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Academic literature on the topic 'Pests of paddy'

Author: Grafiati

Published: 18 May 2024

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Journal articles on the topic "Pests of paddy"

1

Prof. Barry Wiling. "Monitoring of Sona Massori Paddy Crop and its Pests Using Image Processing." International Journal of New Practices in Management and Engineering 6, no. 02 (June 30, 2017): 01–06. http://dx.doi.org/10.17762/ijnpme.v6i02.54.

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Nowadays plant diseases are the major cause of low agriculture yield. So significance of detecting diseases in early stages and treating it will improve the agriculture yield. In India the major agriculture crop is paddy and in central part of south India there is a specific paddy crop called Sona Massori. In our work we concentrated on Sona Masori paddy crop health and pest monitoring using image processing. Here image processing technique is used to observe the image of the leaf and based on the image the diseases are identified using the following process such as image acquisition, pre-processing, segmentation, feature extraction and classification. Mostly diseases are caused by pests, insects and pathogens. In Sona Massori paddy crop 99% of diseases are caused by pests, So detecting pests also plays an important role in improving yield. Here pests are detected by image processing techniques such as Gaussian blur and morphological operations.

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Devie Rosa Anamisa, Budi Dwi Satoto, Muhammad Yusuf, Moch. Kautsar Sophan, and Fifin Ayu Mufarroha. "Application of Fuzzy Inference System Takagi-Sugeno Methods for Diagnosis of Diseases and Pests of Madura Paddy Rice Based on Symptoms." Technium: Romanian Journal of Applied Sciences and Technology 16 (October 29, 2023): 50–56. http://dx.doi.org/10.47577/technium.v16i.9958.

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Diseases and pests of lowland rice are one of the factors that can cause a decrease in rice yields. Therefore, it is necessary to have a diagnostic system to identify diseases and pests of paddy rice from an early age based on damage symptoms. The process of diagnosis requires expertise, knowledge, and experience from experts. Therefore, this research tries to build an expert system that can diagnose diseases and pests of paddy rice early by applying the Fuzzy Inference System Takagi with the Sugeno method. Fuzzy Inference System Takagi forms fuzzy sets using implication functions (rules). Rule composition is obtained from a data set of relationships between regulations, where the affirmation (defuzzification) and input from defuzzification is a constant or linear equation. The Sugeno method is used to diagnose diseases and pests of rice plants based on the symptoms experienced. This research aims to help plant pest control officers diagnose diseases and pests of paddy rice plants from the symptoms that attack the rice. The testing technique used is system accuracy testing and Mean Opinion Score (MOS) testing. The MOS test was carried out by involving 30 respondents consisting of 10 farmers and 20 extension workers, where 4.27 was obtained on a scale of 5 which was categorized into a good system. while testing the accuracy obtained from testing the system on two experts on diseases and pests of Madura paddy rice plants in 30 different cases has resulted in an accuracy rate of 86.66%. The expert system built in this study was able to diagnose 13 diseases and pests of Madura paddy based on the knowledge of two experts on 38 symptoms, and the plan was feasible to use and categorized into a good system.

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Herlinda, Siti, Hendri Candro Nauli Manalu, Rinda Fajrin Aldina, Suwandi Suwandi, Andi Wijaya, Khodijah Khodijah, and Dewi Meidalima. "KELIMPAHAN DAN KEANEKARAGAMAN SPESIES LABA-LABA PREDATOR HAMA PADI RATUN DI SAWAH PASANG SURUT." Jurnal Hama dan Penyakit Tumbuhan Tropika 14, no. 1 (January 5, 2014): 1–7. http://dx.doi.org/10.23960/j.hptt.1141-7.

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ABSTRACTAbundance and Species Diversity of Predatory Spiders for Insect Pests Inhabiting Ratoon Paddy in Tidal Lowland. Ratoon paddy productivity is lower than the main crop. Increasing productivity of the ratoon paddy is to protect the paddy from pests and diseases. This study aimed to analyze the abundance and species diversity of predatory spiders of rice pests on ratoon paddy in tidal lowland. Ratoon paddy field observed was from the main crop that has been harvested and cut 20 cm height. Paddy area observed was 2 ha field planted using Ciherang and Inpara varieties. Spiders inhabiting canopy were sampled using insect nets but soil dwelling spiders were trapped using pitfall traps. The result showed that spider species inhabiting canopy of ratoon paddy were Pardosa pseudoannulata, Lycosa chaperi, Araneus inustus, Cylosa insulana, Atypena adelinae, Erigone bifurca, Erigonidium graminicola, Oxyopes javanus, Argyrodes miniaceus, and Marpisa magister. Spider species found soil dwelling were 11 species, namely Pardosa pseudoannulata, Pardosa sumatrana, Pardosa mackenziei, Pardosa oakleyi, Hogna rizali, Araneus inustus, Cylosa insulana, T. vermiformis, Runcinia albostriata, Coleosoma octomaculatum, and Marpisa magister. Abundance, species number, species diversity for soil dwelling spiders were higher than those for canopy inhabiting spiders. However, the abundance, species number, species diversity for the soil dwelling spiders tended to be higher on the ratoon paddy 3, 4, and 5 week old than those on 1, 2, and 6 week old. From the result, we concluded that abundance, species number, species diversity of spiders found in the ratoon paddy were higher or tended similar to those on the main crop.

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Karthikeyan, K., and P. S. Swathy. "IPM approach against major pests of paddy." Journal of Entomological Research 44, no. 2 (2020): 233. http://dx.doi.org/10.5958/0974-4576.2020.00041.9.

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Juanda, Juanda, Jannus Marpaung, Leonardus Sandy Ade Putra, Fitri Imansyah, and Redi Retiandi Yacoub. "PADDY PAST TRAP SYSTEM BASED ON LONG RANGE COMMUNICATION." Telecommunications, Computers, and Electricals Engineering Journal 1, no. 1 (June 30, 2023): 48. http://dx.doi.org/10.26418/telectrical.v1i1.69895.

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Indonesia is an agricultural country that produces rice plants. The decline in crop yields was caused by pests and had an impact on rice plants which experienced yellowing leaves, broken stems, until the rice fruit became empty. Test results data in the form of numbers in certain units will be presented in the form of tables and graphs. To find out the symptoms or behavior of the system at the time of testing, an analysis is carried out. The research was conducted for 5 nights starting at 18.00 until 06.00 WIB. The LoRa sender will send data when a pest lands on a 1000-1500 VDC wire net. In the research conducted, a total of 97 pests were found. The peak of pest attacks occurs at 19:00 to 20:00 WIB. Walang sangit attacks rice plants in all phases, so it is not surprising that this pest has the largest number, namely 87 pests. The rain that falls makes the lights dim thereby reducing the interest of the pests in the pest traps. Lamps with a wavelength of 500 nm can attract the attention of nocturnal pests that attack rice plants at night.

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Jannah, Atiatul, Yusriadi Marsuni, Samharinto Soedijo, and Samharinto Soedijo. "Keanekaragaman Arthropoda dan Penyakit Tanaman Padi di Desa Kusambi Hilir Kecamatan Lampihong." JURNAL PROTEKSI TANAMAN TROPIKA 6, no. 2 (May 31, 2023): 666–75. http://dx.doi.org/10.20527/jptt.v6i2.1848.

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The purpose of this study was to identify the types of arthropods and diseases in rice plants, especially those in Kusambi Hilir Village, Lampihong District. The method used is a survey method by taking arthropod samples, using insect nets and light traps, observing symptoms of rice plant diseases. The results of the study found that the number of arthropods in paddy fields near the rubber plantations was 219 consisting of 162 individuals (73.97%) pests, 43 individuals (19.63%) predators, 6 individuals (2.73%) parasitoids and 8 individuals ( 3.65%) other arthropods. The number of arthropods in paddy fields near the main road was 159 individuals consisting of 100 individuals (62.89%) pests, 45 individuals (28.30%) predators and 14 individuals (8.81%) parasitoids. The dominant arthropods and diseases in rice are Scirpophaga incertulas Walker and bacterial leaf blight. The diversity index of arthropods is categorized as low because a diversity index of 2.577 is obtained in paddy fields near the main road and (H') is 2.348 in paddy fields near rubber plantations.

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S. K. Nandal, B. K. Beheral, D. Beheral, A. K. Goel, and P. L. Pradhan. "Efficacy of Sprayers Against Pests in Paddy Crop." Journal of Agricultural Engineering (India) 45, no. 4 (December 31, 2008): 9–14. http://dx.doi.org/10.52151/jae2008454.1345.

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An experiment was conducted to study the efficacy of three sprayers, namely spinning disc type low volume sprayer, hand compression sprayer and air assisted power sprayer in controlling some commonly found pests in paddy crop. The spray characteristics revealed that the ratio of VMD to NMD was near to unity (1.06) in case of low volume sprayer followed by 1.33 in hand compression sprayer and 1.39 in power sprayer with a droplet density of 37.67, 25.67 and 21.0 numbers/cm2. The efficacy of the power sprayer in controlling the stem borer (Dead Heart), stem borer (White Ear Head), Leaf Folder Damaged Leaf (LFDL), Whorl Maggot (WM), White Back Plant Hopper (WBPH) and Brown Plant Hopper (BPH) was significantly (P<0.05) higher than low volume sprayer and hand compression sprayer with damage control of 82.90, 59.20, 88.25, 87.85 75.30 and 92.40% respectively. Damage control of Gall Midge (Silver Shoot) did not vary significantly between power sprayer (15.30%) and hand compression sprayer (13.05%). The low volume sprayer and hand compression sprayer were found equally good to control White Ear Head (53.76% and 52.60%) and Whorl Maggot (72.45% and 68.85%). The field capacities of the sprayers were 0.08, 0.1 1 and 0.30 hah in low volume sprayer, hand compression sprayer and power sprayer respectively. The cost of spraying was found to be Rs. 65.00, Rs. 114.00 and Rs. 134.00lha in low volume sprayer, hand compression sprayer and power sprayer respectively.

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Amin, Javeria, Muhammad Almas Anjum, Rida Zahra, Muhammad Imran Sharif, Seifedine Kadry, and Lukas Sevcik. "Pest Localization Using YOLOv5 and Classification Based on Quantum Convolutional Network." Agriculture 13, no. 3 (March 13, 2023): 662. http://dx.doi.org/10.3390/agriculture13030662.

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Pests are always the main source of field damage and severe crop output losses in agriculture. Currently, manually classifying and counting pests is time consuming, and enumeration of population accuracy might be affected by a variety of subjective measures. Additionally, due to pests’ various scales and behaviors, the current pest localization algorithms based on CNN are unsuitable for effective pest management in agriculture. To overcome the existing challenges, in this study, a method is developed for the localization and classification of pests. For localization purposes, the YOLOv5 is trained using the optimal learning hyperparameters which more accurately localize the pest region in plant images with 0.93 F1 scores. After localization, pest images are classified into Paddy with pest/Paddy without pest using the proposed quantum machine learning model, which consists of fifteen layers with two-qubit nodes. The proposed network is trained from scratch with optimal parameters that provide 99.9% classification accuracy. The achieved results are compared to the existing recent methods, which are performed on the same datasets to prove the novelty of the developed model.

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Rofidah, Erna, Siti Arofah, and Indah Trisnawati Dwi Tjahjaningrum. "THE EFFECT OF HABITAT MODIFICATION ON PADDY VARIETY IR 64 FIELD WITH TRAP CROP APPLICATION USING LEMON GRASS (Andropogon nardus ) AND WITHOUT TRAP CROP APPLICATION TOWARDS THE COMPOTITION, ABUNDANCE, AND DIVERSITY OF ARTHROPODS." KnE Life Sciences 2, no. 1 (September 20, 2015): 605. http://dx.doi.org/10.18502/kls.v2i1.226.

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<p>The trap crop technique relies on the attraction of insect pests to plantings other than the main crop. Application using of lemon grass for Habitat modification on paddy field can alter species composition and community structure including Arthropods from insect groups. The lemon grass was planted 20 day before main crop (paddy variety IR 64). This study was conducted in Pasuruan, East Java. Samples were taken using sweep net on vegetative paddy phase, generative paddy phase and ripening paddy phase. Sampling periods from Desember 2012 to March 2013. Each sample was sorted and identified to the family and morphospecies or species. Samples are identified in Zoological laboratory on department of biology, ITS. Study on Arthropoda diversity at different habitats by comparing the species richness is useful for determining ecological indicators at each habitat. The arthropods caught were then classified into some classes: pest (herbivore), natural enemy (parasitoid and predator), and other arthropods. After that, the Species Diversity Index was determined using its Shannon-Wiener Index (H’), Evenness (e), and Species Similarity Index (IS). The compotition of arthropods were classes from herbivore, predator, parasitoid and detritivore. The sum of H’ is higher on paddy field with trap crop application than paddy field without trap crop application. Indicate that a stable relationship could be maintained between rice insect pests and their arthropod natural enemies. </p><p><strong>Keywords</strong> : Habitat modification, Trap crop, Arthropods, compotition, abundance, diversity</p>

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Ainunnisa, I., and H. Haerani. "The identification of pests and diseases of rice plants using sentinel-2 satellite imagery data at the end of the vegetative stage." IOP Conference Series: Earth and Environmental Science 1230, no. 1 (September 1, 2023): 012148. http://dx.doi.org/10.1088/1755-1315/1230/1/012148.

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Abstract One of the factors that affect production yield of cultivation crops, including rice plants, is pest/disease attacks. Various types of pests/diseases are often found in rice cultivation such as rats, stem borers and rice leaf folders. The damage caused by these pests/diseases can lead to production decreases and crop failure. To prevent an increase in pest infestation, monitoring can be carried out by employing remote sensing technologies such as Sentinel 2 satellite imagery. The identification of rice plant pests/diseases can be done using Vegetation Indices such as NDVI and NDRE, due to their sensitivity to plant chlorophyll. The purpose of this study was to identify infected pest and disease of rice plants in paddy fields by using Sentinel-2 satellite imagery. The methods of this study were spatial analysis and simple linear regression analysis, by looking at the relation between Vegetation Indices and rice productivity. The research results showed that based on the low value of NDVI and NDRE at the end of vegetative stage, some of rice fields were infected with pests and diseases. From field observation, it was found that the pests and diseases included rats, rice leaf folders, borers and blasts. Pests/diseases infestation in paddy fields lead to a low Vegetation Index value which results in low rice production. Comparing the NDVI and NDRE, NDRE was better in detecting pests and diseases due to its sensitivity to the plants’ chlorophyll.

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Dissertations / Theses on the topic "Pests of paddy"

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Chakraborty, Kaushik. "Incidence of major insect pests of paddy in relation to climatic conditions and cultural practices : a study at Raiganj, Uttar Dinajpur, West Bengal." Thesis, University of North Bengal, 2009. http://hdl.handle.net/123456789/1413.

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Lin, Ming-Jang, and 林銘璋. "Study on the Control of Pest Snail Pomacea canaliculata in Paddy field by thuringiensin containing fermentation broth from Bacillus thurngiensis." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/5vh5s4.

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碩士
朝陽科技大學
應用化學系碩士班
94
The purpose of the study is to test the thuringiensin (β-exotoxin) from Bacillus thuringiensis for controlling Pest Snail Pomacea canaliculata. Experiments were carried out both in the laboratory and in paddy field. The laboratory test started in 2003, the 29 x 38 cm plastic basins with 10 cm high of soil and 3 cm deep of water were used to imitate paddy field. The compositions of application of thuringiensin containing fermentation broth of Bacillus thuringiensis were 50, 100, 200, 300, 400 ppm with 3 replicates. Paddy field test started in 2005, areas of 3 m2 encircled by plastic board were used for this test. The laboratory test results showed that after using thuringiensin containing fermentation broth of Bacillus thuringiensis, the average death rates of the Ampullarium Canaliculatus were 50% and 100% for the 100 and 200 ppm treatments, respectively. Seven days after transplanting, thuringiensin containing fermentation broth were applied in the test spots. The composition of application of thuringiensin containing fermentation broth were 100 ppm and 200 ppm 3 replicating, in the first and the second rice crop of 2005. The 70% W.P. Niclosamide and tea-seed dregs were used as a chemical controls. The chemical controls that after using 70% W.P. Niclosamide and tea-seed dregs, the average death rates of the Ampullarium Canaliculatus were 100% both treatments after three days, respectively. The results showed that after using thuringiensin containing fermentation broth of Bacillus thuringiensis, the average death rates of the Ampullarium Canaliculatus were 53.3% and 86.7% for the 100 and 200 ppm treatments after seven days, respectively.

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Books on the topic "Pests of paddy"

1

Buddhadev, Manna, and Zoological Survey of India, eds. Studies on nematode parasites associated with paddy crop of West Bengal, India. Kolkata: Zoological Survey of India, 2008.

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K, Pandit Rajat, Brooks Joe E, and United States. Animal and Plant Health Inspection Service., eds. Postharvest grain losses in farm houses in Bangladesh: Rodent population estimates and potential stored paddy losses. [Washington, D.C.?]: U.S. Dept. of Agriculture, Animal and Plant Health Inspection Service, 1994.

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Statistik, Indonesia Badan Pusat, ed. Luas dan intensitas serangan organisme pengganggu tanaman dan bencana alam padi, palawija, dan sayuran di Jawa, 1996 =: Area of paddy, secondary, and vegetables attacked by pests and calamity in Java, 1996. Jakarta, Indonesia: Badan Pusat Statistik, 1998.

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4

Cooper, Jean. My dog Paddy: The story of and abandoned dog. Perth: Jean Cooper, 2002.

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Pest on the run: More humorous short stories from the Paddy Pest chronicles. Bloomington, IN: iUniverse, 2012.

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O'Neill, Peter. Paddy Mullins: The master of Doninga : the authorisedbiography. Edinburgh: Mainstream, 1995.

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Moore, Vivian Miller. Paddy: A ruffed grouse chooses our farm. White River Junction, Vt: White River Press, 2008.

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Burke, Gerry. Pest on the Run: More Humorous Short Stories from the Paddy Pest Chronicles. iUniverse, Incorporated, 2012.

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Pest Takes A Chance: ... And Other Humorous Stories From The Paddy Pest Chronicles. iUniverse, 2011.

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Burke, Gerry. Pest Takes a Chance: ... and Other Humorous Stories from the Paddy Pest Chronicles. iUniverse, Incorporated, 2011.

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Book chapters on the topic "Pests of paddy"

1

Parthasarathy, S., P. Lakshmidevi, P. Yashodha, and C. Gopalakrishnan. "Button Mushroom, Paddy Straw Mushroom and Oyster Mushroom." In Pests and Diseases in Vegetable Crops, 44–55. London: CRC Press, 2024. http://dx.doi.org/10.1201/9781003504153-5.

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Hasan, Md Zahid, Nahid Zeba, Sumaita Binte Shorif, and Morium Akter. "Deep Learning-Based Essential Paddy Pests' Filtration Technique for Economic Damage Management." In Algorithms for Intelligent Systems, 51–65. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6424-0_4.

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Kadota, G., S. Matsumoto, S. Nakamura, R. F. S. Gordon, and J. Hayakawa. "Esprocarb Herbicide Mixtures: Use in Japanese Paddy Rice." In Pest Management in Rice, 389–401. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0775-1_32.

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French, Paul, Hitoshi Matsuyuki, and Hiroshi Ueno. "Paclobutrazol: Control of Lodging in Japanese Paddy Rice." In Pest Management in Rice, 474–85. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0775-1_39.

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Suzuki, K., Y. Shirai, and H. Hirata. "Pyrazosulfuron-Ethyl, a New Sulfonylurea Herbicide for Paddy Rice." In Pest Management in Rice, 338–48. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0775-1_27.

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Rees, R., T. Matsui, and B. Hanisch. "A Novel Use for Benfuresate as a Paddy Rice Herbicide." In Pest Management in Rice, 402–20. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0775-1_33.

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Elakya, R., and T. Manoranjitham. "Pest Classification in Paddy by Using Deep ConvNets and VGG19." In Recent Trends in Computational Intelligence and Its Application, 75–84. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003388913-10.

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Leung, Daren Shi-Chi. "Reviving Community Agrarianism in Post-socialist China." In Beyond Global Food Supply Chains, 69–84. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3155-0_6.

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AbstractTasked with feeding 1.4 billion people, China often promotes its success in food security in relation to its self-sufficient grain production. In the post-socialist context, the reformist state has been pursuing a capital-based vertical model to integrate millions of smallholding producers into the market. Yet, the introduction of high-yield hybrid rice to increase production has resulted in a set of related crises, including widespread environmental pollution, food-safety issues and adverse impacts on rural life. However, agrarian communities are challenging these state-imposed practices of food production. This chapter explores an endogenous form of regenerative agriculture that has emerged in South China since the early 2000s, a Chinese form of food and farming activism for reviving community agrarianism. I argue that the revitalization of “traditional” farming practices as a form of xaingtu (rural) knowledge has evolved with and through local peasants’ experience and struggle over the decades. One example that combines diverse aspects of such knowledge is the “fish-duck-rice paddy”, a well-known symbiotic method of pest control that also works with native varieties, organic manure and cooperative labour. This method revives peasants’ experience of the Mao era as a cultural reference for community agrarianism. The revival of community agrarianism allows farming to be narrated as an evolving social and historical practice, not “wasting” peasants’ knowledge, in contrast to the capitalist agrarian transformation.

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Lingaraj, Vijay Kumar, A. K. Chakravarthy, and Siddanagowda Ujjanagowda Patil. "Impact of Gall Midge, Orseolia Oryzae (Wood-Mason) Infestation on Total Phenols, Proline and Indole Acetic Acid in Paddy (Oryza Sativa Linn.) Genotypes." In New Horizons in Insect Science: Towards Sustainable Pest Management, 261–67. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2089-3_23.

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Sharma, Rahul, and Amar Singh. "Image Pre-Processing and Paddy Pests Detection Using Tensorflow." In Advances in Medical Technologies and Clinical Practice, 131–39. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7188-0.ch010.

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Agriculture is one of the important sources of earning worldwide. With the rapid expansion of the human population and food security for all, the agriculture sector needs to be boosted to increase the yield. Agriculture is the prime source of livelihood in India for more than 50% of the total population. As per Indian agriculture and allied industries industry report, agriculture is one of the major contributors in gross value. Agricultural crops suffer heavy losses due to insect damage and plant diseases. Worldwide, out of the crop losses, major losses are caused by plant pests. In this chapter, various image pre-processing methods and the need of pre-preprocessing are discussed in detail. For image classification, TensorFlow deep neural network is presented. Deep learning model is used for automatic and early detection of paddy pests. Early detection of the pests will aid farmers in adopting necessary preventive measures. Multiple ways to reduce overfitting during model training are also suggested.

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Conference papers on the topic "Pests of paddy"

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Alfarisy, Ahmad Arib, Quan Chen, and Minyi Guo. "Deep learning based classification for paddy pests & diseases recognition." In ICMAI '18: 2018 International Conference on Mathematics and Artificial Intelligence. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3208788.3208795.

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Siregar, Ameilia, and Y. Yurnaliza. "Control of Pests in Saline Paddy of Percut, Northern Sumatera." In Proceedings of the Third Workshop on Multidisciplinary and Its Applications, WMA-3 2019, 11-14 December 2019, Medan, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.11-12-2019.2290811.

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Sandeepanie, W. D. Nilakshi, Samadhi Rathnayake, and Amali Gunasinghe. "Disease Identification and Mapping using CNN in Paddy Fields." In SLIIT International Conference on Advancements in Sciences and Humanities 2023. Faculty of Humanities and Sciences, SLIIT, 2023. http://dx.doi.org/10.54389/nkkj6476.

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Rice, a globally vital staple crop, sustains over half of the world’s caloric needs while supporting the livelihoods of small-scale farmers and landless laborers. The escalating global population has led to an increased demand for rice production. Sri Lanka, renowned for its premium rice quality, has a rich history of paddy cultivation. However, a substantial portion of the country’s 708,000 hectares of paddy land remains underutilized due to water scarcity and unstable terrain. The objective of this project is to enhance paddy crop quality during the critical vegetative phase by employing machine learning and web development for early disease identification. The vegetative phase significantly influences overall yield, resistance to pests and diseases, nutrient assimilation, and environmental sustainability in agriculture. This project primarily focuses on early disease identification during this phase and presents the findings through a user-friendly map interface. Early identification of paddy diseases is vital for effective crop management and high yields. These diseases, caused by various pathogens, can severely impede plant growth and productivity if not promptly detected and treated. Identifying them early enables farmers and experts to take timely, targeted actions such as applying suitable fungicides or implementing cultural practices to control their spread and minimize crop damage. A logical map, displaying disease spread percentages, will gauge the impact of infections on paddy plants. The reliability of this mapping process hinges on model accuracy, which was rigorously validated using multiple metrics to ensure its effectiveness.

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Muzakki, Akmal Sabiq, Isktimal, and Arif Indra Irawan. "Monitoring System for Smart Drones to Remove Bird Pests in Paddy Fields Uses An Internet of Things (IoT)." In 2023 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob). IEEE, 2023. http://dx.doi.org/10.1109/apwimob59963.2023.10365608.

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Agnihotri, Vivek. "Machine Learning based Pest Identification in Paddy Plants." In 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2019. http://dx.doi.org/10.1109/iceca.2019.8822047.

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P, Ananyasreya P., and Subhija E. N. "Paddy Pest Classification Using Deep Learning Based Features." In 2022 Second International Conference on Next Generation Intelligent Systems (ICNGIS). IEEE, 2022. http://dx.doi.org/10.1109/icngis54955.2022.10079825.

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A, Hussain, and Balaji Srikaanth P. "Paddy Crop Pest Identification and Classification Techniques Using Deep Learning." In 2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2023. http://dx.doi.org/10.1109/icses60034.2023.10465565.

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P, Mohanraj, Rajasekar T, Aksha Varshini B, Charumathi V. S, and Dhaarani S. "Pest Identification and Control in Paddy Plants using Ml with an Optimised Activation Function." In 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2023. http://dx.doi.org/10.1109/icaiss58487.2023.10250702.

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Chotikasatian, Chukiat, Watcharapol Chayaprasert, Duangsamorn Suthisut, Siwalak Pathaveerat, and Somnuek Chimruang. "A Preliminary Study of Pest Insect Detection during Paddy Storage in Small-Scale Grain Silos." In 2017 Spokane, Washington July 16 - July 19, 2017. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2017. http://dx.doi.org/10.13031/aim.201700569.

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