Multiple Causation of Perennial Plant Diseases and Control by Team Effort

1969 ◽  
Vol 72 (3) ◽  
pp. 406
Author(s):  
Webster H. Sill
Keyword(s):  
Plant Diseases ◽  
Perennial Plant ◽  
Multiple Causation ◽  
And Control

Nanotechnology as a Smart Way to Promote the Growth of Plants and Control Plant Diseases

2021 ◽  
pp. 1-16
Author(s):  
Heba Mahmoud Mohammad Abdel‐Aziz ◽  
Mohammed Nagib Abdel‐ghany Hasaneen
Keyword(s):  
Control Plant ◽  
Plant Diseases ◽  
And Control

scholarly journals PENGARUH KONSENTRASI MINYAK KEMIRI SUNAN (Reutealis trisperma (Blanco) Airy Shaw) TERHADAP LARVA Crocidolomia binotalis Zell. (Lepidoptera; Pyralidae) HAMA PADA TANAMAN SAWI (Brassica juncea L.)

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Yenny Muliani ◽  
Erry Mustariani ◽  
Rahmat Wahid Ramdyan
Keyword(s):  
Feeding Activity ◽  
Dry Weight ◽  
Plant Diseases ◽  
Hazelnut Oil ◽  
Botanical Pesticide ◽  
Crocidolomia Binotalis ◽  
Randomized Design ◽  
Lepidoptera Pyralidae ◽  
The University ◽  
And Control

ABSTRAKKemiri sunan (Reutealis trisperma (Blanco) Airy Shaw) dikenal sebagai tumbuhan yang berperan sebagai pestisida nabati yang belum banyak diketahui keampuhannya, sehingga perlu dilakukan pengujian untuk memperoleh informasi tentang keampuhan dari tumbuhan ini. Pengujian efektivitasnya dilakukan terhadap larva Crocidolomia binotalis Zell. penyebab kerusakan pada tanaman sawi. Percobaan dilaksanakan di Laboratorium Vertebrata, Departemen Hama dan Penyakit Tumbuhan, Fakultas Pertanian, Universitas Padjadjaran, Jatinangor, berlangsung dari Maret sampai Mei 2019. Percobaan menggunakan Rancangan Acak Lengkap (RAL) dengan 5 perlakuan dan 5 ulangan. Perlakuan meliputi minyak kemiri sunan dengan konsentrasi 10%, 5%, 2.5%, 1.25% dan kontrol. Hasil penelitian menunjukkan minyak kemiri sunan berpengaruh terhadap larva Crocidolomia binotalis. Konsentrasi 10% dapat mengakibatkan mortalitas paling tinggi sebesar 100% pada 7 HSA. Selain toksik, minyak kemiri sunan juga dapat memperpanjang lama perkembangan larva, menghambat aktivitas makan (antifeedant), serta menurunkan berat kering larva dibandingkan dengan kontrol. Minyak kemiri sunan berpotensi sebagai alternatif pengendali hama yang ramah lingkungan karena dapat berperan sebagai pestisida nabatiKata kunci: Kemiri sunan, Crocidolomia binotalis, Pestisida nabatiABSTRACTReutealis trisperma (Blanco) Airy Shaw is know as a plant that acts as a vegetable pesticide that is not yet widely known for its efficacy, so testing is needed to obtain information about the efficacy of this plant. Effectiveness testing is carried out on Crocidolomia binotalis Zell. larvae causing damage to oil palm plants. The experiment was carried out in the vertebrate laboratory, the deparment of pest and plant diseases, the faculty of agriculture, the university Padjadjaran, taking place from March-May 2019. The experiment used the randomized design complete with 5 treatments and 5 replication. The treatments included oil Reutealis trisperma (Blanco) Airy Shaw with a concentration 10%, 5%, 2.5%, 1.25% and control. The result hazelnut oil affected the larva Crocidolomia binotalis Zell. 10% concentration can cause the highest mortality of 100% at 7 HAS. In addition to toxic, hazelnut oil prolong the development of larvae, inhibit feeding activity, and reduce the dry weight of larvae compared to controls. Hazelnut oil has potential as an alternative as an a alternative pest control that is environmentally friendly because it can act as a botanical pesticide.Keywords : Reutealis trisperma, Crocidolomia binotalis, Botanical pesticide

scholarly journals Current Status and Future Perspective on Enzyme Involving in Biocontrol of Plant Pathogen

2021 ◽  
Vol 8 (4) ◽  
Author(s):  
Ami Chaudhari ◽  
Jesal Patel
Keyword(s):  
Crop Yield ◽  
Plant Diseases ◽  
Current Status ◽  
Future Perspective ◽  
Lytic Enzymes ◽  
Molecular Approaches ◽  
Yield And Quality ◽  
And Control ◽  
Near Future ◽  
Rhizosphere Microorganism

To sustain the quality and abundance of fruit, feed and fiber provided by farmers all over the world, plant diseases must be regulated. Plant diseases may be prevented, mitigated, or regulated using a variety of methods. Growers also rely on chemical fertilizers and pesticides for good agronomic and horticultural practices. Such agricultural inputs have taken a vital part in spectacular increases in crop yield and quality over the last 100 years. Microbial enzymes function as biocatalysts for key biochemical reactions and also assist microbes reproduce in a particular niche. The ability of rhizosphere microorganism to increase the growth of plant and control phytopathogens has long been known. Rhizosphere microbes may aid plants in several ways in their fight against phytopathogens. Of all recognized biocontrol pathways, the excretion of lytic enzymes is known as an important way to prevent phytopathogens from living in the region of the rhizosphere. Rhizosphere microorganism produces chitinases, cellulases, proteases, and glucanases in reaction to phytopathogen assault. For assessing antagonist-pathogen interactions, ecological characteristics of antagonists in the rhizosphere, and optimizing the effectiveness of bacterial, fungal, and viral biocontrol agents, new molecular approaches have become available. Given the experience of fungicides in near future, biological management would be another method to control diseases of plant. Since agro-ecosystem is a flexible and functioning structure that involves many variables that affect disease and production of crop, other IPM methods to control diseases of crop are also important in different surrounding conditions. As result, to successfully minimize disease production and crop yield loss in various crop systems, other IPM management mechanisms other than biological control should be considered and implemented.

scholarly journals Goatweed Biology and Control in Pastures

EDIS ◽  
2008 ◽  
Vol 2008 (2) ◽  
Author(s):  
Brent A. Sellers
Keyword(s):  
Fact Sheet ◽  
Perennial Plant ◽  
And Control

SS-AGR-299, a 3-page illustrated fact sheet by Brent A. Sellers, describes the biology and control of this perennial plant, also known as sweet broom and licorice weed, that is becoming a serious problem in Florida pastures. Published by the UF Department of Agronomy, February 2008. SS AGR 299/AG304: Goatweed Biology and Control in Pastures (ufl.edu)

scholarly journals Quantifying Airborne Dispersal Route of Corynespora cassiicola in Greenhouses

2021 ◽  
Vol 12 ◽  
Author(s):  
Qian Zhao ◽  
Yanxia Shi ◽  
Yuhong Wang ◽  
Xuewen Xie ◽  
Lei Li ◽  
...  
Keyword(s):  
Particle Size ◽  
Global Scale ◽  
Plant Diseases ◽  
Transmission Dynamics ◽  
Corynespora Cassiicola ◽  
Air Samples ◽  
High Incidence ◽  
Dispersal Route ◽  
And Control ◽  
New Strategies

Target leaf spot (TLS), caused by Corynespora cassiicola, is an emerging and high-incidence disease that has spread rapidly on the global scale. Aerospores released by infected plants play a significant role in the epidemiology of cucumber TLS disease; however, no data exist concerning the infectiousness and particle size of C. cassiicola aerospores, and the experimental evidence for the aerospores transmission was lacking. In the present study, highly effective approaches to collect and quantify aerospores were developed for exposure chamber and greenhouse studies. Quantifiable levels of C. cassiicola aerospores were detected in 27 air samples from nine naturally infested greenhouses, ranging from 198 to 5,969 spores/m3. The C. cassiicola strains isolated from air samples were infective to healthy cucumber plants. Exposure chambers were constructed to study the characteristics of C. cassiicola aerospores released by artificially infested cucumber plants. The particle size of C. cassiicola ranged predominately from 2.1 to 4.7 μm, accounting for 71.97% of the total amount. In addition, the transmission dynamics of C. cassiicola aerospores from donor cucumber plants to recipient cucumber plants were confirmed in exposure chambers and greenhouses. The concentration of C. cassiicola aerospores was positively associated with cucumber TLS disease severity. This study suggested that aerospore dispersal is an important route for the epidemiology of plant fungal disease, and these data will contribute to the development of new strategies for the effective alleviation and control of plant diseases.

scholarly journals Improving Accuracy of Tomato Plant Disease Diagnosis Based on Deep Learning With Explicit Control of Hidden Classes

2021 ◽  
Vol 12 ◽  
Author(s):  
Alvaro Fuentes ◽  
Sook Yoon ◽  
Mun Haeng Lee ◽  
Dong Sun Park
Keyword(s):  
Deep Learning ◽  
Tomato Plant ◽  
Plant Disease ◽  
High Efficiency ◽  
Recognition Rate ◽  
Disease Diagnosis ◽  
Plant Diseases ◽  
Improve Model ◽  
Improving Accuracy ◽  
And Control

Recognizing plant diseases is a major challenge in agriculture, and recent works based on deep learning have shown high efficiency in addressing problems directly related to this area. Nonetheless, weak performance has been observed when a model trained on a particular dataset is evaluated in new greenhouse environments. Therefore, in this work, we take a step towards these issues and present a strategy to improve model accuracy by applying techniques that can help refine the model’s generalization capability to deal with complex changes in new greenhouse environments. We propose a paradigm called “control to target classes.” The core of our approach is to train and validate a deep learning-based detector using target and control classes on images collected in various greenhouses. Then, we apply the generated features for testing the inference of the system on data from new greenhouse conditions where the goal is to detect target classes exclusively. Therefore, by having explicit control over inter- and intra-class variations, our model can distinguish data variations that make the system more robust when applied to new scenarios. Experiments demonstrate the effectiveness and efficiency of the proposed approach on our extended tomato plant diseases dataset with 14 classes, from which 5 are target classes and the rest are control classes. Our detector achieves a recognition rate of target classes of 93.37% mean average precision on the inference dataset. Finally, we believe that our study offers valuable guidelines for researchers working in plant disease recognition with complex input data.

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