Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: Non-parametric statistical approaches and physiological implications

Delalieux, Stephanie; Aardt, Jan van; Keulemans, Wannes; Schrevens, Eddie; Coppin, Pol

doi:10.1016/j.eja.2007.02.005

Cited by 206 publications

(92 citation statements)

References 26 publications

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“…This method was successfully used in previous studies for detecting scab disease in apple leaves [2,38]. Logistical regression was implemented to examine the ability of each of the fluorescence and reflectance indices (Tables 1 and 2) for detecting the event of interest (disease).…”

Section: Binary Logistic Regressionmentioning

confidence: 99%

Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices

Leufen

Hunsche

et al. 2013

Remote Sensing

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Abstract:Leaf diseases, such as powdery mildew and leaf rust, frequently infect barley plants and severely affect the economic value of malting barley. Early detection of barley diseases would facilitate the timely application of fungicides. In a field experiment, we investigated the performance of fluorescence and reflectance indices on (1) detecting barley disease risks when no fungicide is applied and (2) estimating leaf chlorophyll concentration (LCC). Leaf fluorescence and canopy reflectance were weekly measured by a portable fluorescence sensor and spectroradiometer, respectively. Results showed that vegetation indices recorded at canopy level performed well for the early detection of slightly-diseased plants. The combined reflectance index, MCARI/TCARI, yielded the best discrimination between healthy and diseased plants across seven barley varieties. The blue to far-red fluorescence ratio (BFRR_UV) and OSAVI were the best fluorescence and reflectance indices for estimating LCC, respectively, yielding R 2 of 0.72 and 0.79. Partial

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Section: Binary Logistic Regressionmentioning

confidence: 99%

Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices

Leufen

Hunsche

et al. 2013

Remote Sensing

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“…These sensors obtain continuous narrowband light reflectance data encompassing several regions of the light spectrum, affording researchers the opportunity to discriminate diseased tissue from non-diseased tissue and to identify regions of the light spectrum best suited for detecting plant diseases [10] [16].…”

Section: Introductionmentioning

confidence: 99%

Relationships between Microsclerotia Content and Hyperspectral Reflectance Data in Soybean Tissue Infected by Macrophomina phaseolina

Fletcher¹,

Smith²,

Mengistu³

et al. 2014

AJPS

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Alternative methods are needed to assess the severity of charcoal rot disease [Macrophomina phaseolina (Tassi) Goid] in soybean [Glycine max (L.)] plant tissue. The objective of this study was to define the relationship between light reflectance properties and microsclerotia content of soybean stem and root tissue. Understanding that relationship could lead to using spectral reflectance data as a tool to assess the severity of charcoal rot disease in soybean plants, thus reducing human bias associated with qualitative analysis of soybean plant tissue and cost and time issues connected with quantitative analysis. Hyperspectral reflectance measurements (400 -2490 nm) were obtained with a non-imaging spectroradiometer of non-diseased and charcoal rot diseased ground stem and root tissue samples of six soybean genotypes ("Clark", "LD00-3309", "LG03-4561-14", "LG03-4561-19", "Saline", and "Y227-1"). Relationships between the reflectance measurements and tissue microsclerotia content were evaluated with Spearman correlation (rs) analysis (p < 0.05). Moderate (r s = ±0.40 to ±0.59), strong (r s = ±0.60 to ±0.79), and very strong (r s = ±0.80 to ±1.00) negative and positive statistically significant (p < 0.05) monotonic relationships were observed between tissue spectral reflectance values and tissue microsclerotia content. Nearinfrared and shortwave-infrared wavelengths had the best relationships with microsclerotia content in the ground tissue samples, with consistent results obtained with near-infrared wavelengths in that decreases in near-infrared spectral reflectance values were associated with increases in microsclerotia content in the stem and root tissue of the soybean plants. The findings of R. S. Fletcher et al. 3738 this study provided evidence that relationships exist between tissue spectral reflectance and tissue microsclerotia content of soybean plants, supporting spectral reflectance data as a means for assessing variation of microsclerotia content in soybean plants. Future research should focus on the modelling capabilities of the selected wavelengths and on the feasibility of using these wavelengths in machine learning algorithms to differentiate non-diseased from charcoal rot diseased tissue.

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“…Farmers only have to apply pesticides when abnormalities are detected in the normal growth pattern of the plants. Therefore, it has important implications for biotic stress detection and management in apple orchards [5].…”

Section: Applicationof Spectroscopy In Agro-food Industrymentioning

confidence: 99%

Application of Near-Infrared Spectrometer in Agro-Food Analysis: A Review

Misal¹,

Deshmukh²

2016

IJCA

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In this review paper applications of Near Infrared (NIR) spectroscopy in agro-food analysis is discussed. NIR spectrometers have a wider application use in agro-food industry and many fields. In agro-food industry application includes pesticide residue detection, chemical detection, microbiological hazard detection, physical hazards detection and food safety and traceability. In addition spectrometer are explored within various fields of agricultural products include food, fruits, vegetables, crops and dairy products, oil and beverages.

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Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: Non-parametric statistical approaches and physiological implications

Cited by 206 publications

References 26 publications

Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices

Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices

Relationships between Microsclerotia Content and Hyperspectral Reflectance Data in Soybean Tissue Infected by Macrophomina phaseolina

Application of Near-Infrared Spectrometer in Agro-Food Analysis: A Review

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