Hyperspectral indices to diagnose leaf biotic stress of apple plants, considering leaf phenology

Delalieux, Stephanie; Somers, Ben; Verstraeten, Willem; Aardt, Jan A. N. van; Keulemans, Wannes; Coppin, Pol

doi:10.1080/01431160802541556

Cited by 101 publications

(49 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Recent studies have made progress on detecting diseases and nutrient stresses by hyperspectral remote sensing [32,[38][39][40]. Reflectance indices have been suggested for detecting diseases such as apple leaf scab disease under well controlled conditions [38,39].…”

mentioning

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

View full text Add to dashboard Cite

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

show abstract

mentioning

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

View full text Add to dashboard Cite

show abstract

“…The increase in efficiency of one of these three processes (absorption, fluorescence and thermal emission) will result in a decrease in yield of the other two. As such, the relative intensities of ChlF are strongly related to the efficiency of photochemistry and heat dissipation (Papageorgiou & Govindjee, 2004;Lichtenthaler et al, 2007;Delalieux et al 2009b) and may provide additional data to detect plant stress in an early stage. Generally, fluorescence yield is highest when photochemistry and heat dissipation are lowest.…”

Section: Chlorophyll Fluorescencementioning

confidence: 99%

“…The physiological condition of plants is indicative of plant productivity and adaptability to stress and it is a general indication of the environment in which they grow (Alia et al, 2006;Gray et al, 2010). Research on biotic stresses includes the molecular mechanisms used by viruses, bacteria, fungi, and nematodes to incite disease and those used by plants to resist infection (Li et al, 2008;Yang et al, 2009;Delalieux et al, 2009b). Research on abiotic stresses includes molecular mechanisms by which plants resist such unfavourable conditions as drought, flooding, chilling, light, excess salts, toxic metals, and pollutants (Flawers, 2004;Jones, 2007;El-Nahry & Hammad, 2009).…”

Section: Introductionmentioning

confidence: 99%

Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses

Krezhova¹

2011

Soybean - Genetics and Novel Techniques for Yield Enhancement

View full text Add to dashboard Cite

“…For many purposes, remote sensing techniques provide means of measuring the characteristics of the objects on the Earth surface and for detecting environmental changes that occur as a result of human activities or natural processes [1], [2]. Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture -spectral discrimination of crops and their genotypes [3], quantitative estimation of different biophysical and biochemical parameters through empirical and physical modelling [4], [5], assessing of abiotic and biotic stresses [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing of the Influence of Biotic Stress on Plant Biophysical Variables

Krezhova¹,

Maneva²,

Petrov³

et al. 2017

RadJ

View full text Add to dashboard Cite

Abstract. Hyperspectral remote sensing provides for significant advancement in the evaluation of the subtle changes in biophysical and biochemical attributes of the crop plants. Accurate estimates of leaf pigments, nitrogen, dry matter, water content, and leaf area index (LAI) from remotely sensed data can assist in determining the vegetation physiological state. In this paper, hyperspectral remote sensing measurements of the leaf reflectance were applied for assessing the effect of biotic stress (viral infection) on the spectral behaviour and biophysical variables of young potato plants, cultivar Agata, infected with Potato Virus Y (PVY). Spectral reflectance data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (350-1100 nm) with a spectral resolution of 1.5 nm. For the assessment of differences between the reflectance data of healthy and infected plant data processing techniques, such as Student's t-test, first derivative analyses, and estimation of vegetation indices, were applied. The analyses were performed in green, red, red edge and near infrared spectral ranges (450-850 nm) where the differences were the most significant and give information about changes in the chlorophyll and pigment content, moisture content, cells structures, and plant stress. Several vegetation indices (NDVI -Normalized Difference Vegetation Index, fD -Disease Index, SR -Simple Ratio, TCARI -Transformed Chlorophyll Absorption Reflectance Index, etc.) were computed and the best results for assessing the changes in the physiological state of the plants gave TCARI. A strong relationship was found between the results of the spectral analyses and the serological test DAS-ELISA was applied to assess the presence and the degree of the PVY infection.

show abstract

Hyperspectral indices to diagnose leaf biotic stress of apple plants, considering leaf phenology

Cited by 101 publications

References 58 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

Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses

Remote Sensing of the Influence of Biotic Stress on Plant Biophysical Variables

Contact Info

Product

Resources

About