Статті в журналах: "Diseases and pests"

1

Raman, K. V. "SURVEY OF DISEASES AND PESTS IN AFRICA: PESTS." Acta Horticulturae, no. 213 (September 1987): 145–50. http://dx.doi.org/10.17660/actahortic.1987.213.15.

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2

Heitefuss, Rudolf. "Wheat Diseases and Pests." Journal of Phytopathology 159, no. 4 (October 5, 2010): 324. http://dx.doi.org/10.1111/j.1439-0434.2010.01750.x.

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3

Muminova, R. "Malus Pests and Diseases." Bulletin of Science and Practice, no. 5 (May 15, 2023): 175–80. http://dx.doi.org/10.33619/2414-2948/90/22.

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The Malus is a deciduous tree of the Rosaceae family, which is actively used in horticulture. In order to maintain healthy, productive trees and fruits, it is necessary to know what pests and control measures exist. The paper presents a review of modern literature on the means and methods of combating diseases and pests of the apple tree. In conclusion, practical conclusions are given about the most effective methods of struggle.

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4

Muminova, Ra`no Dalabaevna. "APPLE PESTS AND DISEASES." Theoretical & Applied Science 120, no. 04 (April 30, 2023): 33–36. http://dx.doi.org/10.15863/tas.2023.04.120.8.

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5

Bukhonova, Yu V., and N. G. Mikhina. "Monitoring pests and diseases of linen." Защита и карантин растений, no. 5 (2022): 25–29. http://dx.doi.org/10.47528/1026-8634_2022_5_25.

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6

Bukhonova, Yu V., and N. G. Mikhina. "Monitoring of legume pests and diseases." Защита и карантин растений, no. 3 (2022): 22–26. http://dx.doi.org/10.47528/1026-8634_2022_3_22.

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7

Heitefuss, Rudolf. "Compendium of Hop Diseases and Pests." Journal of Phytopathology 158, no. 5 (May 2010): 391. http://dx.doi.org/10.1111/j.1439-0434.2009.01617.x.

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8

Heitefuss, Rudolf. "Compendium of Beet Diseases and Pests." Journal of Phytopathology 158, no. 5 (May 2010): 392. http://dx.doi.org/10.1111/j.1439-0434.2009.01626.x.

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9

Kidd, Hamish, and Len Copping. "BCPC Conference 2000 - Pests and Diseases." Pesticide Outlook 12, no. 1 (2001): 36–39. http://dx.doi.org/10.1039/b100807m.

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10

Mikhina, N. G., and Yu V. Bukhonova. "Monitoring of cabbage pests and diseases." Защита и карантин растений, no. 12 (2022): 14–19. http://dx.doi.org/10.47528/1026-8634_2022_12_14.

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11

Bukhonova, Yu V., and N. G. Mikhina. "Monitoring of potato pests and diseases." Защита и карантин растений, no. 11 (2022): 20–24. http://dx.doi.org/10.47528/1026-8634_2022_11_20.

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12

Choi, Won Il, and Young-Seuk Park. "Management of Forest Pests and Diseases." Forests 13, no. 11 (October 27, 2022): 1765. http://dx.doi.org/10.3390/f13111765.

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The occurrence patterns of forest insect pests and diseases have been altered by global events such as climate change. Recent developments in improved monitoring methods and tools for data analyses provide new opportunities to understand the causes and consequences of such changes. Using a variety of management tools, forest pest management programs can mitigate the influence of global changes on forest health. The goal of this Special Issue is to improve our understanding of the root causes of changes that have induced global changes. Fifteen papers are included in this Special Issue, covering several issues in forest pest management. One paper reviews the causes of Korean oak wilt, and another paper discusses fourteen invasive tree pests in Russia. The remaining thirteen papers cover issues related to the monitoring and management of forest pests. These studies provide a better understanding of the causes of change in the patterns of forest pests under the influence of global changes. These reviews also contribute to the development of forest-pest-management strategies to mitigate such impacts on forests due to global changes.

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13

Choi and Park. "Monitoring, Assessment and Management of Forest Insect Pests and Diseases." Forests 10, no. 10 (October 3, 2019): 865. http://dx.doi.org/10.3390/f10100865.

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Forest pests are one of the most important factors disturbing forest ecosystems, by impacting forestry economy, ecosystem services, biodiversity, and sustainable ecosystem management. Monitoring the occurrence of forest pests offers clues to understand their impacts on the forest ecosystem and develop a sustainable ecosystem management strategy. This special issue is designed to create a better understanding of the changes and impacts of forest pests according to forest changes, caused by natural or anthropogenic causes. There are 13 papers published in this special issue, covering several issues concerning forest pests. Two of the papers reviewed the changes in forest pests in Korea or Poland. The remaining twelve papers covered issues concerning the monitoring, assessment, and management of forest pests. Through this special issue, we expect to contribute towards the improvement of our knowledge of the structures and processes in forest ecosystems relating to forest pests and fundamental information for the effective management of forest pests.

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14

Luo, She Zhou, and Cheng Wang. "Forest Pests and Diseases Forecasting Based on GIS." Advanced Materials Research 250-253 (May 2011): 2945–48. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.2945.

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Geographic Information System (GIS) has been widely applied to the field of pest management, which provides the new ways and methods for integrated pest research, prevention and control. The main purpose of this study is to forecast and manage forest pests and diseases. For this purpose, I developed the forest pests diseases forecast system, by using ArcObjects (AO) and Visual Basic as the secondary development platform. The system is able to synthetically analyze and judge relevant data, such as weather forecast and tree species, according to the occurrence laws of the forest pests and diseases and the characteristics of biology. The system uses Markov chain and other methods to forecast the occurrence period, amount, scope and the degree of harm of pests and diseases. To validate the reliability of Markov chain model, the pests and diseases data of Liu'an City of Anhui Province, in China from 1975 to 2001, to be applied. The results show that the method used is reliable. The occurrence area and location of forest pests and diseases can be labelled and displayed on the electronic map with three-dimension.

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15

Windi, Windi Tamara, Novriyenni, and Husnul Khair. "Application of Case Based Reasoning Method to Diagnose Rice Plant Diseases." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 3, no. 1 (October 6, 2023): 498–503. http://dx.doi.org/10.59934/jaiea.v3i1.372.

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Rice (Latin: Oryza sativa) is one of the most important cultivated crops in civilization. Although it mainly refers to a type of cultivated plant, rice is also used to refer to several types of the same genus (genus), commonly referred to as wild rice. The problem that often arises is that many rice plants are susceptible to pests and diseases during the planting period. Some pests and diseases that can attack rice plants include: leaf blight, grass, tongguo, rice spout, and dwarf grass. Generally, when rice plants are attacked by pests and diseases, farmers will immediately use pesticides or treatment methods that are sometimes not in accordance with pests. As a result, treatment is not optimal and can even cause new pests and diseases. The purpose of this study is to assist farmers in identifying early symptoms of plant diseases and pests of rice plant diseases using the case base reasoning method, so that the treatment of plant diseases and insect pests is more concentrated and maximal.

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16

Zheng, Qiong, Wenjiang Huang, Qing Xia, Yingying Dong, Huichun Ye, Hao Jiang, Shuisen Chen, and Shanyu Huang. "Remote Sensing Monitoring of Rice Diseases and Pests from Different Data Sources: A Review." Agronomy 13, no. 7 (July 13, 2023): 1851. http://dx.doi.org/10.3390/agronomy13071851.

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Rice is an important food crop in China, and diseases and pests are the main factors threatening its safety, ecology, and efficient production. The development of remote sensing technology provides an important means for non-destructive and rapid monitoring of diseases and pests that threaten rice crops. This paper aims to provide insights into current and future trends in remote sensing for rice crop monitoring. First, we expound the mechanism of remote sensing monitoring of rice diseases and pests and introduce the applications of different commonly data sources (hyperspectral data, multispectral data, thermal infrared data, fluorescence, and multi-source data fusion) in remote sensing monitoring of rice diseases and pests. Secondly, we summarize current methods for monitoring rice diseases and pests, including statistical discriminant type, machine learning, and deep learning algorithm. Finally, we provide a general framework to facilitate the monitoring of rice diseases or pests, which provides ideas and technical guidance for remote sensing monitoring of unknown diseases and pests, and we point out the challenges and future development directions of rice disease and pest remote sensing monitoring. This work provides new ideas and references for the subsequent monitoring of rice diseases and pests using remote sensing.

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17

Phophi, Mutondwa M., and Paramu L. Mafongoya. "Constraints to Vegetable Production Resulting from Pest and Diseases Induced by Climate Change and Globalization: A Review." Journal of Agricultural Science 9, no. 10 (September 13, 2017): 11. http://dx.doi.org/10.5539/jas.v9n10p11.

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Vegetable production worldwide is constrained by pests and diseases which effects are exacerbated by climate change and variability. Greenhouse gas emissions are also increasing due to poor agricultural practices and other human activities. This will continue to have a negative impact on the prevalence of insect pests and diseases. This review focuses on the climatic factors that impact on insect pests and diseases of vegetable crops. High atmospheric temperatures and elevated carbon dioxide increases pest development, survival of pests and distribution of pest to new areas. The distribution of insect pests and diseases are not due to climate changes only but are also a result of globalisation and poor biosecurity measures at country borders. There is limited information on the distribution of pests and diseases due to globalisation in African countries. New exotic pests will continue to be introduced to countries if biosecurity measures are not improved. Future research must focus on how to manage emerging pests and diseases influenced by high temperatures and carbon dioxide and other climatic conditions which influence pest severity under smallholder farmers in the southern African regions.

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18

Visutsak, Porawat. "Ontology-Based Semantic Retrieval for Durian Pests and Diseases Control System." International Journal of Machine Learning and Computing 11, no. 1 (January 2021): 92–97. http://dx.doi.org/10.18178/ijmlc.2021.11.1.1019.

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In Southeast Asia, durian is affectionately called the king of fruit. Durian is the most popular crop planted in eastern and southern of Thailand. The total crop is around 600,000 tons per year; among this, 500,000 tons of the total production were exported worldwide. In Thailand, the knowledge of durian production is based on experience from generation to generation, especially the knowledge of durian pests and diseases control. This paper presents the ontology knowledge based for durian pests and diseases retrieval system. The major contributions of the system consist of 1) the stored knowledge of durian pests and diseases and 2) the diagnosis of durian diseases and the suggestions for the treatments. The ontology knowledge consists of 8 main classes: 1) diseases, 2) pests, 3) cultivars, 4) symptoms of bunch, 5) leaf area symptoms, 6) symptoms of the branches and trunk, 7) symptoms of fruit, and 8) symptoms of root and growth. The experimental results yielded 100% of precision, 88.33% of recall, and 93.8% of overall performance.

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19

Cao, Yiran. "Detection and classification of pests and diseases in rice leaf images based on deep learning algorithms." Applied and Computational Engineering 74, no. 1 (July 11, 2024): 219–24. http://dx.doi.org/10.54254/2755-2721/74/20240477.

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Rice is one of the important food crops worldwide, but it is susceptible to various pests and diseases during its growth process, leading to yield reduction and even death. Therefore, it is very important to detect and categorize rice pests and diseases in a timely and accurate manner. In this paper, we use the dataset from Kaggle public database, which is divided into two categories of images: "normal leaves" and "infested by pests and diseases", and configure AlexNet, Vgg and MobileNetV2 models based on Pytorch framework to detect and classify rice pests and diseases in a timely and accurate manner. MobileNetV2 model was configured based on Pytorch framework to detect and classify pests and diseases in rice leaf images. Through the changes of the loss and Accuracy curves of AlexNet, Vgg and MobileNetV2 models, we found that all three deep learning models have good training effect and can well predict whether the rice leaf images are infested by pests and diseases. The final results show that the prediction accuracy of all three sets of deep learning models reaches more than 97%, and they can detect pests and diseases on rice leaf images very accurately. This means that we can use these models to quickly and accurately detect and categorize rice pests and diseases, so that timely measures can be taken to prevent the spread of pests and diseases and improve the yield and quality of rice.

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20

Zhang, Yin’e, and Yong Ping Liu. "Identification of Navel Orange Diseases and Pests Based on the Fusion of DenseNet and Self-Attention Mechanism." Computational Intelligence and Neuroscience 2021 (September 2, 2021): 1–12. http://dx.doi.org/10.1155/2021/5436729.

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The prevention and control of navel orange pests and diseases is an important measure to ensure the yield of navel oranges. Aiming at the problems of slow speed, strong subjectivity, high requirements for professional knowledge required, and high identification costs in the identification methods of navel orange pests and diseases, this paper proposes a method based on DenseNet and attention. The power mechanism fusion (DCPSNET) identification method of navel orange diseases and pests improves the traditional deep dense network DenseNet model to realize accurate and efficient identification of navel orange diseases and pests. Due to the difficulty in collecting data of navel orange pests and diseases, this article uses image enhancement technology to expand. The experimental results show that, in the case of small samples, compared with the traditional model, the DCPSNET model can accurately identify different types of navel orange diseases and pests images and the accuracy of identifying six types of navel orange diseases and pests on the test set is as high as 96.90%. The method proposed in this paper has high recognition accuracy, realizes the intelligent recognition of navel orange diseases and pests, and also provides a way for high-precision recognition of small sample data sets.

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21

Zubkova, Tatyana, Anastasia Baryshnikova, Dmitry Vinogradov, Tatyana Yuryevna Dubrovina, Ivan Lebedev, and Guladi Gogmachadze. "Analysis of diseases, pests and qualitative parameters of various varieties of lettuce grown under hydroponic conditions." АгроЭкоИнфо 3, no. 63 (June 30, 2024): 30. http://dx.doi.org/10.51419/202143330.

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In greenhouses of protected soil, with high humidity, low ventilation of premises in autumn and winter, and elevated temperatures in summer, optimal conditions are created for the spread of many diseases and pests of salad crops. Salad crops are exposed to fungal, bacterial and viral diseases. In order to quickly cope with problems arising from pests and diseases, it is necessary to know and understand the signs of each of them. The manifestation of diseases and pests can affect the quality of finished products. The purpose of the study is to assess diseases, pests and qualitative parameters of various varieties of lettuce grown in hydroponics conditions. Keywords: LETTUCE, VARIETY, DISEASES, PESTS, QUALITY

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22

Nguru, Wilson, and Caroline Mwongera. "Predicting the future climate-related prevalence and distribution of crop pests and diseases affecting major food crops in Zambia." PLOS Climate 2, no. 1 (January 9, 2023): e0000064. http://dx.doi.org/10.1371/journal.pclm.0000064.

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Environmental factors determine the suitability of natural habitats for crop pests and often facilitate their proliferation and that of the crop diseases they carry. Crop pests and diseases damage food crops, significantly reducing yields for these commodities and threatening food security in developing, predominantly agricultural economies. Given its impact on environmental factors, climate change is an important determinant of crop pest and disease distribution. This study uses Targeting Tools, a climate suitability analysis and mapping toolkit, to explore the potential impact of climate change on select environmental factors linked to crop pest and associated diseases’ proliferation. Based on the existing literature, prediction modeling was performed on 21 key pests and diseases that impact the major food crops for Zambian consumption. Future changes in habitat suitability for these crop pests and diseases were mapped based on their optimal temperature and relative humidity conditions for proliferation. Results project that there will be an overall increased geographical spread of suitable habitats for crop pests (and as follows, crop diseases) that thrive in warmer environments. By the 2030s, crop pests and diseases will increasingly spread across Zambia, with a higher likelihood of occurrence projected under RCPs 2.6, 4.5, and 8.5. Crop pests and diseases that thrive in cooler environments will experience decreasing habitat suitability in the 2030s, but will transition to a slower decrease in the 2050s under RCPs 2.6 and 4.5. Overall crop pest and disease habitat suitability will continue to rise slowly in the 2050s; RCP 8.5 shows an increased habitat suitability for crop pests and diseases that thrive in warm environments, with a decreased likelihood of occurrence for crop pests and diseases that thrive in cooler environments. The results highlight the need for future-facing, long-term climate adaptation and mitigation measures that create less suitable microclimates for crop pests and diseases.

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23

Yin, Helin, Yeong Hyeon Gu, Chang-Jin Park, Jong-Han Park, and Seong Joon Yoo. "Transfer Learning-Based Search Model for Hot Pepper Diseases and Pests." Agriculture 10, no. 10 (September 28, 2020): 439. http://dx.doi.org/10.3390/agriculture10100439.

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The use of conventional classification techniques to recognize diseases and pests can lead to an incorrect judgment on whether crops are diseased or not. Additionally, hot pepper diseases, such as “anthracnose” and “bacterial spot” can be erroneously judged, leading to incorrect disease recognition. To address these issues, multi-recognition methods, such as Google Cloud Vision, suggest multiple disease candidates and allow the user to make the final decision. Similarity-based image search techniques, along with multi-recognition, can also be used for this purpose. Content-based image retrieval techniques have been used in several conventional similarity-based image searches, using descriptors to extract features such as the image color and edge. In this study, we use eight pre-trained deep learning models (VGG16, VGG19, Resnet 50, etc.) to extract the deep features from images. We conducted experiments using 28,011 image data of 34 types of hot pepper diseases and pests. The search results for diseases and pests were similar to query images with deep features using the k-nearest neighbor method. In top-1 to top-5, when using the deep features based on the Resnet 50 model, we achieved recognition accuracies of approximately 88.38–93.88% for diseases and approximately 95.38–98.42% for pests. When using the deep features extracted from the VGG16 and VGG19 models, we recorded the second and third highest performances, respectively. In the top-10 results, when using the deep features extracted from the Resnet 50 model, we achieved accuracies of 85.6 and 93.62% for diseases and pests, respectively. As a result of performance comparison between the proposed method and the simple convolutional neural network (CNN) model, the proposed method recorded 8.62% higher accuracy in diseases and 14.86% higher in pests than the CNN classification model.

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24

Situmorang, Lamhot, and Fristi Riandari. "Expert System Mediagnosa Hama On Phon Oil With Certainty Factor Method." Journal Of Computer Networks, Architecture and High Performance Computing 2, no. 2 (June 1, 2020): 268–74. http://dx.doi.org/10.47709/cnapc.v2i2.416.

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The process of palm oil culture is influenced by various factors, one of which is the pest and disease factors. Generally the problem of farmers differentiating pests and diseases, this is dyed most of the farmers lack information and rely on the experience of other farmers to overcome the existing pest and disease problems. In handling pests and diseases, it is necessary to have a farmer consilant who is able to diagnose pests and diseases on oil palm trees. In this study, an expert system for diagnosing pests and diseases in palm tree plants, as well as providing various solutions for pests or diseases. The method used in this expert system is the Certainty Fators method. Certainty Method The factors was chosen because this method is suitable in the process of determining the identification of pests and diseases and the result of this application is the percentage of the system. The percentage is influenced by the CF value obtained from the system, the percentage of expert system consultations is taken from the highest yield as an alternative to other pests or diseases that attack oil palm tree crops.

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25

Kunz, Sidney E. "Integrated pest management of dipteran pests in the New World." International Journal for Parasitology 17, no. 2 (February 1987): 659–64. http://dx.doi.org/10.1016/0020-7519(87)90143-3.

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26

Mbagho, Alberta, Meliana O. Meo, and Gregorius Rinduh Iriane. "Sistem Pakar Diagnosa Hama Penyakit Tanaman Tomat Menggunakan Metode Forward Chaining." JURNAL SAINS DAN KOMPUTER 7, no. 01 (January 30, 2023): 25–30. http://dx.doi.org/10.61179/jurnalinfact.v7i01.383.

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The tomato (Solanum lyco persicum) is a plant from the solanceae family, native to Central and South America, from Mexico and Peru. Tomatoes have a short life cycle and height from I to 3 meters. Currently, farmers often ignore pests and diseases of tomatoes due to lack of knowledge. They also assessed that it finally happened at the time of planting, experts on pests and diseases of tomatoes were eliminated, there was a lack of socialization from agricultural officials about pests and diseases in tomatoes, but they did not know how to control them and to eliminate diseases quickly or decrease productivity. This study uses the Forward Chaining method, which is a description that starts from known facts and then is matched with IF and IF-THEN rules. Pests and diseases with a high prevalence in tomatoes are pests. Some pests are: fruit caterpillars, earthworms, green aphids, white flies, fruit flies (bractrotera) and further diseases namely: Fusarium wilt, leaf spot disease, bacterial spots, fruit rot. This expert system application provides information on tomato diseases and disease diagnosis, including control solutions that can be used to reduce the risk of damage to tomato plants. This study aims to build an expert system application that can diagnose tomato plant pests and diseases using the forward chaining method. This application is expected to help the community in diagnosing the types of tomato plant pests. The implementation of the application of an expert system for pests and diseases of tomato plants is expected to provide easy access for users and the wider community, through the use of web-based media.

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Nurhasan, H. L. Susilawati, and Supriatna. "The dynamic of pests and plant diseases during three consecutive rice growing seasons." IOP Conference Series: Earth and Environmental Science 1039, no. 1 (September 1, 2022): 012030. http://dx.doi.org/10.1088/1755-1315/1039/1/012030.

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Abstract Pests and diseases are significant factors that affecting global rice production. There is a need that pests and diseases have continuously been controlled, in order to solve the pest and disease problem. The aim of this study was to observe the population dynamics of pests and diseases infestation in lowland rice field during different cropping seasons. The data of pest and disease infestation in Pati District, Central Java Province, Indonesia during the Rainy Season (RS) 2018/2019, the Dry Season (DS) 2019, and the RS 2019/2020 were observed and analyzed. The results showed that the rice fields in Pati were susceptible to stem borer, brown plant hopper, rats, fake white pests, blast and bacterial blight during three consecutive seasons. Tungro was not found. During both the RS and DS, the areas of rice paddy in Pati approximately 470 ha season−1 were affected by stem borer. The second largest damage rice area approximately 221 ha season−1 was affected by blast. Grain loses due to pests and diseases infestation during the RS was higher than during the DS. Micro-climate significantly affected pests and plant diseases. The dynamic of pests and plant disease infestation provide information early warning for high-risk areas of rice production and for pests-diseases management.

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28

Rusli, Mulyadi, and Noni Sulanti. "SISTEM INFORMASI MENDETEKSI HAMA DAN PENYAKIT TANAMAN KOL MELALUI SISTEM PAKAR DENGAN METODE FORWARD CHAINING STUDI KASUS : BALAI PENYULUHAN PERTANIAN KECAMATAN JANGKAT." JURNAL AKADEMIKA 14, no. 1 (November 24, 2021): 15–21. http://dx.doi.org/10.53564/akademika.v14i1.717.

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Анотація:

In the world of agriculture, there are many problems that prevent farmers from cultivating this group of crops, causing crop failure. The problem that is often faced is that pests and diseases become serious problems that cannot be handled properly so that plants die or do not grow properly, and result in crop failure and big losses. The purpose of the study was to build an Expert System to Detect Pests and Diseases of Cabbage Using Forward Chaining Methods at the Agricultural Extension Center, Jangkat District, a system that can replace the temporary role of experts in identifying pests and diseases of cabbage or cabbage plants accurately and quickly. An expert system for diagnosing pests and plant diseases are urgently needed to serve as a means for consultation and learning facilities for farmers, especially from Extension Centers. For this reason, the complexity and difficulties experienced by farmers or can be overcome by providing a software (expert system) in the form of an application program to determine pests and diseases that attack cabbage or cabbage plants and how to handle and prevent them appropriately. The advantage of using an expert system application using web programming is that it makes it easier for farmers to determine pests and diseases and so that there are no errors in giving conclusions about pests and diseases, which is expected to help and facilitate farmers in determining pests and diseases that attack plants.

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29

Gonda, István, Imre Holb, and Klára Bitskey. "Previous data on the relationship between the intensity of pruning and the degree of damage in integrated and organic applegrowing systems." Acta Agraria Debreceniensis, no. 1 (May 27, 2001): 47–52. http://dx.doi.org/10.34101/actaagrar/1/3585.

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In Hungary, fruit growers are increasingly interested in environmentally friendly growing methods, such as organic and integrated systems. Vital is the establishment of a strengthened system of cultivar-pruning-plant protection in production technology. Consequently, our aim was to examine the susceptibility of apple cultivars to diseases and pests and the effect of pruning technique on diseases and pests in organic and integrated growing systems.Two pathogens (Venturia inaequalis, Podosphaera leucotricha) and two pests (Leucoptera malifoliella, Pannonychus ulmi) were observed in organic and integrated systems under „strong” and „weak” pruning techniques. Our results on six cultivars showed that the pathogens and pests infested the trees more in the organic system, as compared to that of integrated production. The pruning technique affected mainly the susceptiblecultivars to diseases and pests. The „weak” pruning technique caused a higher level of diseases and pests infestations than the „strong” pruning technique, especially in the organic growing system. The likely reason is that the shoots grow fast and powerfully under “strong” pruning technique. This supports better preservation of the trees supported by susceptibility of plant tissues to diseases and pests.

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30

Okonya, Joshua, Walter Ocimati, Anastase Nduwayezu, Déo Kantungeko, Nicolas Niko, Guy Blomme, James Legg, and Jürgen Kroschel. "Farmer Reported Pest and Disease Impacts on Root, Tuber, and Banana Crops and Livelihoods in Rwanda and Burundi." Sustainability 11, no. 6 (March 15, 2019): 1592. http://dx.doi.org/10.3390/su11061592.

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Biotic constraints cause major crop losses and, hence, food insecurity in sub-Saharan Africa. This study documented the popularity, production constraints, pests and diseases, farmers’ perceptions on the severity of biotic constraints and the impact of related crop losses on household food security for the key root, tuber and banana (RTB) crops (cassava, potato, sweetpotato and banana). Farmer interviews were conducted in 2014 covering 811 households in Rwanda and Burundi. Farmers were asked to list their RTB crop production constraints, name insect pests and diseases of RTB crops, estimate crop loss due to pests and diseases, and mention if their household experienced any form of food insecurity due to pests and diseases. Cutworms and late blight in potato, banana weevils and banana Xanthomonas wilt in banana, cassava whitefly and cassava mosaic disease in cassava, sweetpotato weevils, and sweetpotato virus disease in sweetpotato were the most predominant pests and diseases reported. Crop losses due to pests and diseases for sweetpotato, banana, potato and cassava were estimated at 26%, 29%, 33%, and 36%, respectively, in Rwanda and 37%, 48%, 38%, and 37% in Burundi. Pests and diseases reduce the profitability of RTB crops, threaten food security, and constitute a disincentive for investment. Sustainable and affordable integrated pest management packages need to be developed.

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31

Falloon, R. E. "DISEASES AND PESTS OF GRASS SEED CROPS." NZGA: Research and Practice Series 5 (January 1, 1990): 25–27. http://dx.doi.org/10.33584/rps.5.1998.3340.

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This paper will discuss the diseases and pests that affect grass seed production. In order to put the diseases and pests into perspective, the principlesof grass seed production will be considered. The components of yield of any crop for which seed is the product are: number of plants per unit area; number of inflorescences per plant; number of seeds per inflorescence; seed weight, Many factors can influence these components, for example: (1) crop establishment (cultivation, seed quality, seeding rate, sowing time, soil moisture and fertility can all affect numbers of plants) (2) crop growth (soil moisture, fertility, grazing and weeds can affect crop growth and influence numbers of inflorescences and numbers and weight of seeds).

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32

Miller, S. A., N. Patel, and C. J. Stanley. "CRANBERRY PESTS AND DISEASES IN NEW ZEALAND." Acta Horticulturae, no. 715 (August 2006): 509–12. http://dx.doi.org/10.17660/actahortic.2006.715.78.

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33

Mikhina, N. G., and Yu V. Bukhonova. "Monitoring pests and diseases of sugar beet." Защита и карантин растений, no. 10 (2022): 21–26. http://dx.doi.org/10.47528/1026-8634_2022_10_21.

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34

Bukhonova, Yu V., and N. G. Mikhina. "Monitoring of pests and diseases of corn." Защита и карантин растений, no. 1 (2022): 19–22. http://dx.doi.org/10.47528/1026-8634_2022_1_19.

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35

Delserone, Leslie M. "Review ofCompendium of Beet Diseases and Pests." Journal of Agricultural & Food Information 11, no. 1 (January 21, 2010): 57–58. http://dx.doi.org/10.1080/10496500903436417.

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36

Heathcote, G. D. "Atlas of diseases and pests in beet." Agriculture, Ecosystems & Environment 24, no. 4 (December 1988): 459–60. http://dx.doi.org/10.1016/0167-8809(88)90125-9.

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37

Royle, D. J., and M. Hubbes. "Diseases and pests in energy crop plantations." Biomass and Bioenergy 2, no. 1-6 (January 1992): 45–54. http://dx.doi.org/10.1016/0961-9534(92)90087-7.

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38

Maas, J. L. "STRAWBERRY DISEASES AND PESTS - PROGRESS AND PROBLEMS." Acta Horticulturae, no. 1049 (August 2014): 133–42. http://dx.doi.org/10.17660/actahortic.2014.1049.11.

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39

Bukhonova, Yu V., and N. G. Mikhina. "Monitoring of pests and diseases for sunflower." Защита и карантин растений, no. 1 (2023): 19–22. http://dx.doi.org/10.47528/1026-8634_2023_1_19.

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40

U, JAWAHARA RAJU, and SIVAPRAKASAM K. "SURVEY ON PESTS AND DISEASES OF CABBAGE." Madras Agricultural Journal 76, April (1989): 192–96. http://dx.doi.org/10.29321/maj.10.a02046.

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Survey on cabbage in 40 villages in the Nilgiris district of Tamil Nadu revealed the severity of the diamond back moth. Plutella xylestella, the cutworm, Agrotis ipsilon the semilooper, Trichoplusia ni, the aphid, Lipaphis erysimi, the club root, Plasmodiophora brassicae, the black rot, Xanthomonas campestris pv. campestris, and the white rot, Sclerotinia sclerotiorum and their importance as key pests and diseases. The larval parasitoid Apanteles plutellae on diamond backmoth and the predatory coccinellid beetle, Menochilus sexmaculatus on the aphid were the predominant bicontrol agents in the cabbage ecosystem in the Nilgiris district of Tamil Nadu.

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41

Andrews, Brian. "Pests and Diseases of Plants – Graeme Ambrose." Ballarat Naturalist (2000:Oct) (October 2000): 2–3. http://dx.doi.org/10.5962/p.384577.

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42

Resti, Yulia, Desi Herlina Saraswati, Des Alwine Zayanti, and Ning Eliyati. "CLASSIFICATION OF DISEASES AND PESTS OF MAIZE USING MULTINOMIAL LOGISTIC REGRESSION BASED ON RESAMPLING TECHNIQUE OF K-FOLD CROSS-VALIDATION." Indonesian Journal of Engineering and Science 3, no. 3 (November 1, 2022): 069–76. http://dx.doi.org/10.51630/ijes.v3i3.83.

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Some of the obstacles in the cultivation of maize that cause low productivity of maize yields are diseases and pests. Early detection of maize diseases and pests is expected to reduce farmer losses. A system for the early detection of diseases and pests can be created by classifying them based on digital images. This study aimed to classify maize diseases and pests using multinomial logistic regression. The model and testing resampling were based on resampling technique of k-fold cross-validation. The research data was obtained from the RGB color feature extraction process for each object in each class of diseases and pests of corn. The results showed that the classification into seven classes using five folds had an accuracy rate of 99.85%, macro precision of 98.59%, and macro recall of 98.15%.

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43

Bell, J. N. B., S. McNeill, G. Houlden, V. C. Brown, and P. J. Mansfield. "Atmospheric change: effect on plant pests and diseases." Parasitology 106, S1 (January 1993): S11—S24. http://dx.doi.org/10.1017/s003118200008608x.

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SUMMARYThe atmosphere plays a key role in plant disease, but only recently has it become understood that atmospheric pollutants can influence the response of plants to attack by pests and pathogens. This paper reviews the evidence for this phenomenon, considering impacts of sulphur dioxide, nitrogen dioxide and ozone, mainly on fungal pathogens and aphid pests. Field observations in polluted areas have indicated changes in abundance of pests and pathogens and in some cases a causal link has been demonstrated in controlled experiments. A major study is described in which consistent marked positive impacts of SO2 and NO2 have been shown on a range of British agricultural aphid pests, using four different approaches: fumigations, nitration studies, exposure along air pollution gradients and a nation-wide field survey. Ozone, in contrast, produces a more complex range of responses. These effects are apparently mediated via chemical changes in the plant. Fungal pathogens show both positive and negative responses to air pollutants. A study is described in which these opposite responses in two different fungal species were observed in a field SO2–fumigation system and confirmed in controlled laboratory fumigations. Models are presented to describe the complex pathways by which air pollutants could influence host plant performance via impacts on pests and pathogens.

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44

Li, Jinyang, Qingdao Huang, and Bing Liu. "An SI integrated pest management model with pesticide resistance to susceptible pests." International Journal of Biomathematics 13, no. 05 (May 28, 2020): 2050037. http://dx.doi.org/10.1142/s1793524520500370.

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In this paper, epidemic diseases among pests are assumed to occur, so pests are divided into susceptible pests and infected pests, and only susceptible pests are harmful to crops. Considering spraying pesticides and releasing of natural enemies and infected pests to control pests, as well as the long-term application of the same pesticide to induce resistance, an integrated pest management with pesticide resistance is established. The pollution emission model is introduced to model the action process of pesticides, which well reflects its residual and delay effects. By using comparison theorem of impulsive differential equation and analysis method, the threshold condition for eradication of susceptible pests is obtained. Then we analyze the frequency of spraying pesticide on the success of pests control. It shows that it is not that the more frequently pesticides are applied, the better the result of the susceptible pests control is. From the sensitivity analysis, the key factors on the threshold are obtained. Finally, the strategies to control susceptible pests are given, including switching pesticides and releasing infected pests and natural enemies elastically.

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45

Nur, Yohani Setiya Rafika, Auliya Burhanuddin, Dasril Aldo, and Widya Lelisa Army. "Sistem Pakar Deteksi Penyakit Bawang Merah dengan Metode Case Based Reasoning." JURNAL MEDIA INFORMATIKA BUDIDARMA 6, no. 3 (July 25, 2022): 1356. http://dx.doi.org/10.30865/mib.v6i3.4180.

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Shallots are tubers commonly consumed by Indonesians. Shallots are one of the three members of the Allium genus that are much-loved and have high economic value. In the process of cultivating shallots susceptible to pests and diseases. Onion caterpillars, leaf flies, earthworms, purpura, fusarium wilt, onion mosaic and leaf spot are some of the pests and diseases that often attack shallot plants. Farmers will immediately give pesticides or methods that are sometimes not suitable for pests and diseases that attack. As a result, maintenance is not optimal and new pests or diseases often arise. This study aims to help farmers find early symptoms of shallot pests and diseases, so that pest and disease control is more optimal and on target. Processed as many as 10 attack data using Case Based Reasoning method. This method will process data in the form of symptoms seen in shallots, so that they can detect types of pests and diseases of shallots and their handling steps with 100% accuracy. Therefore, this method is relevant for the identification of shallot disease

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46

Nindhy Prastiwi, Maulidina, Uky Uky Yudatama, and Nugroho Agung Prabowo. "Sistem Pakar Diagnosis Hama dan Penyakit pada Tanaman Bunga Sedap Malam dengan Dempster Shafer." Jurnal Komtika (Komputasi dan Informatika) 3, no. 2 (April 26, 2020): 40–45. http://dx.doi.org/10.31603/komtika.v3i2.3470.

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Nightly flower plants are one of the flower plants that are much in demand by the public. However, as time goes by the production of savory flower plants determines which one of the causes is caused by pests and diseases. Introduction of pests and diseases and its control sometimes not all farmers know it. This research develops an expert system that can help farmers diagnose pests and diseases that attack night flowering plants with the Dempster Shafer method. The results of this study are the application of an expert system that uses pests and tuberose flower diseases. This system will issue this edition to the publication of night flower pests and diseases inputted by users. The amount of this trust value is the result of calculations using the Dempster Shafer method. The conclusion in this study is that an expert system using the Dempster Shafer method for approval to release pests and diseases of the nightly flower plants is very helpful in overcoming the problem of improving the quality of the nightly flower production.

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47

Jańczak, C., S. Pruszyński, and P. Bubniewicz. "Winter wheat protection against diseases and pests in conventional programme of crop protection and in integrated pest management." Plant Protection Science 38, SI 1 - 6th Conf EFPP 2002 (January 1, 2002): 221–26. http://dx.doi.org/10.17221/10359-pps.

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Results of researches carried out in 2000 and 2001 have demonstrated, that main factors determining yield of winter<br />wheat are: agrotechnical measures, mainly proper choice of field, optimal nitrogen fertilization as well as choice of<br />cultivar well adapted to local climatic conditions. Chemical protection of winter wheat affects first of all stability of<br />yield. Regular inspections of fields with special account to present phytosanitary situation, thresholds of noxiousness and<br />expected development of disease and pest populations should decide on the need of chemical treatments.

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48

Zhou, Leyun, and Yanhua Li. "Problems and Measures in the Prevention and Cntrol of Crop Diseases and Insect Pests." 城市建设理论研究—园林景观 5, no. 1 (2020): 13–15. http://dx.doi.org/10.26789/yljg.2020.01.005.

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Based on the characteristics and current situation of crop diseases and insect pests, this paper analyzes the problems of farmers’ lack of awareness of prevention and control, blind introduction of quarantine pests that lead to the spread of quarantine pests, and lack of advanced pest control technology in the prevention and control of crop diseases and pests. , For reference and reference.

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Frandian, Beni, Ilka Zufria, and Muhammad Dedi Irawan. "Implementasi Certainty Factor Untuk Diagnosis Penyakit dan Hama Pada Pelepah dan Daun Kelapa Sawit Beserta Penanganannya." Journal of Information System Research (JOSH) 3, no. 3 (April 27, 2022): 159–68. http://dx.doi.org/10.47065/josh.v3i3.1455.

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Oil palm (Elaeis guinensis) is a plant that has its own charm and plays an important role in people's lives. Plants are categorized as normal if they can process their physiological functions properly. In line with the development and expansion of community-owned oil palm land areas, more and more problems arise due to various types of diseases and pests attack on oil palm plants, especially on the midrib and leaves of oil palm. The existence of diseases and pests that cause losses in plant productivity also results in loss of costs used to restore plants that have been attacked by diseases or pests in nurseries, immature and mature plants. The lack of understanding of farmers regarding how to diagnose and proper control of oil palm diseases and pests as well as the availability of experts or experts in the field of oil palm in smallholder oil palm plantation areas can be overcome by presenting experts or experts or doubling the knowledge possessed by experts in the coconut field. oil palm by building an expert system for the diagnosis of diseases and pests in oil palm leaf midribs. The certainty factor method is used to describe the uncertainty in thinking and express the degree of confidence of the expert or expert in diagnosing the types of diseases and pests of oil palm. The developed expert system is expected to be useful for farmers in the area or ordinary people in diagnosing diseases and pests on oil palm leaf sheaths through the symptoms selected during consultations to diagnose the types of diseases and pests that are being experienced.

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Osumanu Haruna Ahmed, Lee Yit Leng, Mohamadu Boyie Jalloh Azwan Awang Norawanis, Abdul Razak Adiza Alhassan Musah, and Syahirah Shahlehi. "Brief Review: Climate Change and Its Impact on Mango Pests and Diseases." Journal of Agriculture and Crops, no. 93 (June 25, 2023): 391–99. http://dx.doi.org/10.32861/jac.93.391.399.

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Climate change is negatively impacting the agricultural sector. This review focuses on the effects of climate change on mango pests and diseases, the unknown aspects of this problem, and possible mitigation measures. In addition, mango is susceptible to several pests and diseases infestation at all its stage of life. The major abiotic factors associated with climate change that affect mango pests and diseases include changes in precipitation, wind variability, increased temperature, increases in atmospheric CO2, and changes in light intensity. These factors affect mango pests and diseases in various dimensions in one way or another, including increased activity, growth, development, reproduction, distribution, and migration. These abiotic factors also influence plant growth, development, and reproduction. These interacting factors are complex, and further studies are needed to obtain relevant data to understand the relationships between these factors and pests occurrence. Developing predictive models from these data and intercropping with aromatic plants will be useful for strategies to mitigate the devastating effects of pests and diseases occurrence on mango crops and food security.

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