Characterization of brown planthopper damage on rice crops through hyperspectral remote sensing under field conditions

Prasannakumar, N. R.; Chander, Subhash; Sahoo, Rabi Narayan

doi:10.1007/s12600-013-0375-0

Cited by 25 publications

(22 citation statements)

References 24 publications

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“…Characterization of brown planthopper (BPH) damage on rice plants through hyperspectral remote sensing under field conditions had been carried out by Prasannakumar et al (2014). The study discovered that in the VIS region (400-700nm), spectral reflectance of uninfected plants was lower than infested crops, while reflectance of the infested plant increased with the increase in damage.…”

Section: Remote Sensingmentioning

confidence: 99%

“…Figure 5 shows peaks that were revealed when values of correlation coefficients were plotted against wavelength, whereby four sensitive wavebands were identified; 764nm (r=0.674), 961nm (r=0.70), 1201nm (r=0.70), and 1664nm (r=0.60). Then, three new BPH indices were formulated (Prasannakumar et al, 2014) by using two or more sensitive wavebands, which had been brown planthopper index-1 (BPHI-1), brown planthopper index-2 (BPHI-2), and brown planthopper index-3 (BPHI-3), that showed a good relationship with BPH infestation levels. Furthermore, the BPH damage reflectance model, which is a multilinear regression model, was developed between damage levels and plant reflectance with R 2 = 0.71 and RMSE=1.74, while validation with R 2 = 0.73 and RMSE=0.71 accounted for 73 % of the variability in the BPH damage.…”

Section: Remote Sensingmentioning

confidence: 99%

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Optical imaging techniques for rice diseases detection: A review

2020

JAFE

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Rice diseases have caused great economic losses to farmers in rice cultivation. The current assessment of rice disease evaluation still relies on manual, subjective, and laborious techniques. The manual and subjective evaluations lead to uncertainties since some diseases have almost similar characterisation. The applications of immunological, molecular, and microscope techniques are time-consuming, costly, and skills dependent. Thus, optical techniques are recommended to facilitate the control of diseases through their feasibility, rapidity, and accuracy, which can lead to better management strategies, besides improving production activity. These techniques for detecting and monitoring the diseases are important for precaution and prevention action. The present review discusses the existing and potential optical techniques for the detection of rice diseases. The techniques include optical imaging that consists of computer vision, spectroscopy, multispectral imaging, hyperspectral imaging (HSI), and remote sensing. Thus, this work presents in-depth information related to the nondestructive and potential applications of optical imaging techniques for rice disease detection.

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Section: Remote Sensingmentioning

confidence: 99%

Section: Remote Sensingmentioning

confidence: 99%

Optical imaging techniques for rice diseases detection: A review

2020

JAFE

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“…In contrast, HSI with remote sensing examines many contiguous, narrow spectral channels (Campbell, 1996); thus, it is able to provide additional information, and no critical data are lost. HSI with remote sensing is better than MSI and demonstrates versatility for a variety of crop monitoring applications (Hunt et al, 1989;Blackburn, 1998;Champagne et al, 2003;Zhu et al, 2006;Wang et al, 2008;Prabhakar et al, 2011;Ranjan et al, 2012;Pradhan et al, 2014;Mahajan et al, 2014;Prasannakumar et al, 2014). HSI has already proven to be very effective in defense, agricultural research, and environmental applications (Lu and Chen, 1999;Ustin et al, 2004;Farley et al, 2007).…”

Section: Hsi In Agriculturementioning

confidence: 99%

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

Ahmed¹,

Yasmin²,

Mo³

et al. 2016

Journal of Biosystems Engineering

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Background: Although hyperspectral imaging was originally introduced for military, remote sensing, and astrophysics applications, the use of analytical hyperspectral imaging techniques has been expanded to include monitoring of agricultural crops and commodities due to the broad range and highly specific and sensitive spectral information that can be acquired. Combining hyperspectral imaging with remote sensing expands the range of targets that can be analyzed. Results: Hyperspectral imaging technology can rapidly provide data suitable for monitoring a wide range of plant conditions such as plant stress, nitrogen status, infections, maturity index, and weed discrimination very rapidly, and its use in remote sensing allows for fast spatial coverage. Conclusions: This paper reviews current research on and potential applications of hyperspectral imaging and remote sensing for outdoor field monitoring of agricultural crops. The instrumentation and the fundamental concepts and approaches of hyperspectral imaging and remote sensing for agriculture are presented, along with more recent developments in agricultural monitoring applications. Also discussed are the challenges and limitations of outdoor applications of hyperspectral imaging technology such as illumination conditions and variations due to leaf and plant orientation.

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“…The brown planthopper (BPH), Nilaparvata lugens Stål (Hemiptera: Delphacidae), is an insecticide‐induced resurgent insect pest of rice in Asia (Chelliah & Heinrichs, ; Gao, Gu, Bei, & Wang, ). It is responsible for serious crop losses (up to 60%; Prasannakumar, Chander, & Sahoo, ) due to direct feeding and to vectoring plant pathogenic viruses. Its geographic range has expanded in China, likely due to a range of adaptations to constant exposure to agricultural chemicals (You et al, ).…”

Section: Introductionmentioning

confidence: 99%

Silencing pyruvate kinase (NlPYK) leads to reduced fecundity in brown planthoppers, Nilaparvata lugens (Stål) (Hemiptera: Delphacidae)

Huang

et al. 2017

Arch Insect Biochem Physiol

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Pyruvate kinase (PYK) operates in the glycolytic pathway, responsible for regulating the balance between glycolysis and gluconeogenesis. The previous work indicates PYK acts in development of Drosophila embryos and in embryonic muscle growth, from which it may be inferred that PYK acts in insect fecundity. More to the point, as a central enzyme in the glycolytic pathway, PYK acts in many energy-spending functions in most organisms. On the background findings that triazophos (TZP) stimulates fecundity via increase activities of several genes in brown planthoppers, Nilaparvata lugens, we investigated the combined influence of TZP and silencing a N. lugens PYK (NlPYK) on reproduction-linked biological performance parameters. Here, we report that TZP+dsNlPYK treatments led to reduced (by 26%) ovarian, but not fat body, protein content relative to controls. Ovarian (35%) and fat body (54%) soluble sugar contents were reduced. TZP+dsNlPYK treatments also led to reduced (by about 24%) fecundity, expressed as numbers of eggs laid. These data show directly that NlPYK acts in insect fecundity, probably via increases in glucose metabolism.

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Characterization of brown planthopper damage on rice crops through hyperspectral remote sensing under field conditions

Cited by 25 publications

References 24 publications

Optical imaging techniques for rice diseases detection: A review

Optical imaging techniques for rice diseases detection: A review

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

Silencing pyruvate kinase (NlPYK) leads to reduced fecundity in brown planthoppers, Nilaparvata lugens (Stål) (Hemiptera: Delphacidae)

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