scholarly journals Pendugaan Intensitas Serangan Penyakit BLB (Bacterial Leaf Blight) pada Tanaman Padi menggunakan Pendekatan Citra Termal

2021 ◽  
Vol 9 (1) ◽  
pp. 86
Author(s):  
Ni Luh Putu Jullyantari ◽  
I Made Anom Sutrisna Wijaya ◽  
I Putu Gede Budisanjaya
Keyword(s):  
Technology Development ◽  
Thermal Image ◽  
Leaf Blight ◽  
Bacterial Leaf Blight ◽  
Estimation Accuracy ◽  
Thermal Camera ◽  
Microsoft Excel ◽  
Rice Plants ◽  
Disease Attack ◽  
Attack Intensity

Penyakit BLB merupakan salah satu penyakit yang berbahaya bagi tanaman padi. Penyakit ini biasanya menyerang di setiap fase pertumbuhan. Perhitungan intensitas serangan penyakit BLB masih dilakukan secara manual. Pengembangan teknologi dalam pendugaan intensitas serangan penyakit BLB sangat diperlukan. Penelitian ini bertujuan untuk membangun persamaan pendugaan intensitas serangan penyakit BLB menggunakan pendekatan citra termal. Penelitian ini menggunakan Drone DJI Inspire 1 dengan kamera termal DJI Zenmuse XT. Pengolahan data menggunakan software Agisoft Photoscan, Arcgis 10.3 dan Microsoft Excel. Dari hasil analisis citra termal diperoleh bahwa persamaan pendugaan intensitas serangan adalah y = 4.9533x-144.42 dan akurasi pendugaannya tinggi yaitu 90,45% dengan nilai eror 8,43%. Suhu kanopi dapat diklasifikasi menjadi empat sesuai dengan intensitas serangan yaitu 29,83-31,84oC untuk intensitas serangan ringan, 31,85-34,39oC untuk intensitas serangan sedang, 34,40-43,52oC untuk intensitas serangan berat dan 43,53-48,09oC untuk intensitas serangan puso. Berdasarkan hasil dari penelitian yang telah dilakukan dapat disimpulkan bahwa pendekatan citra termal dapat digunakan untuk menduga intensitas serangan penyakit BLB pada tanaman padi.   Bacterial Leaf Blight (BLB) is a dangerous disease for rice plants. This disease can attack in every phase of growth. Calculation of BLB disease attack intensity is currently still done manually. Technology development in estimating the intensity of BLB disease is very necessary. This study aims to establish the equation for estimating BLB disease intensity using a thermal image approach. Drone DJI Inspire 1 with a thermal camera DJI Zenmuse XT was used in this research. Processing data using software Agisoft Photoscan, Arcgis 10.3 and Microsoft Excel. From the results of the thermal image analysis, it was found that the equation for estimating attack intensity is y = 4.9533x-144.42 and estimation accuracy is high at 90,45% with an error value of 8,43%. Temperature of the canopy can be classified into four according to the intensity of the attack, namely 29,83-31,84oC for mild attack intensity, 31,85-34,39oC for moderate attack intensity, 34,40-43,52oC for intensity of severe attacks and 43,53-48,09oC for intensity of puso attacks. From these results it can be concluded that the thermal image approach can be used to estimate BLB disease attacks on rice plants.

scholarly journals Pendugaan Intensitas Serangan Penyakit BLB (Bacterial Leaf Blight) pada Tanaman Padi melalui Pendekatan Citra Multispektral

2020 ◽  
Vol 8 (2) ◽  
pp. 338
Author(s):  
Gusti Bagus Eka Chandra ◽  
I Made Anom S. Wijaya ◽  
Yohanes Setiyo
Keyword(s):  
Technology Development ◽  
Leaf Blight ◽  
Multispectral Image ◽  
Bacterial Leaf Blight ◽  
Estimation Accuracy ◽  
Multispectral Images ◽  
Multispectral Imagery ◽  
Rice Plants ◽  
Red Edge ◽  
Disease Attack

ABSTRAK Penyakit Bacterial Leaf Blight (BLB) merupakan salah satu penyakit yang berbahaya bagi tanaman padi. Penyakit ini bisa menyerang di setiap fase pertumbuhan. Perhitungan intensitas serangan penyakit BLB saat ini masih dilakukan secara manual. Diperlukan pengembangan teknologi dalam pendugaan intensitas serangan penyakit BLB melalui citra multispektral. Penelitian ini bertujuan untuk (1) untuk mendapatkan nilai korelasi terbaik antara intensitas serangan penyakit BLB dengan parameter citra multispektral (2) Untuk mendapatkan persamaan pendugaan intensitas serangan penyakit BLB berdasarkan pendekatan citra multispektral. Drone DJI Inspire 1 dengan kamera multispektral digunakan untuk menangkap gambar petak padi. Pengolahan data citra multispektral menggunakan Agisoft Photoscan dan software QGIS 3.8. Berdasarkan dari hasil akuisisi, citra multispektral menghasilkan citra band red, NIR, green, red edge, RGB yang kemudian diolah menjadi transformasi citra NDVI, EVI, dan NDRE. Dari ketiga parameter citra multispektral, nilai NDVI memiliki tingkat korelasi yang lebih kuat dengan koefisien determinasi sebesar 97,5% dan menghasilkan persamaan linier sebagai berikut y = -419,6 + 169,3. Dalam perhitungan nilai eror parameter NDVI memilikinilai eror paling rendah dibandingkan parameter EVI dan NDRE yaitu sebesar 4,64% dengan akurasi pendugaan 95,36%. Citra multispektral dapat digunakan dalam pendugaan intensitas serangan penyakit BLB pada tanaman padi karena menghasilkan nilai korelasi yang sangat kuat, dan akurasi pendugaan yang tinggi dengan nilai eror yang rendah tidak melebihi 10%. ABSTRACT  Bacterial Leaf Blight (BLB) is a disease that is dangerous for rice plants. This disease can attack in every phase of growth. Calculation of BLB disease attack intensity is currently still used manually method. Technology development is needed in estimating the intensity of BLB disease through multispectral imagery. This study aims (1) to get the best correlation value between the intensity of BLB disease attack with multispectral image parameters (2) to get the equation for estimating the intensity of BLB based on multispectral images parameter. Drone DJI Inspire 1 with a multispectral camera is used to captured the paddy field. The captured images was processed using Agisoft Photoscan and QGIS 3.8 software. Based on the results of the acquisition, multispectral images produce red, NIR, green, red edge, RGB band images which were then transformed into NDVI, EVI, and NDRE images. Of the three multispectral image parameters, NDVI values ??have a stronger correlation level with a determination coefficient of 97.5% and produce the following linear equation y = -419.6 + 169.3. In calculating the NDVI parameter error value has the lowest error value compared to the EVI and NDRE parameters which is 4.64% with an accuracy estimate of 95.36%. Multispectral imagery can be used in estimating the intensity of BLB disease attacks in rice plants because it produces a very strong correlation value, and high estimation accuracy with a low error value does not exceed 10%.

scholarly journals On forecasting of bacterial leaf blight of rice plants by using natural phage

1974 ◽  
Vol 20 ◽  
pp. 62-65
Author(s):  
Norisato GAMO ◽  
Takayuki YAMAGUCHI ◽  
Sadao KIMURA
Keyword(s):  
Leaf Blight ◽  
Bacterial Leaf Blight ◽  
Rice Plants ◽  
Natural Phage

scholarly journals Pendugaan Intensitas Serangan Penyakit Blas pada Tanaman Padi Melalui Pendekatan Citra NDVI (Normalized Difference Vegetation Index)

2019 ◽  
Vol 7 (2) ◽  
pp. 287
Author(s):  
I Made Prasetia Candra Andika ◽  
I Made Anom Sutrisna Wijaya ◽  
Ida Bagus Putu Gunadnya
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Technology Development ◽  
Blast Disease ◽  
Aerial Photo ◽  
Rice Plants ◽  
Processing Data ◽  
Arc Gis ◽  
The Relationship ◽  
Attack Intensity

Penyakit blas merupakan salah satu penyakit yang berbahaya bagi tanaman padi. Penyakit ini bisa menyerang di setiap fase pertumbuhan. Perhitungan intensitas serangan penyakit blas saat ini masih  dilakukan secara manual. Diperlukan pengembangan teknologi dalam pendugaan intensitas serangan penyakit blas melalui citra NDVI. Penelitian ini bertujuan untuk (1) untuk mendapatkan ketinggian foto udara NDVI terbaik, (2) untuk mendapatkan umur tanaman padi dengan intensitas serangan penyakit blas tertinggi, (3) untuk mendapatkan hubungan antara intensitas serangan penyakit blas dengan nilai NDVI tanaman padi. Penelitian ini menggunakan Drone DJI Phantom 4 dengan lensa NDVI. Pengolahan data menggunakan Web Drone Deploy dan software Arc Gis 10.3. Berdasarkan dari hasil analisis, detail terbaik dari pembesaran 200% mendapatkan akuisisi ketinggian dari citra NDVI adalah 20 meter dengan ukuran piksel 1,4732 cm/pixel. Pertumbuhan intensitas serangan penyakit blas tertinggi  terjadi pada umur 98 hari setelah tanam. Hubungan antara intensitas serangan penyakit blas dengan nilai NDVI memiliki koefisien determinasi sebesar 0,986. Persamaan regresi didapatkan dalam penelitian ini adalah y = -23345x3 + 21191x2- 6416,8x + 665,07 dengan akurasi sebesar sebesar 91,74%.   Blast is one of disease that is dangerous for rice plants. This disease can attack in every phase of growth. Calculation of the intensity of blast disease attacks is still done manually. Technology development is needed in estimating the intensity of blast disease attacks through NDVI imagery. This study purpose (1) to get the best NDVI aerial photo altitude, (2) to get the age of rice plants with the highest attack intensity of blast disease, (3) to get a relationship between the intensity of blast disease and the NDVI value of rice plants. This study use Drone DJI Phantom 4 with lens NDVI. Processing data using Web Drone Deploying and Arc Gis 10.3 software. Based on the analysis results, the best detail of 200% zooming results obtained altitude of the NDVI image acquisition that is 20 m with pixel density of 1,4732 cm/pixel. The highest intensity of blast disease attacks occurs at the age of 98 days after planting. The relationship between the intensity of blast disease and NDVI value has a determination coefficient of 0.986. The regression equation obtained in this study is y = -23345x3 + 21191x2- 6416,8x + 665,07 with an estimated accuracy of 91,74%.

scholarly journals The Effectiveness of Several Plant Extracts to Induce Rice Plant Resistance against Bacterial Leaf Blight - (Xanthomonas oryzae pv. oryzae)

2019 ◽  
Vol 23 (1) ◽  
pp. 16
Author(s):  
Fitri Widiantini ◽  
Avissa Ayuningdiyas ◽  
Endah Yulia ◽  
Tarkus Suganda
Keyword(s):  
Plant Extracts ◽  
Seed Treatment ◽  
Defense Mechanism ◽  
Leaf Blight ◽  
Xanthomonas Oryzae ◽  
Bacterial Leaf Blight ◽  
Rice Seedlings ◽  
Control Techniques ◽  
Rice Plants ◽  
Plant Defense Mechanism

Resistant plants are one of the disease control techniques that considered to be effective. Resistant plants can be produced in various ways including the application of plant extracts. The aim of this study was to examine the ability of several plant extracts to increase the resistance of rice plants to bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae (Xoo). A total of 13 plants were extracted and applied in two methods, which were seed treatment and seedling treatment which sprayed on two-week old rice seedlings. Xoo bacteria were inoculated on rice plants two weeks after planting. The observations on the intensity of BLB disease infection showed that water hyacinth extract (Eichhornia crassippes), spiny amaranth (Amaranthus spinosus) and jasmine leaves (Jasminum grandiflorum) can suppress the development of BLB disease in both application methods. The application of plant extracts as inducing agents needs to be repeated to maintain the activated plant defense mechanism.

scholarly journals Potential of Bacillus subtilis for controlling bacterial leaf blight pathogen in rice

Food Research ◽  
2020 ◽  
Vol 4 (S5) ◽  
pp. 124-130
Author(s):  
K.S. Ku Asmah ◽  
Z. Sapak
Keyword(s):  
Bacillus Subtilis ◽  
Disease Severity ◽  
Severe Disease ◽  
Severity Index ◽  
Leaf Blight ◽  
Bacterial Leaf Blight ◽  
In Vivo Studies ◽  
Disease Severity Index ◽  
Rice Plants

Bacterial leaf blight (BLB) of rice is an economically important disease caused by Xanthomonas oryzae pv. oryzae (Xoo) throughout the world. To control this disease, bacterial isolate of Bacillus subtilis UiTMB1 was screened for the antagonistic activity against the pathogen in vitro and in vivo studies. A bacterial assay and detached leaf technique were used to evaluate the potential of the bacterium against BLB pathogen in the laboratory. Meanwhile, the glasshouse study was conducted to further examine the aptitudes of the isolate on the disease control and growth-promoting of rice plants. The findings revealed that B. subtilis UiTMB1 is able to control the disease and enhance the growth of rice plants. Rice plants treated with B. subtilis UiTMB1 before being inoculated with BLB pathogen showed less severe disease symptoms with low disease severity index of 3.43 compared to rice plants without B. subtilis UiTMB1 with high disease severity index of 8.4. Besides controlling the disease, B. subtilis UiTMB1 was also promoting plant height, chlorophyll content, number of tillers and biomass of rice plants.

scholarly journals PERTUMBUHAN, HASIL DAN TOLERANSI GENOTIP PADI TERHADAP PENYAKIT HAWAR DAUN (Bacterial Leaf Blight) PADA APLIKASI DOSIS Paenibacillus Polymixa BERBEDA

2017 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Ai Komariah ◽  
Eva Lady Mustika
Keyword(s):  
Rainy Season ◽  
Leaf Blight ◽  
Growth Yields ◽  
Bacterial Leaf Blight ◽  
Rice Plants ◽  
Rice Yields ◽  
Main Plot ◽  
Blight Disease ◽  
The Village ◽  
Dose Variation

The research was to study the effect of genotype rice plants and Paenibacillus Polymixa dose to growth, yields and genotype  tolerances to  BLB (Bacterial Leaf Blight) deseases.The research was conducted in the village Kedawung Majalaya Karawang District of West Java in the rainy season, from Januari 2015 until  Mei 2015.  The  experiment was  used Strip plots design with genotypes of rice was the main plot consist of  Sri Putih (v1), Manohara (v2) and  IR 64 (v3), subplots were doses paenybacilus polymixa (d1 ) Dose Paenybacillus polymixa 0 liters / ha, (d2) Dose Paenybacillus polymixa 2.5 liters / ha (5 ml / liter), (d3) Dose Paenybacillus polymixa 5 liters / ha (10 ml / liter) and (d4) Dose Paenybacillus pol ymixa 7.5 liters / ha (15 ml / liter).  The results of the experiment shosed that no interaction between the administration of the dose variation Paenybacillus polymixa with genotype rice plants against rice yields and not interaction between administration of the dose variation Paenybacillus polymixa with genotype rice plants to suppress the intensity of the attack Bacterial leaf blight disease. For the intensity of the disease, dose applications Paenybacillus polymixa 2.5 liters / ha (5 ml / liter) was effectively used during the vegetative age of 21, 28 and 35 days after planting. 

scholarly journals Penggunaan Pestisida Biorasional untuk Pengendalian Penyakit Hawar Daun Bakteri pada Tanaman Padi

2021 ◽  
Vol 2 ◽  
pp. 145-149
Author(s):  
Agus Nurawan ◽  
Yati Haryati ◽  
Kiki Kusyaeri Hamdani
Keyword(s):  
Serratia Marcescens ◽  
Block Design ◽  
Leaf Blight ◽  
Bacterial Leaf Blight ◽  
Bacillus Firmus ◽  
West Java ◽  
Rice Plants ◽  
Randomized Complete Block Design ◽  
Blight Disease

Bacterial leaf blight can cause rice loss between 15-80%. Biorational pesticides can be an alternative to controlling the disease. Bacillus firmus, Burkholderia sp, and Serratia marcescens against bacterial leaf blight on rice plants in the field. The study was conducted in Maret-Juni 2014 in the land of the Independent Farmers Group, Cipeuyeum Village, Haurwangi District, Cianjur Regency, West Java. The design uses a randomized complete block design (RCBD) with 6 treatments and 4 replications. The treatments consist of: 1) Mekongga + biorational, 2) Inpari 14 + biorational, 3) Sintanur + biorasional, 4) Mekongga + without biorational, 5) Inpari 14 + without biorational, and 6) Sintanur + without biorational. The results of the study showed that the application of biorational pesticides can reduce the intensity of bacterial leaf blight disease. Sintanur varieties with the application of biorational pesticides produce higher and higher R / C ratios of 6.81 tons ha-1 and 2.79.

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