Remote Sensing of Biotic Stress in Crop Plants and Its Applications for Pest Management

Prabhakar, M.; Prasad, Y. G.; Rao, Mahesh

doi:10.1007/978-94-007-2220-0_16

Cited by 43 publications

(65 citation statements)

References 119 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Precision agriculture [14,[100][101][102][103] requires the development of methods of remote sensing of fields and fast analysis of the derived data. The prospective direction of field monitoring is in the application of spectral indices [41,104,105] due to their connection to physiological processes [15,61] and the damage caused by stressors and pathogens in plants [102,106,107].…”

Section: Discussionmentioning

confidence: 99%

“…Early monitoring of these damages plays an important role in precision agriculture and ecological monitoring. As a result, remote sensing of the photosynthetic process is an important practical problem [13][14][15]. There are many methods that can be used for the analysis of the photosynthesis process in plants; in particular, pulse-amplitude-modulation (PAM)-fluorometry [16,17], JIP-test [18][19][20], and analysis of CO 2 exchange [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Connection of the Photochemical Reflectance Index (PRI) with the Photosystem II Quantum Yield and Nonphotochemical Quenching Can Be Dependent on Variations of Photosynthetic Parameters among Investigated Plants: A Meta-Analysis

Sukhova

Sukhov

2018

Remote Sensing

View full text Add to dashboard Cite

Abstract:The development of spectral methods of remote sensing, including measurement of a photochemical reflectance index (PRI), is a prospective trend in precision agriculture. There are many works which have investigated the connection between photosynthetic parameters and PRI; however, their results varied and were sometimes contradictory. For this paper, we performed a meta-analysis of works in this field. Here, only linear correlations of PRI with photosynthetic parameters-including quantum yield of photosystem II (∆F/Fm'), nonphotochemical quenching of chlorophyll fluorescence (NPQ), and light use efficiency (LUE)-were investigated. First, it was shown that the correlations were dependent on conditions of PRI measurements (leaf or canopy; artificial light or sunlight). Second, it was shown that a minimal level of the photosynthetic stress, and the variation of this level among investigated plants, can influence the linear correlation of PRI with ∆F/Fm' and NPQ; the effect was dependent on conditions of measurements. In contrast, the distribution of LUE among plants did not influence its correlation with PRI. Thus, the meta-analysis shows that the distribution of photosynthetic parameters among investigated plants can be an important factor that influences the efficiency of remote sensing on the basis of the PRI measurement.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Connection of the Photochemical Reflectance Index (PRI) with the Photosystem II Quantum Yield and Nonphotochemical Quenching Can Be Dependent on Variations of Photosynthetic Parameters among Investigated Plants: A Meta-Analysis

Sukhova

Sukhov

2018

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…1 Remote sensing increases the efficiency of this process by gathering data associated with crop health quickly and automating processes for crop health visual display and evaluation. 2 Satellite imagery is not collected with the frequency required for precision agriculture, and atmospheric effects or cloud cover can have dramatic effects on the quality of data produced. Ground-based (tractor-mounted) sensors achieve high resolution, but operational and data efficiency measures may be much reduced compared with other approaches.…”

Section: Introductionmentioning

confidence: 99%

Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment

Stanton

Starek

Elliott³

et al. 2017

J. Appl. Remote Sens

View full text Add to dashboard Cite

"Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment," J. Appl. Remote Sens. 11(2), 026035 (2017), doi: 10.1117/1.JRS.11.026035. Abstract. A small, fixed-wing unmanned aircraft system (UAS) was used to survey a replicated small plot field experiment designed to estimate sorghum damage caused by an invasive aphid. Plant stress varied among 40 plots through manipulation of aphid densities. Equipped with a consumer-grade near-infrared camera, the UAS was flown on a recurring basis over the growing season. The raw imagery was processed using structure-from-motion to generate normalized difference vegetation index (NDVI) maps of the fields and three-dimensional point clouds. NDVI and plant height metrics were averaged on a per plot basis and evaluated for their ability to identify aphid-induced plant stress. Experimental soil signal filtering was performed on both metrics, and a method filtering low near-infrared values before NDVI calculation was found to be the most effective. UAS NDVI was compared with NDVI from sensors onboard a manned aircraft and a tractor. The correlation results showed dependence on the growth stage. Plot averages of NDVI and canopy height values were compared with per-plot yield at 14% moisture and aphid density. The UAS measures of plant height and NDVI were correlated to plot averages of yield and insect density. Negative correlations between aphid density and NDVI were seen near the end of the season in the most damaged crops.

show abstract

“…Numerous important reviews (29,71,111,117,156) and textbooks (54,60,61,124) describe the theory and applications of remote sensing, and it has been an established research discipline for about four decades (12,147). It was Isaac Newton who discovered that light could be separated into a spectrum of colors, and approximately 100 years later, James Clerk Maxwell discovered that light as we see it is part of a very wide radiometric spectrum (113).…”

Section: Background and Contextmentioning

confidence: 99%

Remote Sensing and Reflectance Profiling in Entomology

Nansen

Elliott

2016

Annu. Rev. Entomol.

View full text Add to dashboard Cite

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

show abstract

Remote Sensing of Biotic Stress in Crop Plants and Its Applications for Pest Management

Cited by 43 publications

References 119 publications

Connection of the Photochemical Reflectance Index (PRI) with the Photosystem II Quantum Yield and Nonphotochemical Quenching Can Be Dependent on Variations of Photosynthetic Parameters among Investigated Plants: A Meta-Analysis

Connection of the Photochemical Reflectance Index (PRI) with the Photosystem II Quantum Yield and Nonphotochemical Quenching Can Be Dependent on Variations of Photosynthetic Parameters among Investigated Plants: A Meta-Analysis

Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment

Remote Sensing and Reflectance Profiling in Entomology

Contact Info

Product

Resources

About