Rice Plant Diseases Research Articles

Sistem Pakar Diagnosa Hama Penyakit Tanaman Padi Dan Holtikultura Menggunakan Metode Forward Chaining Berbasis Android

The development of information and communication technology-based smartphones and mobilephone growing rapidly. It is characterized by the number of smartphone users in the community. Utilization of information and communication technology is implemented in the form of knowledge application. One of these applications on the world agricultural expert system based on mobile. Knowledge of this expert system has many sources including research or research and observations that have been practiced by experts and issued either through web resources and other sources such as agricultural books, journals and others. This expert system uses Forward Chaining method using base database organized into a table in a rule that an expert and user can draw conclusions from what has been diagnosed by this expert system. Application of expert system designed and developed as an expert tools and users in diagnosing pests and diseases of rice plants and horticulture of the analysis by an expert and analysis according to the book or internet media. This expert system will show the questions will then be selected by the user to find a solution on the diagnostics program that has been done on this expert system. In addition the expert system is equipped with the paperwork to determine how plant pest management, plant species and type of fertilizer.

Keragaman Morfologi Daun Padi Lokal Indonesia dan Korelasinya dengan Ketahanan Penyakit Hawar Daun Bakteri

Bacterial leaf blight (BLB) is one of the major diseases of rice plants mainly in irrigated rice caused by pathogenic bacteria Xanthomonas oryzae pv. oryzae (Xoo). Leaf morphology becomes an interesting character to be investigated due to its relationship with the intensity of BLB disease, because the leaf is the part of plant which is infected by the bacteria. The purpose of this research was to obtain information on the variability of leaf morphology and its correlation with BLB diseases, to support plant breeding program of BLB disease-resistant rice varieties. A total of 25 local rice accessions were characterized phenotypically. Leaf morphological characters were examined without replication, while in Xoo resistance (pathotype IV) test was done by using randomized block design with three replications. Characterization on leaf morphology indicated that all local rice accessions had green collar, transparent auricle color, white ligule color, and 2-cleft ligule shape. In four weeks after inoculation, four accessions (Ketan Lomah Hitam, Bumbuy Inih, Gonggoi, and Waren) showed disease severity percentages of BLB diseases on the range between 13-16%. These observations indicated that these accessions had slightly sussceptible response to BLB diseases wich were better than the other accessions. Leaf-surface morphology was positively correlated with BLB disease. The four accessions were feathery or slightly hairy with a short-sized leaf. The results of this research could be used as a reference for developing of BLB resistance rice varieties.

RICE PLANT DISEASE CLASSIFICATION USING TRANSFER LEARNING OF DEEP CONVOLUTION NEURAL NETWORK

Abstract. Early and accurate diagnosis of plant diseases is a vital step in the crop protection system. In traditional practices, identification is performed either by visual observation or by testing in laboratory. The visual observation requires expertise and it may vary subject to an individual which may lead to an error while the laboratory test is time consuming and may not be able to provide the results in time. To overcome these issues, image based machine learning approach to detect and classify plant diseases has been presented in literature. We have focused specifically on rice plant (Oryza sativa) disease in this paper. The images of the diseased symptoms in leaves and stems have been captured from the rice field. We have collected a total of 619 rice plant diseased images from the real field condition belong to four classes:(a) Rice Blast (RB), (b) Bacterial Leaf Blight (BLB), (c) Sheat Blight (SB) and (d) Healthy Leave (HL). We have used a pre-trained deep convolutional neural network(CNN) as a feature extractor and Support Vector Machine (SVM) as a classifier. We have obtained encouraging results. The early identification of rice diseases by this approach could be used as a preventive measure well as an early warning system. Further, it could be extended to develop a rice plant disease identification system on real agriculture field.

Identification of Diseases in Rice Plants Using the Gray Level Co-Occurrence Matrix Method

Rice plants (Oryza sativa, sp) are a staple food raw material that is vital for the people of Indonesia. Rice plants are included as a year / annual plant group. The management of rice plants is an innovative and dynamic approach in increasing the production and opinion of farmers through assembling technological components in a participatory manner with farmers. For this reason, appropriate technology facilities are needed that can be used by farmers in determining the type of leaf disease that burns during the growing period of rice so that it can increase production. This study aims to apply the Gray level Co-Occurrence Matrix method to produce feature values on rice leaves. Differences in the patterns of rice leaves are used by identifying each rice leaf pattern, which results in the type of leaf disease burning through the rice leaf pattern. In this study, the accuracy of this system was obtained at 72.5%.

ESforRPD2: Expert System for Rice Plant Disease Diagnosis

One of the factors causing rice production disturbance in Indonesia is that farmers lack knowledge of early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make an early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts and uses a Waterfall Paradigm and Unified Modeling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with a sensitivity of 87.5%. ESforRPD2 is available in Indonesian at http://esforrpd2.blog.unmul.ac.id

Plant extracts, bioagents and new generation fungicides in the control of rice sheath blight in Guyana

Sheath blight disease has become a major constraint in cultivation of rice in Guyana inflicting significant yield losses. Eleven plant extracts, three biocontrol agents and five new generation fungicides were screened for their efficacy against sheath blight pathogen, Rhizoctonia solani under in vitro conditions. The extracts of lemon grass, thick leaf thyme, marigold and clove at 15% showed high inhibition to mycelial growth of R. solani. Among biocontrol agents, Bacillus cereus OG2L exhibited high inhibition against mycelial growth of R. solani. New generation fungicides viz., Antracol (Propineb), Nativo (Trifloxystrobin + Tebuconazole), Silvacur Combi (Tebuconazol + Triadimenol), Cyclops (Cinnamon Oil + Clove Oil) and a biofungicide (Serenade - Bacillus subtilis cepa QST 713) recorded complete inhibition of R. solani under in vitro conditions. The plant extracts, bioagent and new generation fungicides that showed high inhibition to R. solani under in vitro were evaluated for their efficacy against shealth blight disease under greenhouse and field experiments. The extracts of lemon grass (7.21; 8.04; 4.85%), thick leaf thyme (6.71; 7.28; 4.71%) at 15%; B. cereus OG2L at 2 g L−1 (7.86; 8.68; 5.09%) and new generation fungicides viz., Antracol 70WP (8.51; 7.79; 5.27%), Nativo (7.62; 7.21; 4.20%) and Serenade (7.78; 7.66; 4.79%) have recorded low percent disease severity compared to untreated control (26.25; 31.16; 20.43%) in greenhouse, field trials I and II, respectively. The plant extracts, bioagent and new generation fungicides recorded a greater reduction (73.63%) in sheath blight disease incidence with an average yield increased from 10.25 to 36.03% compared to the control. The current study has provided chemical and non-chemical options for an integrated management of sheath blight disease in rice plants.

Market Potential of Paddy Crop in Dhamtari District of Chhattisgarh

Syngenta India Ltd. is a leading company in Fungicide marketing in Chhattisgarh. The present study had been assigned by the organization for the period of two months in-plant training programme in the Dhamtari district of Chhattisgarh with a view to analyse the Market share of different fungicide company. Fungicides prevent and cure diseases which can have adverse effects on crop yields and quality. The market in rice Plant diseases are caused by a great variety of pathogens.

ESforRPD2: Expert System for Rice Plant Disease Diagnosis

One of the factors causing rice production disturbance in Indonesia is the lack of knowledge of farmers on early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts, and uses a Waterfall Paradigm and Unified Modelling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with an accuracy of 87.5%. ESforRPD2 is available in Indonesian at: http://esforrpd2.blog.unmul.ac.id

Detection and classification of rice plant diseases

Detection and classification of rice plant diseases

Molecular diversity of internal transcribed spacer among the monoconidial isolates of Magnaporthe oryzae isolated from rice in Southern Karnataka, India.

Blast disease of rice plant is caused by Magnaporthe oryzae (anamorph Pyricularia oryzae). This disease is recognized to be one of the most serious diseases of rice crop around the world. A total of 72 monoconidial isolates of M. oryzae obtained from blast disease samples collected around Southern Karnataka were characterized using internal transcribed spacers of the ribosomal DNA sequences. These were analyzed by comparing with already deposited sequences in GenBank database. It helped in diagnosing the invasive pathogen in all locations. Variability of rDNA sequences was found to be highly polymorphic with 0.068962 nucleotide diversity showing 6 distinct clades. 33 haplotype groups were identified with haplotype diversity of 0.8881 and Tajima's neutrality test with a D value of −1.96827 with P < 0.05 showing the presence of variations among the sequences of pathogen isolates. The Tajima’s D value of less than one indicates the presence of a high number of rare alleles. Our study indicates that the pathogen might have undergone recent selection pressure because of the exposure to a large number of cultivars resulting in the evolution of rare alleles. This shows the importance of characterizing internal transcribed spacer (ITS) to know pathogen diversity and its fitness which has potential to contribute to the field of breeding for blast disease resistance.

Evaluasi Ketahanan Galur International Rice Bacterial Blight terhadap Hawar Daun Bakteri dan Identifikasi Patotipe Xanthomonas oryzae pv. oryzae Provinsi Jawa Tengah Berdasarkan Galur IRBB

Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is the major disease in rice plants causing considerable economic losses. The objective of the study was to evaluate the resistant International Rice Bacterial Blight (IRBB) lines against bacterial leaf blight and the identification of Xoo pathotype from Central Java Province as the basis recommendation of the resistant varieties assembly with the background of resistant genes to overcome BLB disease. The evaluation of Xoo isolates from 22 districts in Central Java Province on IRBB lines was conducted in the rainy season 2016-2017 using split plot with three replications. The main plot was 15 IRBB lines, while the subplot was 110 Xoo isolates. Among 15 lines of IRBB, there were 10 lines have functioned as pathotype examiner of Xoo. The results obtained 6 lines were reacted resistant, namely IRBB5, IRBB7, IRBB8, IRBB57, IRBB64, and IRBB66. The IRBB66 line can be used as a resistant elder for the assembly of BLB resistant varieties because it has a combination of pyramiding resistant genes that were effective against BLB in some areas of Central Java Province. Pathotype IX was only found and dominant in Pemalang. Pathotype X was obtained in six districts of Tegal, Brebes, Banjarnegara, Purbalingga, Purworejo, and Grobogan. Pathotype XII was the most dominant prototype in 15 districts. Assembling of resistant varieties with resistant gene backgrounds based on the existence of a specific Xoo pathotype in the field can reduce the severity of BLB disease.

Comparison of various filters for noise removal in paddy leaf images

Automatic detection of plant diseases is one the important challenging problems in agriculture field. So the basic analyzing method for automatic identification is filtering technique of preprocessing method. Hence, this Image filtering plays a important role to remove noise from image. Consequently this preprocessing method is the initial stage to make better image quality. The purpose of this paper is comparing four types of filtering techniques to differentiate the image quality in Gaussian filter, median filter, mean filter and weiner respectively filter using common data set. The image quality of overall results shows that the comparison of various filtering technique performed to enhancement quality using hybrid technique. So this paper gives best starting for researchers to automatic detection of rice plant disease detection.

Respon Beberapa Varietas Padi Terhadap Serangan Fusarium fujikuroi Penyebab Penyakit Bakanae

Fusarium fujikuroi is the cause of bakanae disease in rice plants. Level of bakanae disease attack on some rice cultivation land in West Sumatra, especially in Padang Pariaman district is quite high. One effort to suppress the development of F. fujikuroi is by planting resistant varieties. In this study, 15 rice varieties originating Sumatera Barat were used to be tested for their response to F. fujikuroi attack. The purpose of this study was to obtain the varieties with the low attack rate of F. fujikuroi. Parameters observed were number of dead seeds, number of dead seedlings, number of stunted seedlings, number of seeds showing symptoms of Bakanae and total infected seeds. The results of the study indicated that symptoms of F. fujikuroi attack varied which were dead seeds, stunting seedlings, dead seedslings and bakanae. The response of rice varieties to F. fujikuroi attack was different with characterized by different levels of infection rates. Low infection rates were found in Pessel varieties (2.0%), Batang sahalai (15.5%), Cisokan (17.0%), and Batang Lembang (20%). Other varieties showed a high percentage of F. fujikuroi attacks ranging from 20% to 54.5%.

Penerapan Metode Forward Chaining Pada Sistem Pakar Untuk Diagnosa Hama Dan Penyakit Padi

&#x0D; So that the computer can act as and as good as a human being, then the computer should be given the lack of knowledge that has the ability to catch. One of them is an expert system, is a system that attempted to adopt human knowledge to a computer that is designed to model the ability to resolve problems such as befits an expert. With this expert system, people who have yet to figure it out at all to resolve the problem or just simply looking for an actual information can only be obtained with the help of experts in their field. Knowledge society in Indonesia about pests and diseases of rice plant is still low, including handling is known only to the extent of the knowledge of fellow farmers, pest and disease if there is a new kind of farmers are not aware of it, on the other hand there are some the expert or experts who know about the pests and diseases of rice plant, but the number of experts or experts with a large number of farmers are not balanced. Therefore, due to the application of the method of forward chaining inference on expert system to diagnose plant pests and diseases of rice can be the information and knowledge that will help the community or individuals to know the types of pests and what diseases that attack the rice plant, without having to wait and expect a straight answer from the experts

Klasifikasi Penyakit Daun Padi Berdasarkan Hasil Ekstraksi Fitur GLCM Interval 4 Sudut

One of the factors causing rice production depression is a typical disease in rice plants. Typical of disease in rice plants, among others, such Blast Disease, Leaf Blight Disease, Disease Hawar On Stem, Crackle Disease and so on. Each type of disease requires different treatment, but not all farmers know the type of disease so as to allow for errors in the handling. This research made an application program that can identify rice pests to facilitate farmers solve the problems of rice plants disease since it becomes important to make a disease classification system on the leaves of rice plants. This research uses backpropagation method to classify the type of disease resulting from feature extraction of GLCM with 4 angles. Results obtained 80% accuracy from 30 data, with 16 seconds testing time.

Comparative analysis of microbial diversity and bacterial seedling disease‐suppressive activity in organic‐farmed and standardized commercial conventional soils for rice nursery cultivation

AbstractThe outbreak of rice plant diseases can be effectively suppressed in organic farming systems. However, the mechanisms of disease suppression by organic farming systems are not well understood. When Burkholderia‐infected rice seeds were sown and cultivated on nine organic‐farmed soils which were supplied by nine independent organic rice farmers or standardized commercial conventional soils, the emergence of bacterial seedling diseases was suppressed to equivalent degrees in nine organic‐farmed soils, whereas the diseases occurred in two commercial conventional soils. In any organic or commercial conventional soil sown with healthy rice seeds as a control, the diseases did not appear. Upon physicochemical analysis of the nine organic‐farmed soils, component common to these organic‐farmed soils seemed to not be directly associated with disease‐suppressive activity. However, microbiome analyses indicated that the bacterial population in these nine organic‐farmed soils was more diverse than those in commercial conventional soils. Intriguingly, the diverse bacterial population structures of organic‐farmed soils were preserved after irrigating and sowing rice seeds, but that of commercial conventional soils was clearly changed by them. Thus, organic‐farmed soils seem to maintain robust bacterial populations despite the irrigation and seedling growth. Indeed, pathogenic Burkholderia in infected rice seeds also did not proliferate in the seedling grown on organic‐farmed soils. Taken together, the common feature of organic‐farmed soils might be the correlation between bacterial seedling disease‐suppressive activity and higher robustness of the diversified microbiome.

PENGARUH KONSENTRASI P. polymyxa DAN DOSIS PUPUK NITROGEN TERHADAP INTENSITAS SERANGAN PENYAKIT BLAS (Pyricularia oryzea) PADA TANAMAN PADI (Oryza sativaL.)

Rice is the main food crop commodity in Indonesia. However, in the process of cultivation there are obstacles that can reduce the level of productivity. One of the obstacles is the presence of pest attack one of them attacks blas disease (Pyricularia oryza). One of the causes is excessive nitrogen fertilization. One of the factors that can suppress the development of this disease is by application of P. polymyxa. This is the underlying title of this study. This study aims to determine the effect of P. polymyxa concentration and dose of nitrogen fertilizer on the intensity of blast disease (Pyricularia oryzea) in rice plants (Oryza sativa L.). This research was conducted in February - June 2017, where research Kebumen, Banyubiru, Semarang at altitude of place 478 m. The method used in this research is factorial method with RAKL pattern consists of 2 treatment factors and 3 repetitions. The first factor is the concentration of P. polymyxa (P) consisting of 4 levels ie concentration 0, 5, 10 and 15 cc / liter (P0, P1, P2 and P3) and the second factor is the dosage of nitrogen fertilizer (N) ie dose 45, 90 and 135 kg / ha (K0, K1, K2 and K3). The results showed that interaction between P. polymyxa concentration and nitrogen dose gave a very real effect on the intensity parameter of leaf blast attack and number of tillers but gave a real effect on the intensity parameter of neck blast attack, plant height, number of grain of hollow per panicle, and per hectare, number of permedional grains, wet stalks, dry stover, productive shoots, panicle length, number of grains per panicle and weight per 1000 seeds. The best treatment in the study of the effect of P. polymyxa concentration and the dose of nitrogen fertilizer on the intensity of blast disease (Pyricularia oryzea) in rice plants (Oryza sativa L.) was P2N2 (P. polymyxa 10 cc / liter with nitrogen dose of 90 kg / ha) .

Bioactive substance use of leaf extract of piper caninum blume pressing for blas disease and increase production in rice

The purpose of this study was to determine the effect of bioactive substances in the leaf extract of Piper caninum against rice blast disease caused by the fungus Pyricularia oryzae. This study was conducted in a greenhouse, using a completely randomized design. The results showed that the leaf extract of P. caninum formula can significantly suppress the intensity of blast disease in rice plants. The inhibition (90.51%) contained at a concentration of 2.5%. P. caninum leaf extract also significantly affect the growth and yield components. The concentration of 2.5% provides the highest grain yield (11.43 t/ha), while the extract 3.5% the intensity of the disease has increased and yield components decreased because the rice plants begin to experience toxic due to the concentration exceeding the limit too high extract optimal.

Comparing the genetic diversity and structure of indigenous Korean and Chinese populations of Laodelphax striatellus Fallén using mitochondrial haplotypes

The small brown planthopper, Laodelphax striatellus Fallén, is a major migratory pest from China to Korea and transmits viral diseases of rice plants. In this study, we compared the genetic structures of overwintered indigenous Korean and Chinese populations. The eight Korean populations consisted of 33 haplotypes, and 16 of these were newly identified. The genetic diversity of the Korean population revealed high haplotype diversity (Hd) and low nucleotide diversity (π) of 0.86±0.017 and 0.0024±0.0001 on average, respectively. These values for the Chinese population were Hd=0.92±0.016 and π=0.0026±0.0002. Overall, genetic distances by pairwise FST were generally low, ranging from −0.022 to 0.089. Moreover, the Korean population revealed its ongoing population expansion by showing negative values in the neutrality test (Tajima's D=−1.4, Fu's Fs=−15.8) and a unimodal pattern in the mismatch distribution analysis. The genetic structures and population relationships were determined using 8 indigenous Korean and 30 Chinese populations by Bayesian approaches and population tree construction, respectively. The genetic structure was inferred as five (K=5), and all indigenous Korean populations as well as 10 Chinese populations from the Shanghai city, Anhui, Henan, Jiangsu, Liaoning, Shandong, and Zhejiang provinces were grouped into ‘G3’. These results provide partial support for unidirectional gene flow by migratory Chinese populations into Korea. Further analysis conducted using specimens from China and Korea collected in similar periods is necessary to clarify the migration population's origin and its effect on the genetic structure of the indigenous populations.

UJI ADAPTASI VARIETAS UNGGUL BARU TERHADAP WERENG HIJAU DAN PENYAKIT TUNGRO DI KABUPATEN MERAUKE, PROVINSI PAPUA

&lt;p&gt;&lt;em&gt;&lt;span class="fontstyle0"&gt;Tungro is one of the important diseases in rice plants caused by two types of viruses were rod virus (rice tungro bacilliform virus) and spherical virus (rice tungro spherical virus) that was transmitted by the green leafhopper (GLH) Nephotettix virescens. The purpose of this study to determine the adaptation of new improved varieties against GLH and tungro disease in Merauke, Papua Province. Research conducted at Tanah Miring District, Merauke, Papua Province between February and June 2010. The study was a randomized block design with three replications. The treatment consisted of 11 varieties, namely Inpari 1, Inpari 2, Inpari 3, Inpari 4, Inpari 5 Merawu, Inpari 6 Jete, Inpari 7 Lanrang, Inpari 8, Inpari 9 Elo, Inpari 10 Laeya, and Ciherang. Observations included the intensity of tungro and GLH population density at the age of rice plants of 1, 2, 3, and 4 weeks after planting (WAP). In addition, it was observed also the yield components of rice. The results showed that the GLH population density and the intensity of tungro disease was not significantly different at the 11 varieties tested. GLH attack had been found in 1 WAP with an average population density of 4.18 individual/20 single swing. GLH increases with the age of the rice crop with an average population density in 2 WAP (20 individual), 3 WAP (103.27 individual), and 4 WAP (154.15 individual) per 20 single swing. Tungro disease intensity in 11 varieties began were found in 3 WAP on average by 0.16% and increased at 4 WAP on average by 0.28%. Varieties significant effect on yield components such as plant height, panicle length, number of total grain/panicle, percentage of filled grain, 1000 grain weight and productivity except the number of panicles/clump. &lt;/span&gt;&lt;/em&gt;&lt;span class="fontstyle2"&gt;&lt;strong&gt;&lt;span&gt;&lt;br /&gt; &lt;!--[if !supportLineBreakNewLine]--&gt;&lt;br /&gt; &lt;!--[endif]--&gt;&lt;/span&gt;&lt;/strong&gt;&lt;/span&gt;&lt;/p&gt;