scholarly journals Reflectance Spectroscopy for Non-Destructive Measurement and Genetic Analysis of Amounts and Types of Epicuticular Waxes on Onion Leaves

Molecules ◽  
2020 ◽  
Vol 25 (15) ◽  
pp. 3454 ◽  
Author(s):  
Eduardo D. Munaiz ◽  
Philip A. Townsend ◽  
Michael J. Havey
Keyword(s):  
Prediction Models ◽  
Full Range ◽  
Reflectance Spectroscopy ◽  
Thrips Tabaci ◽  
Gas Chromatography Mass Spectrometry ◽  
Spectral Features ◽  
Epicuticular Waxes ◽  
Least Squares Regression ◽  
Destructive Measurement ◽  
Non Destructive

Epicuticular waxes on the surface of plant leaves are important for the tolerance to abiotic stresses and plant–parasite interactions. In the onion (Allium cepa L.), the variation for the amounts and types of epicuticular waxes is significantly associated with less feeding damage by the insect Thrips tabaci (thrips). Epicuticular wax profiles are measured using used gas chromatography mass spectrometry (GCMS), which is a labor intensive and relatively expensive approach. Biochemical spectroscopy is a non-destructive tool for measurement and analysis of physiological and chemical features of plants. This study used GCMS and full-range biochemical spectroscopy to characterize epicuticular waxes on seven onion accessions with visually glossy (low wax), semi-glossy (intermediate wax), or waxy (copious wax) foliage, as well as a segregating family from the cross of glossy and waxy onions. In agreement with previous studies, GCMS revealed that the three main waxes on the leaves of a wild type waxy onion were the ketone hentriacontanone-16 (H16) and fatty alcohols octacosanol-1 (Oct) and triacontanol-1 (Tri). The glossy cultivar “Odourless Greenleaf” had a unique phenotype with essentially no H16 and Tri and higher amounts of Oct and the fatty alcohol hexacosanol-1 (Hex). Hyperspectral reflectance profiles were measured on leaves of the onion accessions and segregating family, and partial least-squares regression (PLSR) was utilized to generate a spectral coefficient for every wavelength and prediction models for the amounts of the three major wax components. PLSR predictions were robust with independent validation coefficients of determination at 0.72, 0.70, and 0.42 for H16, Oct, and Tri, respectively. The predicted amounts of H16, Oct, and Tri are the result of an additive effect of multiple spectral features of different intensities. The variation of reflectance for H16, Oct, and Tri revealed unique spectral features at 2259 nm, 645 nm, and 730 nm, respectively. Reflectance spectroscopy successfully revealed a major quantitative trait locus (QTL) for amounts of H16, Oct, and Tri in the segregating family, agreeing with previous genetic studies. This study demonstrates that hyperspectral signatures can be used for non-destructive measurement of major waxes on onion leaves as a basis for rapid plant assessment in support of developing thrips-resistant onions.

Prediction of soil organic and inorganic carbon concentrations in Tunisian samples by mid-infrared reflectance spectroscopy using a French national library

2020 ◽  
Author(s):  
Tiphaine Chevallier ◽  
Cécile Gomez ◽  
Patricia Moulin ◽  
Imane Bouferra ◽  
Kaouther Hmaidi ◽  
...  
Keyword(s):  
Inorganic Carbon ◽  
Prediction Models ◽  
Reflectance Spectroscopy ◽  
Soil Samples ◽  
Infrared Reflectance ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Climate Conditions ◽  
Infrared Reflectance Spectroscopy ◽  
Soil Database

<p>Mid-Infrared Reflectance Spectroscopy (MIRS, 4000–400 cm<sup>-1</sup>) is being considered to provide accurate estimations of soil properties, including soil organic carbon (SOC) and soil inorganic carbon (SIC) contents. This has mainly been demonstrated when datasets used to build, validate and test the prediction model originate from the same area A, with similar geopedological conditions. The objective of this study was to analyze how MIRS performed when used to predict SOC and SIC contents, from a calibration database collected over a region A, to predict over a region B, where A and B have no common area and different soil and climate conditions. This study used a French MIRS soil dataset including 2178 soil samples to calibrate SIC and SOC prediction models with partial least squares regression (PLSR), and a Tunisian MIRS soil dataset including 96 soil samples to test them. Our results showed that using the French MIRS soil database i) SOC and SIC of French samples were successfully predicted, ii) SIC of Tunisian samples was also predicted successfully, iii) local calibration significantly improved SOC prediction of Tunisian samples and iv) prediction models seemed more robust for SIC than for SOC. So in future, MIRS might replace, or at least be considered as, a conventional physico-chemical analysis technique, especially when as exhaustive as possible calibration database will become available.</p>

scholarly journals Estimating Soil Properties and Nutrients by Visible and Infrared Diffuse Reflectance Spectroscopy to Characterize Vineyards

Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1895
Author(s):  
José Ramón Rodríguez-Pérez ◽  
Víctor Marcelo ◽  
Dimas Pereira-Obaya ◽  
Marta García-Fernández ◽  
Enoc Sanz-Ablanedo
Keyword(s):  
Soil Properties ◽  
Diffuse Reflectance Spectroscopy ◽  
Full Range ◽  
Cost Effective ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Standard Normal Variate ◽  
Standard Normal ◽  
Western Spain ◽  
Shortwave Infrared

Visible, near, and shortwave infrared (VIS-NIR-SWIR) reflectance spectroscopy, a cost-effective and rapid means of characterizing soils, was used to predict soil sample properties for four vineyards (central and north-western Spain). Sieved and air-dried samples were measured using a portable spectroradiometer (350–2500 nm) and compared for pistol grip (PG) versus contact probe (CP) setups. Raw data processed using standard normal variate (SVN) and detrending transformation (DT) were grouped into four subsets (VIS: 350–700 nm; NIR: 701–1000 nm; SWIR: 1001–2500 nm; and full range: 350–2500 nm) in order to identify the most suitable range for determining soil characteristics. The performance of partial least squares regression (PLSR) models in predicting soil properties from reflectance spectra was evaluated by cross-validation. The four spectral subsets and transformed reflectances for each setup were used as PLSR predictor variables. The best performing PLSR models were obtained for pH, electrical conductivity, and phosphorous (R2 values above 0.92), while models for sand, nitrogen, and potassium showed moderately good performances (R2 values between 0.69 and 0.77). The SWIR subset and SVN + DT processing yielded the best PLSR models for both the PG and CP setups. VIS-NIR-SWIR reflectance spectroscopy shows promise as a technique for characterizing vineyard soils for precision viticulture purposes. Further studies will be carried out to corroborate our findings.

scholarly journals High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3723 ◽  
Author(s):  
Hacer Akpolat ◽  
Mark Barineau ◽  
Keith A. Jackson ◽  
Mehmet Z. Akpolat ◽  
David M. Francis ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
High Performance ◽  
Prediction Models ◽  
Least Squares Regression ◽  
Family Farms ◽  
Non Invasive ◽  
Uv Visible ◽  
The Ohio State University ◽  
Non Destructive ◽  
Β Carotene

Our objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-trans-lycopene and β-carotene levels were measured with a UV-visible spectrophotometer, and prediction models were developed using PLSR and ANN. Regression models developed with Raman spectra provided excellent prediction performance by ANN (rpre = 0.9, SEP = 1.1 mg/100 g) and PLSR (rpre = 0.87, SEP = 2.4 mg/100 g) for non-invasive determination of all-trans-lycopene in fruits. Although the number of samples were limited for β-carotene quantification, PLSR modeling showed promising results (rcv = 0.99, SECV = 0.28 mg/100 g). Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with novel profiles and for separating orange varieties with distinct carotenoids (high in β-carotene and high in cis-lycopene).

scholarly journals Non-Invasive Monitoring of Ethanol and Methanol Levels in Grape-Derived Pisco Distillate by Vibrational Spectroscopy

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6278
Author(s):  
Ahmed Menevseoglu ◽  
Didem P. Aykas ◽  
Beatriz Hatta-Sakoda ◽  
Victor Hugo Toledo-Herrera ◽  
Luis E. Rodriguez-Saona
Keyword(s):  
Prediction Models ◽  
Least Squares Regression ◽  
Non Invasive ◽  
Calibration Models ◽  
Excitation Laser ◽  
Ft Ir ◽  
Online Stores ◽  
Non Destructive ◽  
Ft Ir Spectroscopy

Handheld Raman and portable FT-IR spectroscopy devices were evaluated for fast and non-invasive determination of methanol and ethanol levels in Peruvian Pisco. Commercial Peruvian Pisco (n = 171) samples were kindly provided by the UNALM Alliance for Research in Alcohol and its Derivatives (Lima, Peru) and supplemented by purchases at grocery and online stores. Pisco spectra were collected on handheld Raman spectrometers equipped with either a 1064 nm or a 785 nm excitation laser and a portable infrared unit operating in transmission mode. The alcohol levels were determined by GC–MS. Calibration models used partial least-squares regression (PLSR) to develop prediction algorithms. GC–MS data revealed that 10% of Pisco samples had ethanol levels lower than 38%, indicating possible water dilution. Methanol levels ranged from 10 to 130 mg/100 mL, well below the maximum levels allowed for fruit brandies. Handheld Raman equipped with a 1064 nm excitation laser gave the best results for determining ethanol (SEP = 1.2%; RPre = 0.95) and methanol (SEP = 1.8 mg/100 mL; RPre = 0.93). Randomly selected Pisco samples were spiked with methanol (75 to 2800 mg/100 mL), and their Raman spectra were collected through their genuine commercial bottles. The prediction models gave an excellent performance (SEP = 98 mg/100 mL; RPre = 0.97), allowing for the non-destructive and non-contact determination of methanol and ethanol concentrations without opening the bottles.

scholarly journals Quantitative Trait Loci Controlling Amounts and Types of Epicuticular Waxes in Onion

2014 ◽  
Vol 139 (5) ◽  
pp. 597-602 ◽  
Author(s):  
Steven J. Damon ◽  
Michael J. Havey
Keyword(s):  
Insect Pest ◽  
Epicuticular Wax ◽  
Thrips Tabaci ◽  
Gas Chromatography Mass Spectrometry ◽  
Chromosome 2 ◽  
Nucleotide Polymorphisms ◽  
Epicuticular Waxes ◽  
Onion Thrips ◽  
Chromosome 5 ◽  
Epicuticular Wax Biosynthesis

Natural variation exists in onion (Allium cepa L.) for amounts and types of epicuticular waxes on leaves. Wild-type waxy onion possesses copious amounts of these waxes, whereas the foliage of semiglossy and glossy phenotypes accumulates significantly less wax. Reduced amounts of epicuticular waxes have been associated with resistance to onion thrips (Thrips tabaci Lindeman), an important insect pest of onion. A segregating family from the cross of waxy and semiglossy onions was used to map single nucleotide polymorphisms (SNPs) and identify chromosome regions affecting amounts and types of epicuticular waxes as measured by gas chromatography–mass spectrometry. The amount of the primary epicuticular wax on onion leaves, hentriacontanone-16, was controlled by one region on chromosome 5. One region on chromosome 2 affected concentrations of several primary fatty alcohols. Results indicate that the region on chromosome 2 may be associated with the acyl reduction pathway, and the region on chromosome 5 may affect the decarbonylation pathway of epicuticular wax biosynthesis. Because lower amounts of epicuticular waxes are recessively inherited, SNPs tagging regions on chromosomes 2 and 5 will be useful for marker-assisted breeding to vary amounts and types of epicuticular waxes on onion foliage with the goal to develop cultivars resistant to onion thrips.

scholarly journals Variation for Epicuticular Waxes on Onion Foliage and Impacts on Numbers of Onion Thrips

2014 ◽  
Vol 139 (4) ◽  
pp. 495-501 ◽  
Author(s):  
Steven J. Damon ◽  
Russell L. Groves ◽  
Michael J. Havey
Keyword(s):  
Natural Variation ◽  
Thrips Tabaci ◽  
Gas Chromatography Mass Spectrometry ◽  
Epicuticular Waxes ◽  
Feeding Damage ◽  
Wild Type ◽  
Onion Thrips ◽  
Integrated Programs ◽  
Foliar Pathogens ◽  
Wax Crystals

Natural variation exists in onion (Allium cepa L.) for amounts of epicuticular waxes on foliage, and plants with lower amounts of these waxes suffer less feeding damage from onion thrips (Thrips tabaci Lind.). Wild-type onion possesses copious amounts of epicuticular waxes and is often referred to as “waxy.” The recessively inherited “glossy” phenotype has significantly less wax relative to waxy types and shows resistance to onion thrips but is vulnerable to spray damage, foliar pathogens, and excessive transpiration. Phenotypes visually intermediate between waxy and glossy also exist in onion, which we refer to as “semiglossy.” Epicuticular waxes on the leaves of glossy, semiglossy, and waxy onions were evaluated for appearance using scanning electron microscopy (SEM) and amounts and types were analyzed using gas chromatography/mass spectrometry. Wax crystals were clearly visible on the surface of waxy foliage with decreasing amounts on semiglossy and none on glossy leaves. The ketone hentriacontanone-16 was the most prevalent wax on leaves of waxy onion and was significantly (P < 0.01) less on semiglossy relative to waxy plants and on glossy relative to waxy and semiglossy plants. Numbers of adult and immature onion thrips were significantly reduced (P < 0.05) on glossy and/or semiglossy accessions relative to waxy in field and greenhouse cage experiments. These results indicate that semiglossy plants possess intermediate amounts of epicuticular waxes that may protect leaves from diseases or environmental stresses while still conferring resistance to onion thrips. Therefore, the semiglossy phenotype should be useful in integrated programs managing this important onion pest.

scholarly journals Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy

2021 ◽  
Vol 12 ◽  
Author(s):  
Irsa Ejaz ◽  
Siyang He ◽  
Wei Li ◽  
Naiyue Hu ◽  
Chaochen Tang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Prediction Models ◽  
Low Cost ◽  
Nir Spectroscopy ◽  
Grain Morphology ◽  
Whole Grains ◽  
Least Squares Regression ◽  
Sorghum Grains ◽  
Sorghum Grain ◽  
Non Destructive

Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Fourier-transform (FT) NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by FT-NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. This study aimed to provide a reference for the evaluation of sorghum grain biochemicals for food, feed, and fuel without destruction and complex chemical analysis.

scholarly journals Satellite Imagery for Monitoring and Mapping Soil Chromium Pollution in a Mine Waste Dump

2021 ◽  
Author(s):  
Vahid Khosravi ◽  
Faramarz Doulati Ardejani ◽  
Asa Gholizadeh ◽  
Mohammadmehdi Saberioon
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Near Infrared ◽  
Prediction Models ◽  
Fitness Function ◽  
Reflectance Spectroscopy ◽  
Landsat 8 ◽  
Least Squares Regression ◽  
Cr Concentration ◽  
Sentinel 2A

Weathering and oxidation of sulphide minerals in mine wastes release toxic elements in surrounding environments. As an alternative to traditional sampling and chemical analysis methods, the capability of proximal and remote sensing techniques was investigated in this study to predict Chromium (Cr) concentration in 120 soil samples collected from a dumpsite in Sarcheshmeh copper mine, Iran. The samples mineralogy and Cr concentration were determined and were then subjected to laboratory reflectance spectroscopy in the range of Visible--Near Infrared--Shortwave Infrared (VNIR–SWIR: 350–2500 nm). The raw spectra were pre-processed using Savitzky–Golay First-Derivative (SG-FD) and Savitzky–Golay Second-Derivative (SG-SD) algorithms. The important wavelengths were determined using correlation analysis, Partial Least Squares Regression (PLSR) and Genetic Algorithm (GA). Artificial Neural Networks (ANN), Stepwise Multiple Linear Regression (SMLR) and PLSR data mining methods were applied to the selected spectral variables to assess Cr concentration. The developed models were then applied to the selected bands of Aster, Hyperion, Sentinel-2A and Landsat 8-OLI satellite images of the area. Afterwards, rasters obtained from the best prediction model were segmented using a binary fitness function. According to the outputs of the laboratory reflectance spectroscopy, the highest prediction accuracy was obtained using ANN applied to the SD pre-processed spectra with R2 = 0.91, RMSE = 8.73 mg.kg-1 and RPD = 2.76. SD-ANN also showed an acceptable performance on mapping the spatial distribution of Cr using Ordinary Kriging (OK) technique. Using satellite images, SD-SMLR provided the best prediction models with R2 values of 0.61 and 0.53 for Hyperion and Sentinel-2A, respectively. This led to the higher visual similarity of the segmented Hyperion and Sentinel-2A images with the Cr distribution map. The findings of this study indicated that applying the best prediction models obtained by spectroscopy to the selected wavebands of Hyperion and Sentinel-2A satellite imagery could be considered as a promising technique for rapid, cost-effective and eco-friendly assessment of Cr concentration in highly heterogeneous mining areas of Sarcheshmeh in Iran.

scholarly journals Early Detection of Sage (Salvia officinalis L.) Responses to Ozone Using Reflectance Spectroscopy

Plants ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 346 ◽  
Author(s):  
Marchica ◽  
Loré ◽  
Cotrozzi ◽  
Lorenzini ◽  
Nali ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Full Range ◽  
Vegetation Indices ◽  
Leaf Traits ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Spectral Models ◽  
Spectral Profiles ◽  
Salvia Officinalis L ◽  
The Impact

Advancements in techniques to rapidly and non-destructively detect the impact of tropospheric ozone (O3) on crops are required. This study demonstrates the capability of full-range (350–2500 nm) reflectance spectroscopy to characterize responses of asymptomatic sage leaves under an acute O3 exposure (200 ppb for 5 h). Using partial least squares regression, spectral models were developed for the estimation of several traits related to photosynthesis, the oxidative pressure induced by O3, and the antioxidant mechanisms adopted by plants to cope with the pollutant. Physiological traits were well predicted by spectroscopic models (average model goodness-of-fit for validation (R2): 0.65–0.90), whereas lower prediction performances were found for biochemical traits (R2: 0.42–0.71). Furthermore, even in the absence of visible symptoms, comparing the full-range spectral profiles, it was possible to distinguish with accuracy plants exposed to charcoal-filtered air from those exposed to O3. An O3 effect on sage spectra was detectable from 1 to 5 h from the beginning of the exposure, but ozonated plants quickly recovered after the fumigation. This O3-tolerance was confirmed by trends of vegetation indices and leaf traits derived from spectra, further highlighting the capability of reflectance spectroscopy to early detect the responses of crops to O3.

scholarly journals Genetic Analyses of Epicuticular Waxes Associated with the Glossy Foliage of ‘White Persian’ Onion

2020 ◽  
Vol 145 (1) ◽  
pp. 67-72 ◽  
Author(s):  
Eduardo D. Munaiz ◽  
Michael J. Havey
Keyword(s):  
Phenotypic Variation ◽  
Thrips Tabaci ◽  
Chromosome 8 ◽  
Chromosome 1 ◽  
Gas Chromatography Mass Spectrometry ◽  
Epicuticular Waxes ◽  
Onion Thrips ◽  
Genetic Analyses ◽  
Recessive Locus ◽  
The Cross

Onion (Allium cepa) plants with lower amounts of epicuticular waxes on foliage suffer less damage from the insect pest Thrips tabaci (onion thrips). Glossy onion accumulates significantly less epicuticular wax compared with wild-type “waxy” onion, and a single recessive locus (gl) has been proposed to condition this phenotype. Genetic analyses of types and amounts of epicuticular waxes were completed using two segregating families from the cross of the glossy inbreds B9885 and B9897 (both originally selected from the onion cultivar White Persian) with waxy inbred B8667 and semiglossy (intermediate amounts of waxes) inbred B5351, respectively. F2 progenies were grown in greenhouses and scored visually for foliar phenotypes, and amounts and types of epicuticular waxes were determined using gas chromatography-mass spectrometry (GCMS). For one F2 family from the cross of glossy B9885 by waxy B8667, visually scored glossy vs. waxy foliage fit a 1:3 ratio and the phenotype mapped to chromosome 8 of onion. This same region on chromosome 8 was significantly associated with amounts of the ketone hentriacontanone-16 (H16) and fatty alcohols 1-octacosanol (Oct1) and 1-triacontanol (Tri1). Visually scored F2 progeny from the cross of glossy B9897 × semiglossy B5351 did not fit expected models for one or two recessive loci. Significant quantitative trait loci (QTL) were revealed on chromosomes 5 and 8 controlling amounts of H16. Epistasis was detected between regions on chromosomes 1 and 8, and a 100-fold increase of H16 was conditioned by homozygous genotypes for the B5351 region on chromosome 1 and the B9885 region on chromosome 8. The three QTL model explained 41% of the phenotypic variation for amounts of H16 at logarithm of odds of 16.6. Amounts of Oct1 and Tri1 in the B9897 × B5351 family were associated with a major QTL on chromosome 1, explaining 37% to 46% of the phenotypic variation, respectively. This research demonstrates that glossy foliage of ‘White Persian’ onion is conditioned by a recessive locus on chromosome 8 for which we propose the name glwp. These results are important for selection of onion with unique profiles of epicuticular waxes to reduce losses resulting from onion thrips.

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