Early-Stage Brown Spot Disease Recognition in Paddy Using Image Processing and Deep Learning Techniques

India is an agricultural country. Paddy is the main crop here on which the livelihood of millions of people depends. Brown spot disease caused by fungus is the most predominant infection that appears as oval and round lesions on the paddy leaves. If not addressed on time, it might result in serious crop loss. Pesticide use for plant disease treatment should be limited because it raises costs and pollutes the environment. Usage of pesticide and crop loss both can be minimized if we recognize the disease in a timely manner. Our aim is to develop a simple, fast, and effective deep learning structure for early-stage brown spot disease detection by utilizing infection severity estimation using image processing techniques. The suggested approach consists of two phases. In the first phase, the brown spot infected leaf image dataset is partitioned into two sets named as early-stage brown spot and developed stage brown spot. This partition is done on the basis of calculated infection severity. Infection severity is computed as a ratio of infected pixel count to total leaf pixel count. Total leaf pixel counts are determined by segmenting the leaf region from the background image using Otsu's thresholding technique. Infected pixel counts are determined by segmenting infected regions from leaf regions using Triangle thresholding segmentation. In the second phase, a fully connected CNN architecture is built for automatic feature extraction and classification. The CNN-based classification model is trained and validated using early-stage brown spot, developed stage brown spot, and healthy leaves images of rice plants. Early-stage brown spot and developed stage brown spot images used in training and validation are the same images that are obtained in phase 1. The experimental analysis shows that the proposed fully connected CNN-based early-stage brown spot disease recognition model is an effective approach. The classification accuracy of the suggested model is found to be 99.20%. The result of the suggested method is compared with those existing CNN-based disease recognition and classification methods that have used leaf images to recognize the diseases. It is observed that the performance of our method is significantly better than compared methods.

Studies on the isolation, identification and enzyme activity of bioagent Pseudomonas fluorescens used for controlling brown spot disease of rice caused by Helminthosporium oryzae

In the present investigation studies was carried out ontheIsolation, Identification and Enzyme activity of bioagent Pseudomonas fluorescens used for controlling Brown spot disease of Rice caused by Helminthosporium oryzae(Breda de Haan).This is a fungal pathogen causing major disease that causes enormous losses in grain yield (upto 90%) particularly when leaf spotting phase assumes epiphytotic proportions.

First Report of Brown Spot on White Button Mushroom (Agaricus bisporus) Caused by Cedecea neteri in Iran

In autumn 2018, cap discoloration and browning symptoms (up to 20% incidence) were observed on commercially grown white button mushrooms (Agaricus bisporus) in two distinct farms located in Shiraz and Marvdasht Counties in Southern Iran. Symptomatic caps (13 and six caps from Shiraz and Marvdasht Counties, respectively) were characterized by visible brown discoloration with no blotch symptoms, bacterial sticky mass and cap wilting. Isolation of bacterial strains from infected cap tissues was performed on yeast-extract peptone glucose agar (YPGA) according to Hamidizade et al. (2020). The resulted bacterial colonies were oyster-white in color, non-fluorescent, domed convex circular with smooth margins 1-2 mm in diameter. A total of six bacterial strains (Shiraz: Ir1002, Ir1003, Ir1004, Ir1005, Ir1007 and Marvdasht: Ir1027) were isolated from distinct mushroom samples. Standard biochemical and phenotypic analyses (Schaad et al. 2001) showed that the bacterial strains were Gram and oxidase negative, catalase positive and facultatively anaerobic, while no capsule or endospore was observed. All strains were positive in urease production, arginine dihydrolase, hydrolysis of tween 80, and utilization of sucrose and D-sorbitol, while they were negative in amylase, cellulose, lecithinase, pectinase, and protease production as well as casein hydrolysis. Based on these phenotypic characteristics, the strains were supposed to be members of Enterobacteriaceae. They also did not induce hypersensitive reaction (HR) on tobacco (Nicotiana tabacum cv. Turkish) leaves nor did they produce tolaasin when streaked side-by-side with “Pseudomonas reactans” strains on King B medium (Osdaghi et al. 2019). Pathogenicity of the strains was evaluated (repeated twice) on fresh caps of white button mushroom using cut-cap method (Hamidizade et al. 2020). Reference strains of Pseudomonas tolaasii (CFBP 8707) and Mycetocola spp. (CFBP 8708) were used as positive controls, while sterile distilled water was used as a negative control. Brown discoloration appeared 24-36 hours post inoculation on cap surfaces while control caps remained asymptomatic. Koch’s postulates were accomplished by re-isolation and identification of bacterial strains from the symptomatic caps using colony morphology and Gram staining. For molecular identification, all initial as well as re-isolated strains were subjected to amplification and sequencing of 16S rDNA and gyrB (Yamamoto and Harayama 1995; Hamidizade et al. 2020). Obtained nucleotide sequences were deposited into NCBI GenBank (16S: MZ298620 to MZ298625; gyrB: MZ313184 to MZ313189). BLAST search using the 16S rDNA and gyrB sequences showed that the strains isolated in this study had 97-99% sequence similarity to the reference strains of Cedecea neteri. Phylogenetic analyses also confirmed close relationship of bacterial strains from this study to C. neteri strains. Pure cultures of representative strains Ir1004 (CFBP 8900) and Ir1027 (CFBP 8896) are deposited in CIRM-CFBP culture collection. This is the first report of C. neteri causing brown spot disease on button mushroom in Iran, while the bacterium has previously been reported to cause soft rot on Pholiota nameko (Yan et al. 2018), and yellow sticky disease on Flammulina velutipes (Yan et al. 2019) in China. Further comprehensive investigations will shed a light on the economic impact of the brown spot disease on mushroom industry in Iran.

Impact of Agro-met Conditions and Crop Growth Stages on the Progression of Brown Spot Disease in Basmati Rice

The present study was carried out at Crop Research Centre of SVPUAT Meerut, U.P during three cropping seasons i.e. 2018, 2019 and 2020 using basmati rice as test cultivar. The study was primarily focused upon the combined effect of weather parameters and crop growth stages of rice crop on the progression of brown spot disease. It was noticed that disease was first observed at late vegetative stage in every cropping season viz. 2018, 2019 and 2020 and reached its maximum towards maturity phase of the crop by obtaining total AUDPC’S of 1049.3, 1170.74 and 852.6 respectively. A significant negative correlation between weekly percent disease index (PDI) and T-max & T-min was obtained recording correlation coefficients (r) of (- 0.71 & - 0.98), (- 0.88 & - 0.98) and (- 0.63 & - 0.98) during 2018, 2019 and 2020 respectively indicating decline in maximum and minimum temperatures at the terminal stages of the crop can greatly favor disease progression. A non-significant positive correlation was obtained between weekly m-RH and PDI to the end of every crop season. During the year 2020, a highly significant negative correlation was obtained between weekly a-RH and PDI (r = - 0.803) in contrast with the years 2018 (r = - 0.55) and 2019 (r = -0.477) exhibiting non-significant negative correlation which might be the reason for low PDI during the year 2020 due to greater decline in relative humidity to the end of the crop season. Although, a non-significant negative correlation between weekly PDI and RF (rainfall) and partial positive correlation with weekly bright sunshine hours (BSS) was obtained during all three crop seasons, high intermittent rainfall from late vegetative to reproductive stage during 2018 and 2019 might be responsible for large amount of spore dispersal (high inoculum pressure) leading to greater disease progression. The regression model developed using 2018, 2019 and 2020 meteorological data, which was validated with disease severity data of 2019 yielded significant R2 value of 0.98 using observed and predicted values.

Biochemical Profiling of Resistant Phenotypes Against Bipolaris oryzae Causing Brown Spot Disease in Rice

Brown leaf spot disease of rice is a dominant lethal disease, caused by the fungus Bipolaris oryzae. The pathogen is an obligate parasite and causes qualitative and quantitative damage to rice crop. The objective of the present study was to investigate what extent the defense related biochemical compounds reflect the distinct categories of resistance phenotypes in rice against brown spot disease. This was done by determining the concentration of Catalase (CAT), Phenylalanine ammonia-lyase (PAL), Polyphenol oxidase (PPO), Peroxidase (POD), and β-1,3-Glucanase enzymes in resistant, moderately resistant and susceptible rice genotypes. The disease resistant phenotypes in rice line (PARC-7) reflect the higher accumulation of CAT, PAL, PPO, POD, and β-1,3-Glucanase. The pattern of enzyme accumulation was similar in all resistant genotypes. The rice genotypes with moderately resistant phenotypes showed significant difference with respect to the concentration of biochemical defense-related compounds. The difference in accumulation of defense related enzymes reflected the level of disease severity (% leaf area covered) on resistant and moderately resistant genotypes. The susceptible rice genotypes showed the minimum concentration of these enzymes, with the lowest concentrations found in the rice variety Bas-2000 (80% Disease Index). The differential defense response in resistant and susceptible genotypes suggests that these enzymes can be used as biochemical markers for early detection of disease resistant genotypes. The study of enzyme accumulation at different time points and at different levels of disease severity helps to understand the resistance mechanisms against brown spot disease in rice.

Assessment of Genetic Parameter of Variability and Heritability based on Morphological Traits and Disease Parameters for Brown Spot in Rice (Oryza sativa L.)

Cochliobolus miyabeanus is a serious threat to the standing rice crop in context of production and productivity as it results in loss of both grain quality and yield. The pathogen causes brown spot disease in rice which had resulted in two severe famines in past. Hence, in this regard it is imperative to search for new and diverse resistance sources and to evaluate them with respect to genetic variability and inherent genetic potential for various morphological traits including yield and yielding attributing traits and disease estimating parameters for identifying high yielding diverse resistant lines that could be utilized in future breeding programmes aimed at development of superior cultivars against brown spot disease. Keeping this in view this study was conducted at Rice Research Farm, RPCAU, Pusa to evaluate 300 genotypes for rice for various morphological traits and disease estimating parameters along with three checks for disease response in augmented design. All the recommended package of practices was followed along with necessary prophylactic plant protection measures to raise a good crop. Data on different traits and parameters under study were recorded and analysed biometrically to assess the genetic parameter of variability and heritability. The ANOVA showed significant difference among the genotypes for most of the traits and parameters under study which reflects ample amount of variability among the genotypes. Further, the smaller difference between GCV and PCV and higher estimates of heritability and genetic advance as percentage of mean revealed higher percentage of inherent genetic potential in overall variability. The higher estimates of heritability and genetic advance as percent of mean for grain yield per plant and AUDPC suggested that the resistant lines identified in this study can be easily advanced through generation following phenotypic selection for derivation of high yielding resistant lines.

First Report of Alternaria tenuissima Causing Brown Spot Disease of Angelica dahurica in China

Angelica dahurica (Fisch. ex Hoffm.) is an abundantly cultivated Chinese herbal medicine plant in China with about 4000 hectares grown, the annual production is up to 24,000 tons. The medicinal part of A. dahurica is its root, and mainly function for treat cold, headache, toothache, rhinitis, diabetes, etc. Besides, A. dahurica is also used as a spice in Asia. In September 2018, brown spot was observed on the leaves of A. dahurica in fields of Anguo City, Hebei Province, China. In the field investigated, the incidence of brown spot disease reached 15%. The infected leaves showed brown spots surrounded with pale yellow edge, resulting in withered of the whole leaf. It seriously endangers the growth of A. dahurica, reducing the yield and quality of medicinal materials, even leading to the death of plants. We isolated the pathogen from 10 leaves with same lesions, the small square leaf pieces of approximately 3 to 5 mm were obtained with the sterile scissors from the junction of infected and healthy tissues, sterilized with sodium hypochlorite (10%) for 1 min followed by washing in sterile water for 3 times, then incubated on potato dextrose agar (PDA) plates at 25°C for 4 days. The culture was transferred to new PDA plates and was cultivated in dark at 25°C for 10 days. A total of 3 species of fungi were isolated, and only one fungus species has been found to be able to cause the original pathological characteristics of A. dahurica leaves through the back-grafting experiment. The mycelium was black and began to sporulate after 8 days on PDA media by single spore separation. Multiple spores joined together to form spores chain. The spores were spindle-shaped, yellow to yellow brown, and size ranged from 45 to 55 × 15 to 20 µm (n=50), with zero to three longitudinal septa and one to five transverse septa. For pathogenicity tests, the spore suspension (3.5×105 spores/mL) were inoculated to healthy plants grown in experimental field, the test was repeated four times, and 10 leaves were inoculated in each repetition, and the sterile water was inoculated as the blank control. Inoculated leaves were covered with transparent plastic bags for 24 h to keep humidity. Nine days later, it was found that there were lesions on the leaves inoculated with the pathogen, and the traits were the same as those in the field, while the controls are healthy. The fungus was consistently isolated from the inoculated leaves. The similar isolates were re-isolated from the inoculated and infected leaves and identified as Alternaria tenuissima by DNA sequencing, fulfilling Koch’s postulates. Fungal genomic DNA was extracted from 7-day-old culture. PCR amplifications were performed using primers ITS1 / ITS4 and TEFF / TEFR respectively (Takahashi et al. 2006, Du 2008). The nucleotide sequence of PCR products, which have been deposited in Genebank under the accession numbers MN153514 and MN735428, showed 99.8%-100% identity with the corresponding sequences of A. tenuissima (MW194297 and MK415954). In order to further identify the pathogen species, we constructed a phylogenetic tree by combining TEF sequence and ITS sequence to distinguish the relationship between the pathogen and other minor species in the genus Alternaria, the isolate was clustered in the Alternaria clade. Therefore, the pathogen was identified as A. tenuissima based on the morphological characteristics and molecular identification. To our knowledge, this is the first report of A. tenuissima causing leaf spot on A. dahurica in China.