scholarly journals UAV Remote Sensing: An Innovative Tool for Detection and Management of Rice Diseases

2021 ◽  
Author(s):  
Xin-Gen Zhou ◽  
Dongyan Zhang ◽  
Fenfang Lin
Keyword(s):  
Remote Sensing ◽  
Rice Blast ◽  
Sheath Blight ◽  
Diseased Plant ◽  
Rice Sheath Blight ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Aerial Vehicle ◽  
Innovative Tool ◽  
China And Japan

Unmanned aerial vehicle (UAV) remote sensing is a new alternative to traditional diagnosis and detection of rice diseases by visual symptoms, providing quick, accurate and large coverage disease detection. UAV remote sensing offers an unprecedented spectral, spatial, and temporal resolution that can distinguish diseased plant tissue from healthy tissue based on the characteristics of disease symptoms. Research has been conducted on using RGB sensor, multispectral sensor, and hyperspectral sensor for successful detection and quantification of sheath blight (Rhizoctonia solani), using multispectral sensor to accurately detect narrow brown leaf spot (Cercospora janseana), and using infrared thermal sensor for detecting the occurrence of rice blast (Magnaporthe oryzae). UAV can also be used for aerial application, and UAV spraying has become a new means for control of rice sheath blight and other crop diseases in many countries, especially China and Japan. UAV spraying can operate at low altitudes and various speeds, making it suitable for situations where arial and ground applications are unavailable or infeasible and where precision applications are needed. Along with advances in digitalization and artificial intelligence for precision application across fertilizer, pest and crop management needs, this UAV technology will become a core tool in a farmer’s precision equipment mix in the future.

scholarly journals Eco-Friendly Management of Rice Diseases

2015 ◽  
Vol 3 (1) ◽  
pp. 80-88 ◽  
Author(s):  
Md. Amanut Ullah Razu ◽  
Ismail Hossain
Keyword(s):  
Leaf Spot ◽  
Leaf Extract ◽  
Sheath Blight ◽  
Leaf Blight ◽  
Bacterial Leaf Blight ◽  
Curvularia Lunata ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Clove Extract ◽  
Field And Laboratory Conditions

Comparative efficacy of BAU-Biofungicide (2%), a product of Trichoderma harzianum, Garlic (Allium sativum) clove extract (5%), Allamanda(Allamanda cathartica) leaf extract (5%), Bion (25ppm), Amistar (0.1%) and Tilt 250EC (0.1%) were evaluated for eco-friendly managementof diseases of rice cv. BRRI Dhan-49 under field and laboratory conditions from July,2013 to March,2014. The field experiment was carriedout following Randomised Complete Block Design and the laboratory experiments were done following Completely Randomized Design.Brown spot, Narrow brown leaf spot, Bacterial leaf blight and Sheath blight were recorded in the field. The lowest incidence of brown spotand narrow brown leaf spot was observed in plots treated with BAU-Biofungicide and that of bacterial leaf blight was observed in plots sprayedwith Allamanda leaf extract. In case of sheath blight, the lowest incidence was observed in BAU-Biofungicide sprayed plots. The highest grainyield (3680.34kg/ha) was recorded in plots sprayed with BAU-Biofungicide which is 40.56% higher over control. The highest seed germination(%) was recorded when seeds were treated with Garlic clove extract (89.29%) followed by BAU-Biofungicide (87.30%). The prevalence ofseed-borne fungi was investigated by blotter method. The identified seed-borne fungal species were Bipolaris oryzae, Fusarium oxysporum,Fusarium moniliforme, Curvularia lunata, Aspergillus niger and Aspergillus flavus. Maximum reduction of seed-borne infection of pathogenswas obtained by treating seeds with BAU-Biofungicide (2% of seed weight).DOI: http://dx.doi.org/10.3126/ijasbt.v3i1.11977    Int J Appl Sci Biotechnol, Vol. 3(1): 80-88 

Effects of rice-water chestnut intercropping on rice sheath blight and rice blast diseases

2013 ◽  
Vol 43 ◽  
pp. 89-93 ◽  
Author(s):  
Junhao Qin ◽  
Hongzhi He ◽  
Shiming Luo ◽  
Huashou Li
Keyword(s):  
Rice Blast ◽  
Sheath Blight ◽  
Rice Sheath Blight ◽  
Water Chestnut ◽  
Rice Water

scholarly journals EVALUATION OF DIFFERENT FUNGICIDES AGAINST BLAST, BROWN LEAF SPOT AND SHEATH BLIGHT OF RICE UNDER FIELD CONDITIONS IN SHEIKHUPURA, PAKISTAN

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Muhammad Shahbaz ◽  
Usman Shakir ◽  
Amna Palwasha ◽  
Faqir Ahmad ◽  
Muhammad Riaz ◽  
...  
Keyword(s):  
Leaf Spot ◽  
Sheath Blight ◽  
Field Conditions ◽  
Brown Leaf Spot ◽  
Brown Leaf

Hybrid Rice Outperforms Inbred Rice in Resistance to Sheath Blight and Narrow Brown Leaf Spot

Plant Disease ◽  
2021 ◽  
Author(s):  
Jun Shi ◽  
Xin-Gen (Shane) Zhou ◽  
Zongbu Yan ◽  
Rodante E. Tabien ◽  
Lloyd T Wilson ◽  
...  
Keyword(s):  
Leaf Spot ◽  
Hybrid Rice ◽  
Sheath Blight ◽  
Comparative Performance ◽  
Breeding Lines ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Almost All ◽  
Elite Breeding Lines ◽  
Moderately Resistant

Sheath blight (ShB, caused by Rhizoctonia solani AG1-1A) and narrow brown leaf spot (NBLS, Cercospora janseana) are among the most important diseases affecting rice production in Texas and other southern United States. Because of high yielding potential, hybrid rice acreage has continually increased. Understanding the relative levels of resistance to ShB and NBLS in hybrids over inbreds is important to effective disease management but remain largely unknown. Comparative performance of hybrid rice and inbred rice was evaluated with 173 hybrid and 155 inbred genotypes (cultivars and elite breeding lines) over five crop seasons (2016 to 2020) and two locations in Texas. The results show that genotype, cultivar type (hybrid or inbred), location, and their interactions had a significant effect on the severity of ShB and NBLS. ShB severities in hybrid genotypes were significantly lower than in inbred genotypes, with an average of 27% reduction in disease severity over the 5 year x 2 location evaluation. Most (53%) of the hybrid genotypes were rated moderately resistant (MR), whereas almost all (97%) of the inbred genotypes ranged from very susceptible (VS) to moderately susceptible (MS). Similarly, NBLS severities in hybrid genotypes are significantly lower than those in inbred genotypes. All but four hybrid genotypes exhibit immune reaction to NBLS. In contrast, 77% of the inbred genotypes exhibit the NBLS symptoms, with disease resistance reactions ranging from susceptible (S) to resistant (R). The results demonstrate that hybrid rice is generally less susceptible to sheath blight and has a higher level of resistance against NBLS compared to inbred rice.

Recurrent Phenotypic Selection for Resistance to Brown Leaf Spot in Smooth Bromegrass 1

Crop Science ◽  
1986 ◽  
Vol 26 (3) ◽  
pp. 533-536 ◽  
Author(s):  
Clyde C. Berg ◽  
Robert T. Sherwood ◽  
Kenneth E. Zeiders
Keyword(s):  
Leaf Spot ◽  
Phenotypic Selection ◽  
Smooth Bromegrass ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Selection For

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

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