Analysis of remote reflection spectroscopy to monitor plant health

Woodhouse, R.; Heeb, M.; Berry, Wade L.; Hoshizaki, T.; Wood, Mark

doi:10.1016/0273-1177(94)90297-6

Cited by 12 publications

(8 citation statements)

References 8 publications

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“…Studies utilizing spectroscopy to monitor lettuce condition have been explored in a wide range of stressors. For example, Woodhouse, Heeb, Berry, Hoshizaki, and Wood () showed the potential of this technique for monitoring health conditions of excised leaves of lettuce grown hydroponically under different stress conditions (i.e., copper, zinc, nitrogen, phosphorus, potassium, drought), applied singularly. More recently, studies have focused on the determination of nitrogen content of lettuce leaves and canopy by spectra using multivariate modeling methods (Gao, Mao, & Zhang, ; Itoh et al, ; Mao, Gao, Zhang, & Kumi, ; Sun et al, ).…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems

Cotrozzi

Couture

2019

Plants People Planet

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Advancements in our ability to rapidly detect plant responses to stress are necessary to improve crop management practices and meet the global challenge of food security. Using optical approaches to detect plant stress before symptoms become apparent has great potential, but these approaches lack testing in multiple-stress environments and fail to fully exploit the data collected. Using hyperspectral data from lettuce, we show that optical measurements can provide growers with important stress-related information to inform crop management practices. We suggest that integrating this technology into protected agrosystems, such as greenhouses, could greatly improve crop quality and yield. Summary• Tools to detect and predict stress pre-visually are essential to optimally manage agrosystems. Here, we investigated the capability of reflectance spectroscopy to characterize responses of asymptomatic crop leaves under multi-stress conditions.• Full range (350-2,500 nm) reflectance measurements and traditional plant stress responses were collected on lettuce leaves under the combination of different supplemental light types and intensities, fertilization and salinity. Partial leastsquares discriminate analysis and regression modeling and spectral indices were employed to characterize plant responses to multiple stress conditions, both alone and in combination.• Spectral profiles (400-800 nm + 1,900-2,200 nm) of individuals grown under variable environments were statistically different (p < .05) for multiple combinations.Partial least-squares discriminate analysis accurately classified the different single stressors well (accuracy: 0.76-0.91), but generated moderate accuracies (0.63-0.65) for two-stress combinations, and low accuracy (0.33) for higher order stress combinations. Osmotic potential, and chlorophyll and phenol concentrations were well predicted by spectral data (validation R 2 : 0.70-0.84). Higher lettuce yield and quality was found under sodium light at high intensity (850 µmol m −2 s −1 photosynthetic active radiation), with high fertilization (150 ppm N) and no salinity. | 245

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Section: Introductionmentioning

confidence: 99%

Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems

Cotrozzi

Couture

2019

Plants People Planet

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“…Nevertheless, remote monitoring of plant health by reflectance spectroscopy in the visible and near infrared waveband regions is achievable. Simple ratioing techniques have allowed detection of water stress in the classical NIR waveband regions while metal toxicity and deficiency conditions were detected by notable changes in the visible light range despite high variability in data and background noise [107]. However, such simple techniques do not allow for discriminatory identification of the specific stress in question.…”

Section: Stress-associated Leaf Spectral Propertiesmentioning

confidence: 99%

Signature Optical Cues: Emerging Technologies for Monitoring Plant Health

Liew

Chong

et al. 2008

Sensors

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Optical technologies can be developed as practical tools for monitoring plant health by providing unique spectral signatures that can be related to specific plant stresses. Signatures from thermal and fluorescence imaging have been used successfully to track pathogen invasion before visual symptoms are observed. Another approach for non-invasive plant health monitoring involves elucidating the manner with which light interacts with the plant leaf and being able to identify changes in spectral characteristics in response to specific stresses. To achieve this, an important step is to understand the biochemical and anatomical features governing leaf reflectance, transmission and absorption. Many studies have opened up possibilities that subtle changes in leaf reflectance spectra can be analyzed in a plethora of ways for discriminating nutrient and water stress, but with limited success. There has also been interest in developing transgenic phytosensors to elucidate plant status in relation to environmental conditions. This approach involves unambiguous signal creation whereby genetic modification to generate reporter plants has resulted in distinct optical signals emitted in response to specific stressors. Most of these studies are limited to laboratory or controlled greenhouse environments at leaf level. The practical translation of spectral cues for application under field conditions at canopy and regional levels by remote aerial sensing remains a challenge. The movement towards technology development is well exemplified by the Controlled Ecological Life Support System under development by NASA which brings together technologies for monitoring plant status concomitantly with instrumentation for environmental monitoring and feedback control.

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“…For example, historical waste-disposal activities at the Department of Energy’s Oak Ridge Y-12 Plant resulted in the release of Li to the groundwater [ 8 ]. Numerous studies have shown that there are shifts in plant reflectance spectra due to metal stress (or simulated metal stress) [ 2 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ] but to the authors’ knowledge none have considered response to Li exposure.…”

Section: Introductionmentioning

confidence: 99%

Reflectance-Based Vegetation Index Assessment of Four Plant Species Exposed to Lithium Chloride

Martínez

Sharp

Johnson

et al. 2018

Sensors

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This study considers whether a relationship exists between response to lithium (Li) exposure and select vegetation indices (VI) determined from reflectance spectra in each of four plant species: Arabidopsis thaliana, Helianthus annuus (sunflower), Brassica napus (rape), and Zea mays (corn). Reflectance spectra were collected every week for three weeks using an ASD FieldSpec Pro spectroradiometer with both a contact probe (CP) and a field of view probe (FOV) for plants treated twice weekly in a laboratory setting with 0 mM (control) or 15 mM of lithium chloride (LiCl) solution. Plants were harvested each week after spectra collection for determination of relevant physical endpoints such as relative water content and chlorophyll content. Mixed effects analyses were conducted on selected endpoints and vegetation indices (VI) to determine the significance of the effects of treatment level and length of treatment as well as to determine which VI would be appropriate predictors of treatment-dependent endpoints. Of the species considered, A. thaliana exhibited the most significant effects and corresponding shifts in reflectance spectra. Depending on the species and endpoint, the most relevant VIs in this study were NDVI, PSND, YI, R1676/R1933, R750/R550, and R950/R750.

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Analysis of remote reflection spectroscopy to monitor plant health

Cited by 12 publications

References 8 publications

Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems

Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems

Signature Optical Cues: Emerging Technologies for Monitoring Plant Health

Reflectance-Based Vegetation Index Assessment of Four Plant Species Exposed to Lithium Chloride

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