ranged from 67.23 ± 0.91 to 77.29 ± 0.18 mg GAE/g, 41.91 ± 3.20 to 55.78 ± 0.00 mmol TEAC/ml, 288.40 ± 25.00 to 386.40 ± 16.90 mg TEAC/g, 112.60 ± 17.60 to 257.88 ± 12.20 mg/ml 102.77 ± 0.77 to 245.10 ± 20.40 mg/ml respectively. TPC, TFC, and TTT of ripe areca nuts strongly correlated with their free radical antioxidant capacities whereas; the alkaloid content of unripe areca nuts correlated negatively with the TPC, TFC, and TTT content. Both ripe and unripe nuts exhibit a weak correlation with hydroxyl radical scavenging assay.

First report of beet western yellows virus in radish in Korea.

Radish (Raphanus sativus L.) is an important root vegetable widely consumed in kimchi in Korea. In October 2021, radish leaves with virus-like symptoms of mosaic and yellowing were collected in three fields around Naju, Korea (Fig. S1). A pooled sample (n = 24) was screened for causal viruses by high-throughput sequencing (HTS), with detection confirmed by reverse transcription (RT) PCR. Total RNA was extracted from symptomatic leaves using the Plant RNA Prep kit (Biocube System, Korea), and a cDNA library was constructed and sequenced on an Illumina NovaSeq 6000 system (Macrogen, Korea). De novo transcriptome assembly yielded 63,708 contigs, which were analyzed against the viral reference genome database in GenBank by BLASTn and BLASTx searches. Two large contigs were clearly of viral origin. BLASTn analysis showed that a 9,842-bp contig (4,481,600 mapped reads, mean read coverage 68,758.6×) had 99% identity (99% coverage) with isolate CCLB of turnip mosaic virus (TuMV) from radish in China (KR153038). A second contig of 5,711 bp (7,185 mapped reads, mean read coverage 189.9×) had 97% identity (99% coverage) with isolate SDJN16 of beet western yellows virus (BWYV) from Capsicum annuum in China (MK307779). To confirm the presence of these viruses, total RNA extracted from 24 leaf samples was subjected to RT-PCR using primers specific for TuMV (N60_5'-ACATTGAAAAGCGTAACCA-3' and C30_5'-TCCCATAAGCGAGAATACTAACGA-3', amplicon 356 bp) and BWYV (95F_5'-CGAATCTTGAACACAGCAGAG-3' and 784R_5'-TGTGGG ATCTTGAAGGATAGG-3', amplicon 690 bp) for virus detection. Of the 24 samples, 22 were positive for TuMV and 7 were co-infected with BWYV. Single infection of BWYV was not detected. Infection with TuMV, the predominant virus in radish in Korea, was previously reported (Choi and Choi, 1992; Chung et al., 2015). To determine the complete genomic sequence of the BWYV isolate (BWYV-NJ22) from radish, RT-PCR was conducted using eight overlapping primer pairs designed according to the alignment of previously reported BWYV sequences (Table S2). Terminal sequences of the viral genome were analyzed by 5' and 3' rapid amplification of cDNA ends (RACE; Thermo Fisher Scientific Corp.). The assembled complete genome sequence of BWYV-NJ22 was 5,694 nt long and was deposited in GenBank (accession no. OQ625515). The Sanger sequences shared 96% nt identity with the HTS-derived sequence. BLASTn analysis showed that BWYV-NJ22 had high nucleotide identity (98%) at the complete genome level with a BWYV isolate (OL449448) from C. annuum in Korea. BWYV (genus Polerovirus, family Solemoviridae), is an aphid-borne virus with a host range that includes > 150 plant species and is one of the most important viruses causing yellowing and stunting of vegetable crops (Brunt et al., 1996; Duffus 1973). In Korea, BWYV was first reported to infect paprika, followed by pepper, motherwort, and figwort (Jeon et al., 2021; Kwon et al., 2016; 2018; Park et al., 2018). During fall and winter 2021, 675 radish plants with virus-like symptoms of mosaic, yellowing, and chlorosis were collected from 129 farms in major cultivation areas in Korea and analyzed by RT-PCR using the BWYV detection primers. The incidence of BWYV in radish plants was 4.7%, and all infections were mixed infections with TuMV. To our knowledge, this is the first report of BWYV infecting radish in Korea. The symptoms of single BWYV infection are unclear, as radish is a new host plant of BWYV in Korea. Further research on the pathogenicity and impact of this virus in radish is therefore needed.

Assessing green total factor productivity and spatial spillover effect in China’s maize industry for sustainable food production: a carbon emissions perspective

Although Enhancing green total factor productivity (GTFP) within the agricultural sector is crucial for fostering sustainable development. In this paper, the GTFP of China’s maize industry is analyzed using the SBM-GML index method, considering data from the primary maize-producing provinces from 2004 to 2020. This analysis incorporates carbon emissions as undesirable outputs. The spatial Durbin model aids in investigating the factors influencing maize GTFP. Our findings reveal a positive trajectory for China’s maize GTFP over the designated period, featuring an average yearly increase of 0.8%. This ascension is primarily attributed to advancements in green maize technology. In the key cultivation regions of the Yellow and Huaihai areas, the Northern region, and the Southwest region, the average annual growth rates were 1.5%, 0.87%, and 0.09%, respectively. Among the direct influences, variables such as regional human capital, the extent of maize cultivation area, financial assistance towards agriculture, and the degree of agricultural mechanization considerably bolster the optimization of maize GTFP. Conversely, urbanization and the prevalence of natural disasters in the agricultural sector pose substantial challenges to enhancing maize GTFP. Furthermore, the spatial spillover effects reveal that natural agricultural disasters in a particular region inadvertently contribute to the improvement of maize GTFP in adjacent regions. Additionally, the regional human capital levels can significantly impede the progress of maize GTFP in neighboring regions. Therefore, to ensure food security, it is imperative to actively advocate for green development within the maize industry to Enhancing green total factor productivity (GTFP) in agriculture is crucial for agriculture to promote sustainable development. In this paper, using data from 2004-2020 from China’s main maize-producing provinces, the SBM-GML index method is used to measure China’s maize GTFP, and the spatial Durbin model is applied to examine the influencing factors and spatial spillover effects of China’s maize GTFP growth. The results of the study revealed a positive trajectory of Chinese maize GTFP over the specified period, with an average annual growth of 0.8%. This enhancement is mainly attributed to the progress of green maize technology. The average annual growth rates were 1.5%, 0.87%, and 0.09% in the major cultivation areas of the Yellow and Huaihai regions, the northern and southwestern regions, respectively. The analysis of influencing factors showed that among the direct influencing factors, variables such as regional human capital, extent of maize cultivation area, financial assistance to agriculture and degree of agricultural mechanisation contributed significantly to the optimization of maize GTFP. Conversely, urbanisation and the prevalence of natural disasters in the agricultural sector pose significant challenges to improving maize GTFP. Furthermore, spatial spillovers reveal that natural agricultural disasters in a given region unintentionally contribute to the improvement of maize GTFP in neighbouring regions. Furthermore, regional human capital levels can significantly hinder progress in maize GTFP in neighbouring regions. Therefore, in order to ensure food security, the greening of maize production must be actively promoted.

Occurrence and Distribution of Major Viruses Infecting Passion Fruit in Guizhou Province, China, and Molecular Characterization of Two Potyviruses.

The planting of passion fruit (Passiflora edulis) in the Guizhou Province has gradually increased, and the area under cultivation ranks third in China. However, the cultivation and production of passion fruit is severely affected by viral diseases. In 2021 and 2022, we investigated the occurrence of multiple viral diseases in major cultivation areas and identified the main viruses and conducted field surveys in different growing areas of passion fruit in the Guizhou Province, China. A total of 308 samples were randomly collected from 10 different passion fruit cultivation areas, and seven viral diseases were identified using electron microscopy, small RNA sequencing, and reverse transcription-polymerase chain reaction (RT-PCR). Among them, the infection rate of Telosma mosaic virus (TeMV) was the highest (50%), followed by East Asian Passiflora virus (EAPV) (19%), and Cucumber mosaic virus (CMV) (15%). The detection rates of the other four viruses were lower: Passiflora latent virus (PLV) (1%), Turnip mosaic virus (TuMV) (0.6%), Passiflora virus Y (PaVY) (0.3%), and Euphorbia leaf curl virus (ELCV) (6%). In addition, high rates of mixed TeMV + CMV + EAPV infections were found in the province. Notably, 79% of EAPV-infected plants were also infected with TeMV. Finally, the molecular characteristics of the two highly detected potyviruses, TeMV and EAPV, were analyzed. To our knowledge, this study is the first systematic survey of viral diseases of passion fruit in the Guizhou Province, China.

Incidence of Virus Diseases in Major Cultivated Areas of Watermelon and Melon in Chungbuk Province

To investigate the incidence status of viruses in major cultivated areas of watermelon and melon in Chungbuk Province, samples were collected from 2020 to 2021 in vinyl greenhouse of Jincheon and Eumseong and examined for virus infection using reverse transcription polymerase chain reaction. Of the six viruses on watermelon that was analyzed in this study, watermelons were infected with cucumber mosaic virus (CMV), watermelon mosaic virus (WMV), cucumber green mottle mosaic virus (CGMMV), and cucurbit aphid-borne yellows virus (CABYV). The incidence rate of CMV was 20.9–35.0%, WMV 0.4–15.8%, CGMMV 1.6–38.5%, and CABYV was 3.5–3.7% from 2020 to 2021. But strangely, there were no incidence of zucchini yellow mosaic virus and cucurbit chlorotic yellows virus (CCYV) during investigation. From this result, we knew the major virus was CGMMV on watermelon in Chungbuk Province. Molecular diagnosis assays of the two melon viruses, showed that melons were infected with CABYV and CCYV from 2020 to 2021. The incidence rate of CABYV was 53.9–92.2% and CCYV was 2.7–20.8%. The incidence of CABYV was high in melon cultivation of Jincheon and Eumseong, Chungbuk. Afterwards, it is necessary to establish a control management strategy for reduce the incidence of CABYV. Furthermore, we must pay attention that of CCYV even if the incidence was low.

보리, 밀, 감자, 고구마, 콩, 옥수수, 이탈리안라이글라스 작물재배 농가 조사를 위한 표본설계

In this paper, sample survey is considered for each crop to develop technologies tailored to the consumer for seven crops, including barley, wheat, potato, sweet potato, bean, corn and Itailan ryegrass to estimate the cultivation area and scale of cultivation for each crop, and to determine the spread and performance of varieties currently being distributed to farms. The purpose of this study is to generate basic data base or crops by estimating the cultivation area and cultivation scale for each crop based on the results of interviews (telephone) surveys by farmhouse and analyzing the dissemination performance of the varieties being distributed to farmhouses. Among the 13 crops surveyed, this paper considers the 2021 farm management DB for 7 crops as the population, selects major cultivation areas according to the climate characteristics of each crop based on the cultivation area for each crop, Stratified according to the cultivation area for each crop by major production area, and about 1,200 farms were divided into a total layer and a sample layer, and the proportional distribution, Neiman distribution, and idempotent distribution were considered. Sample farm households were distributed. Finally, the weight adjustment and estimation process for sample farms were presented.

Crop Identification and Analysis in Typical Cultivated Areas of Inner Mongolia with Single-Phase Sentinel-2 Images

The Hetao Plain and Xing’an League are the major cultivated areas and main grain-producing areas in Inner Mongolia, and their crop planting structure significantly affects the grain output and economic development in Northern China. Timely and accurate identification, extraction, and analysis of typical crops in Xing’an League and Hetao Plain can provide scientific guidance and decision support for crop planting structure research and food security in ecological barrier areas in Northern China. The pixel samples and the neighborhood information were fused to generate a spectral spatial dataset based on single-phase Sentinel-2 images. Skcnn_Tabnet, a typical crop remote sensing classification model, was built at the pixel scale by adding the channel attention mechanism, and the corn, sunflower, and rice in the Hetao Plain were quickly identified and studied. The results of this study suggest that the model exhibits high crop recognition ability, and the overall accuracy of the three crops is 0.9270, which is 0.1121, 0.1004, and 0.0874 higher than the Deeplabv3+, UNet, and RF methods, respectively. This study confirms the feasibility of the deep learning model in the application research of large-scale crop classification and mapping and provides a technical reference for achieving the automatic national crop census.

High-Throughput Sequencing for Deciphering the Virome of Alfalfa (Medicago sativa L.).

Alfalfa (Medicago sativa L.), also known as lucerne, is a major forage crop worldwide. In the United States, it has recently become the third most valuable field crop, with an estimated value of over $9.3 billion. Alfalfa is naturally infected by many different pathogens, including viruses, obligate parasites that reproduce only inside living host cells. Traditionally, viral infections of alfalfa have been considered by breeders, growers, producers and researchers to be diseases of limited importance, although they are widespread in all major cultivation areas. However, over the past few years, due to the rapid development of high-throughput sequencing (HTS), viral metagenomics, bioinformatics tools for interpreting massive amounts of HTS data and the increasing accessibility of public data repositories for transcriptomic discoveries, several emerging viruses of alfalfa with the potential to cause serious yield losses have been described. They include alfalfa leaf curl virus (family Geminiviridae), alfalfa dwarf virus (family Rhabdoviridae), alfalfa enamovirus 1 (family Luteoviridae), alfalfa virus S (family Alphaflexiviridae) and others. These discoveries have called into question the assumed low economic impact of viral diseases in alfalfa and further suggested their possible contribution to the severity of complex infections involving multiple pathogens. In this review, we will focus on viruses of alfalfa recently described in different laboratories on the basis of the above research methodologies.

Evaluation of machine learning models for rice dry biomass estimation and mapping using quad-source optical imagery

ABSTRACT Several machine learning regression models have been advanced for the estimation of crop biophysical parameters with optical satellite imagery. However, literature on the comparative performances of such models is still limited in range and scope, especially under multiple data sources, despite the potential of multi-source imagery to improving crop monitoring in cloudy areas. To fill in this knowledge gap, this study explored the synergistic use of Landsat-8, Sentinel-2A, China’s environment and disaster monitoring and forecasting satellites (HJ-1 A and B) and Gaofen-1 (GF-1) data to evaluate four machine learning regression models that include Random Forest (RF), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), and Gradient Boosting Decision Tree (GBDT), for rice dry biomass estimation and mapping. Taking a major rice cultivation area in southeast China as case study during the 2016 and 2017 growing seasons, a cross-calibrated time series of the Enhanced Vegetation Index (EVI) was obtained from the quad-source optical imagery and on which the aforementioned models were applied, respectively. Results indicate that in the before rice heading scenario, the most accurate dry biomass estimates were obtained by the GBDT model (R2 of 0.82 and RMSE of 191.8 g/m2) followed by the RF model (R2 of 0.79 and RMSE of 197.8 g/m2). After heading, the k-NN model performed best (R2 of 0.43 and RMSE of 452.1 g/m2) followed by the RF model (R2 of 0.42 and RMSE of 464.7 g/m2). Whist the k-NN model performed least in the before heading scenario, SVM performed least in the after heading scenario. These findings may suggest that machine learning regression models based on an ensemble of decision trees (RF and GBDT) are more suitable for the estimation of rice dry biomass, at least with optical satellite imagery. Studies that would extend the evaluation of these machine learning models, to other parameters like leaf area index, and to microwave imagery, are hereby recommended.

Integrated Profiling of Fatty Acids, Sterols and Phenolic Compounds in Tree and Herbaceous Peony Seed Oils: Marker Screening for New Resources of Vegetable Oil.

Tree peonies (Paeonia ostii and Paeonia rockii) are popular ornamental plants. Moreover, these plants have become oil crops in recent years. However, there are limited compositional studies focused on fatty acids. Therefore, this work aims to reveal compositional characteristics, regarding fatty acids, sterols, γ-tocopherol and phenolic compounds, of tree peony seed oils from all major cultivation areas in China, and to compare with herbaceous peony seed oil. For that, an integrative analysis was performed by GC-FID, GC-MS and UHPLC-Q-TOF-MS technologies. The main fatty acid was α-linolenic acid (39.0–48.3%), while β-sitosterol (1802.5–2793.7 mg/kg) and fucosterol (682.2–1225.1 mg/kg) were the dominant phytosterols. Importantly, 34 phenolic compounds, including paeonol and “Paeonia glycosides” (36.62–103.17 μg/g), were characterized in vegetable oils for the first time. Conclusively, this work gives new insights into the phytochemical composition of peony seed oil and reveals the presence of bioactive compounds, including “Paeonia glycosides”.

Bacteriome and Mycobiome in Nicotiana tabacum Fields Affected by Black Shank Disease.

Phytophthora nicotianae is a widespread cause of black shank disease of tobacco plants and causes substantial harvest losses in all major cultivation areas. The oomycete primarily affects plant roots and the stem, where it leads to a progressing decay of the diseased tissues. In this resource announcement, we provide two complementary datasets comprising 16S gene fragment amplicons (bacteriome) and ITS1 region amplicons (mycobiome) that were sequenced on an Illumina-based platform. Soil samples were obtained from disease-affected fields in Guizhou province (China) and include control samples from adhering fields without previous disease incidence. Both datasets were acquired at a high sequencing depth and accompanied by detailed metadata, which facilitate their implementation in comparative studies. The resource announcement provides a basis for disease-specific biomarker detection and correlation studies that include the microbiome.

GC/MS based metabolite profiling of Indonesian specialty coffee from different species and geographical origin.

The consumption of high quality coffee such as specialty Arabica and fine Robusta coffee is increasing steadily in recent years. Development of single origin coffee is an important strategy to maintain coffee quality, grade and high cupping score. Indonesia is a top exporting country for Arabica coffee with high variety of specialty coffees from different origins. Despite its long standing reputation in global coffee market, very few is known about the variability among Indonesian specialty coffees. This study aims to observe metabolite variability among Indonesian coffees from different species and geographical origins by means of non-targeted GC/MS metabolite profiling. Sixty-four compounds were tentatively identified from 16 green and roasted coffee beans from different species and cultivation areas in Indonesia and were subjected to principal component analysis (PCA). Ten Specialty Arabica coffee and five Fine Robusta representing all important high quality coffees of Indonesia were also analyzed independently to further classify Indonesian coffee according to their origin. PCA results of 16 green and roasted coffee beans of different species and cultivation areas showed that samples were separated along PC1 based on different roasting condition (green and roasted) with 52.9% variance and were separated along PC2 based on different species with 19.3% variance. The result from this study showed the clustering of samples based on three major cultivation areas in Indonesia (western, central, eastern part). Metabolites showing higher concentration in Sulawesi, Papua, Flores and Sumatra samples were glycerol, glucuno-1,5-lactone, gluconic acid and sorbitol. A clear distinction in galactitol and galactinol concentration between all samples from eastern part of Indonesia and western and middle part of Indonesia was also observed. Our results showed that each region (western, central and eastern part of Indonesia) has signature compounds that may serve as discriminant markers for coffee authentication. This is the first report on the classification of Indonesian specialty coffee based on their metabolic profiles and can act as a basis for marker identification for routine procedures in industry.

Genetic Diversity of the Pear Scab Fungus Venturia nashicola in Korea

Scab disease caused by Venturia nashicola is of agroeconomic importance in cultivation of Asian pear. However, little is known about the degree of genetic diversity in the populations of this pathogen. In this study, we collected 55 isolates from pear scab lesions in 13 major cultivation areas in Korea and examined the diversity using sequences of internal transcribed spacer (ITS) region, β-tubulin (TUB2), and translation elongation factor-1α (TEF-1α) genes as molecular markers. Despite a low level of overall sequence variation, we found three distinctive subgroups from phylogenetic analysis of combined ITS, TUB2, and TEF-1α sequences. Among the three subgroups, subgroup 1 (60% of isolates collected) was predominant compared to subgroup 2 (23.6%) or subgroup 3 (16.4%) and was distributed throughout Korea. To understand the genetic diversity among the subgroups, RAPD analysis was performed. The isolates yielded highly diverse amplicon patterns and none of the defined subgroups within the dendrogram were supported by bootstrap values greater than 30%. Moreover, there is no significant correlation between the geographical distribution and the subgroups defined by molecular phylogeny. Our data suggest a low level of genetic diversification among the populations of V. nashicola in Korea.

Large-scale field survey reveals overall yield loss in Japanese apricot possibly caused by two ampeloviruses

Japanese apricot (Prunus mume Sieb. et Zucc.) is one of the most popular fruit tree species in Japan and is most densely cultivated in Wakayama Prefecture. Since the 1980s, graft-transmissible symptoms, such as leaf-edge necrosis and incomplete flower development, have been observed in Nanko, the major Japanese apricot cultivar in Wakayama. Two ampeloviruses, plum bark necrosis stem pitting-associated virus (PBNSPaV) and little cherry virus 2 (LChV-2) were detected in Nanko trees showing typical symptoms. However, there is currently insufficient epidemiological data to infer that these viruses cause the symptoms. In this study, we conducted a large-scale survey of symptoms and RT-PCR detection of the two viruses in midwestern districts, the major cultivation areas in Wakayama. Among 208 surveyed Nanko trees, two viral infections were significantly associated with incomplete flower development, low fruit bearing rate, and interveinal chlorosis. LChV-2 infection also affected Nanko fruit and stone sizes. Additionally, we showed that the two viruses were already widely distributed throughout the main cultivation area. These results imply that the two ampeloviruses cause overall yield loss in Japanese apricot in Wakayama Prefecture.

Characterization of alfalfa virus F, a new member of the genus Marafivirus.

Viral infections of alfalfa are widespread in major cultivation areas and their impact on alfalfa production may be underestimated. A new viral species, provisionally named alfalfa virus F (AVF), was identified using a virion-associated nucleic acid (VANA) metagenomics-based approach in alfalfa (Medicago sativa L.) samples collected in Southern France. The nucleotide sequence of the viral genome was determined by de-novo assembly of VANA reads and by 5’/3’ RACE with viral RNA extracted from enriched viral particles or with total RNA, respectively. The virus shares the greatest degree of overall sequence identity (~78%) with Medicago sativa marafivirus 1 (MsMV1) recently deduced from alfalfa transcriptomic data. The tentative nucleotide sequence of the AVF coat protein shares ~83% identity with the corresponding region of MsMV1. A sequence search of the predicted single large ORF encoding a polyprotein of 235kDa in the Pfam database resulted in identification of five domains, characteristic of the genus Marafivirus, family Tymoviridae. The AVF genome also contains a conserved “marafibox”, a 16-nt consensus sequence present in all known marafiviruses. Phylogenetic analysis of the complete nucleotide sequences of AVF and other viruses of the family Tymoviridae grouped AVF in the same cluster with MsMV1. In addition to 5’ and 3’ terminal extensions, the identity of the virus was confirmed by RT-PCRs with primers derived from VANA-contigs, transmission electron microscopy with virus-infected tissues and transient expression of the viral coat protein gene using a heterologous virus-based vector. Based on the criteria demarcating species in the genus Marafivirus that include overall sequence identity less than 80% and coat protein identity less than 90%, we propose that AVF represents a distinct viral species in the genus Marafivirus, family Tymoviridae.

Resistance of Pepper Cultivars to Ralstonia solanacearum Isolates from Major Cultivated Areas of Chili Peppers in Korea

고추(Capsicum annuum L.)의 주요 병해 중 하나인 풋마름병은 지구 온난화로 인해 여름철 기온이 점차 상승하고 있는 우리 나라에서 피해가 증가하는 추세이다. 이 연구에서는 국내 고추 주산지 12곳에서 풋마름병이 발생한 식물체를 채집하여 총 14 개의 병원균을 분리하였으며, 각 균주의 생리형을 분류하고 병원성 비교 실험을 수행하였다. 생리형 검정 결과 14개의 균주는 생리형 3과 4의 두 개 그룹으로 나뉘었다. 또한 분리 균주들의 병원성 비교 실험에서는 14개의 균주를 10개의 고추 시판품종과 저항성 대조품종(‘코네시안핫’)과 감수성 대조품종(‘건초왕’)을 포함하여 총 12개의 품종에 접종하였다. 그 결과 균주는 병원 성에 따라 6개의 그룹으로 나뉘었고, 고추는 14개 균주의 저항성에 따라 4개의 그룹으로 나뉘었다. 균주 그룹 I은 12개의 고추 품종에 대해 병원성이 가장 강한 균주임을 확인한 반면 균주 그룹 IV는 병원성이 가장 약한 균주임을 확인하였다. 또한, 고추 그 룹 B, C와 D는 몇몇 균주에 중도 저항성(M) 및 저항성(R)을 나타냈지만 저항성 정도가 저항성 대조품종인 ‘코네시안핫’만큼 강 하지 않은 것을 확인할 수 있었다. 이와 같은 결과는 5개의 고추 판별품종을 사용하여 R. solanacearum 균주의 병원성을 비교할 수 있을 것이라 생각된다. 결과적으로 이 연구는 풋마름병 저항성 품종 육성 시 어떤 생리형이 국내에 존재하는지에 대한 정보를 제시하고, 저항성 육종에 이용할 수 있는 유전자원의 선발 방법에 대한 정보를 제공한 점에서 유용할 것으로 사료된다.

Impacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5 and 2.0 °C

Abstract. A new temperature goal of “holding the increase in global average temperature well below 2 ∘C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 ∘C above pre-industrial levels” has been established in the Paris Agreement, which calls for an understanding of climate risk under 1.5 and 2.0 ∘C warming scenarios. Here, we evaluated the effects of climate change on growth and productivity of three major crops (i.e. maize, wheat, rice) in China during 2106–2115 in warming scenarios of 1.5 and 2.0 ∘C using a method of ensemble simulation with well-validated Model to capture the Crop–Weather relationship over a Large Area (MCWLA) family crop models, their 10 sets of optimal crop model parameters and 70 climate projections from four global climate models. We presented the spatial patterns of changes in crop growth duration, crop yield, impacts of heat and drought stress, as well as crop yield variability and the probability of crop yield decrease. Results showed that climate change would have major negative impacts on crop production, particularly for wheat in north China, rice in south China and maize across the major cultivation areas, due to a decrease in crop growth duration and an increase in extreme events. By contrast, with moderate increases in temperature, solar radiation, precipitation and atmospheric CO2 concentration, agricultural climate resources such as light and thermal resources could be ameliorated, which would enhance canopy photosynthesis and consequently biomass accumulations and yields. The moderate climate change would slightly worsen the maize growth environment but would result in a much more appropriate growth environment for wheat and rice. As a result, wheat, rice and maize yields would change by +3.9 (+8.6), +4.1 (+9.4) and +0.2 % (−1.7 %), respectively, in a warming scenario of 1.5 ∘C (2.0 ∘C). In general, the warming scenarios would bring more opportunities than risks for crop development and food security in China. Moreover, although the variability of crop yield would increase from 1.5 ∘C warming to 2.0 ∘C warming, the probability of a crop yield decrease would decrease. Our findings highlight that the 2.0 ∘C warming scenario would be more suitable for crop production in China, but more attention should be paid to the expected increase in extreme event impacts.

Occurrence and distribution of viral diseases of bittergourd (Momordica charantia L) in major cultivated areas of Kerala

Occurrence and distribution of viral diseases of bittergourd (<i>Momordica charantia L</i>) in major cultivated areas of Kerala

A year-round production strategy for the wax apple in Taiwan

Wax apple (Syzygium samarangense Merr. & Perry) has been a popular fruit crop in Taiwan because of its refreshing taste and attractive appearance. Pingtung County, accounting for 78% of the total planting area, is the major cultivation area. Regardless of the stable domestic and export market demand, the production area in Taiwan has decreased by almost 30% in the past decade, mainly due to labor shortage, high technical threshold, and production risk. Nevertheless, the cultivation area in central Taiwan has been increasing in recent years, especially in Nantou, Chiayi, and Yunlin Counties. The expansion of production regions facilitates year-round supply of wax apple fruits. By choosing suitable cultivars and forcing techniques in combination with adequate geographical and environmental conditions, a continuous supply chain for premium fruit has been established. Between October and December, market demand is fulfilled by fruits from Liukuei District in Kaohsiung City. Fruits from Pintung area satisfied the winter/spring market, from November to May. The cool temperatures in high altitude areas (600-1000 m a.s.l.) of Chiayi and Nantou favor the production of high quality fruits for niche markets from June to September. In addition, quality fruits of cultivars with consistent good fruit coloring and low cracking rates can be produced, from March to May, in Pingtung and, between June and September, in central Taiwan. Innovative production technologies and progressive breeding programs further ensure the sustainability of year-round wax apple production in Taiwan.