Drought Response of Rice in Northeastern Thailand Assessed via Fourier Transform Infrared Spectroscopy

2021 ◽  
Vol 74 ◽  
Author(s):  
Piyaporn Phansak ◽  
Supatcharee Siriwong ◽  
Nantawan Kanawapee ◽  
Kanjana Thumanu ◽  
Wuttichai Gunnula ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Drought Stress ◽  
Lignin Content ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Breeding Programs ◽  
Treatment Groups ◽  
Drought Tolerant ◽  
Relative Water ◽  
Rice Landrace

Abstract Drought isa major constraint in many rainfed areas and affects rice yield. We aimed to characterize the physiological changes in rice in response to drought using Fourier transform infrared (FTIR) spectroscopy. Eighty rice landrace seedlings were subjected to drought in the greenhouse using a PEG 6000. Physiological parameters, including total chlorophyll content, relative water content, electrolyte leakage, and biochemical changes were evaluated. Based on the FTIR results, the landraces were divided into three main groups: tolerant, moderately tolerant, and susceptible. Principal component analysis revealed spectral differences between the control and drought stress treatment groups. Lipid, pectin, and lignin content increased after drought stress. The biochemical components of plants at different drought tolerance levels were also compared. The lipid (CH2 and CH3), lignin (C=C), pectin (C=O), and protein (C=O, N–H) contents were the highest in the drought-tolerant cultivars, followed by the moderately tolerant and susceptible cultivars, respectively. Cultivar 17 and 49 were the most tolerant, and the functional groups were identified and characterized using FTIR. Overall, these results will be useful in selecting parental cultivars for rice breeding programs.

scholarly journals Differential Activity of Antioxidant Enzymes and Physiological Changes in Wheat (Triticum aestivum L.) Under Drought Stress

2019 ◽  
Vol 11 (2) ◽  
pp. 266-276
Author(s):  
Kamal MIRI-HESAR ◽  
Ali DADKHODAIE ◽  
Saideh DOROSTKAR ◽  
Bahram HEIDARI
Keyword(s):  
Water Stress ◽  
Drought Stress ◽  
Field Capacity ◽  
Triticum Aestivum L ◽  
Plant Production ◽  
Breeding Programs ◽  
Drought Tolerant ◽  
Severe Water Stress ◽  
Significant Difference ◽  
Relative Water

Drought stress is one of the most significant environmental factors restricting plant production all over the world. In arid and semi-arid regions where drought often causes serious problems, wheat is usually grown as a major crop and faces water stress. In order to study drought tolerance of wheat, an experiment with 34 genotypes including 11 local and commercial cultivars, 17 landraces, and six genotypes from International Maize and Wheat Improvement Center (CIMMYT) was conducted at the experimental station, School of Agriculture, Shiraz University, Iran in 2010-2011 growing season. Three different irrigation regimes (100%, 75% and 50% Field Capacity) were applied and physiological and biochemical traits were measured for which a significant difference was observed in genotypes. Under severe water stress, proline content and enzymes’ activities increased while the relative water content (RWC) and chlorophyll index decreased significantly in all genotypes. Of these indices, superoxide dismutase (SOD) and RWC were able to distinguish tolerant genotypes from sensitives. Moreover, yield index (YI) was useful in detecting tolerant genotypes. The drought susceptibility index (DSI) varied from 0.40 to 1.71 in genotypes. These results indicated that drought-tolerant genotypes could be selected based on high YI, RWC and SOD and low DSI. On the whole, the genotypes 31 (30ESWYT200), 29 (30ESWYT173) and 25 (Akbari) were identified to be tolerant and could be further used in downstream breeding programs for the improvement of wheat tolerance under water limited conditions.

scholarly journals Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2506 ◽  
Author(s):  
Yunfeng Chen ◽  
Yue Chen ◽  
Xuping Feng ◽  
Xufeng Yang ◽  
Jinnuo Zhang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Spectroscopic Technique ◽  
Variety Identification ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Discriminant Models ◽  
The Fourier Transform ◽  
Better Than

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000–550 cm−1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures

2020 ◽  
pp. 000370282096971
Author(s):  
Nataša Radosavljević Stevanović ◽  
Milena Jovanović ◽  
Federico Marini ◽  
Slavica Ražić
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Illegal Market ◽  
Ft Ir

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical “cutting” agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.

Evaluation of diverse cowpea [Vigna unguiculata (L.) Walp.] germplasm accessions for drought tolerance

2019 ◽  
Author(s):  
K.D. Nkoana ◽  
Abe Shegro Gerrano ◽  
E.T. Gwata
Keyword(s):  
Drought Stress ◽  
Drought Tolerance ◽  
Water Content ◽  
Relative Water Content ◽  
Evaluation Method ◽  
Moisture Stress ◽  
Proline Content ◽  
Drought Tolerant ◽  
Relative Water ◽  
Germplasm Accessions

The genetic potential for drought tolerance in cowpea within the small holder sector has not been fully exploited in South Africa. Thus, a drought evaluation experiment was conducted at the ARC-VOP to evaluate 28 cowpea germplasm accessions including two controls viz. IT96D-602 (drought tolerant) and TVU7778 (susceptible to drought) in the drought screening house using plastic box evaluation method in January, 2017. Genotypes raised for three weeks were subjected to 5 weeks of water stress treatment to determine their physiological response through leaf wilting index, relative water content and proline content followed by re-watering to determine genotype (s) with ability to recover from drought stress. Analyses of variance showed highly significant differences in response to moisture stress among the cowpea accessions for the selected physiological traits except for leaf wilting index at week two of drought stress. Stem greenness and recovery appeared to be a reliable indicator of drought tolerant genotypes which was readily observed in Acc1257, Acc1168, Acc2355, IT96D-602 and Acc5352 which also correlated significantly and positively with relative water content and proline content. The genotypes responded differently to drought stress indicating that there is sufficient genetic variability that can be utilized further in breeding for drought stress within the cowpea species.

Rapid Differentiation and Identification of Shigella sonnei and Escherichia coli O157: H7 by Fourier Transform Infrared Spectroscopy and Multivariate Statistical Analysis

2014 ◽  
Vol 926-930 ◽  
pp. 1116-1119 ◽  
Author(s):  
Li Jun Yang ◽  
Jing Wang ◽  
Zhao Jie Li ◽  
Xiao Hua Song ◽  
Yu Min Liu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Statistical Analysis ◽  
Fourier Transform Infrared Spectroscopy ◽  
Multivariate Statistical Analysis ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Shigella Sonnei ◽  
Multivariate Statistical ◽  
Simple Method

Fourier transform infrared spectroscopy (FTIR) combined with multivariate statistical analysis was applied to differentiate and identify Shigella sonnei and Escherichiacoli O157: H7. FTIR absorption spectra from 4000-600 cm-1 were collected from sampling 10 μL of bacterial suspention. The spectra between 1800 and 900 cm-1 highlighted the most distinctive variations and were the most useful for characterizing the selected microorganisms. Spectra of the two bacteria were noticeably segregated with distinct clustering by principal component analysis (PCA). Further more, another cluster model of hierarchical cluster analysis (HCA) was established and could also gave a good separation between the two bacteria. These results demonstrate that FTIR technology has considerable potential as a rapid, accurate and simple method for differentiating and identifying bacteria.

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