scholarly journals Prospector: A mobile application for portable, high‐throughput near‐infrared spectroscopy phenotyping

tppj ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Trevor W. Rife ◽  
Chaney Courtney ◽  
Jenna Hershberger ◽  
Michael Allen Gore ◽  
Mitchell Neilsen ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
High Throughput ◽  
Mobile Application ◽  
Near Infrared

scholarly journals Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dari F. Da ◽  
Ruth McCabe ◽  
Bernard M. Somé ◽  
Pedro M. Esperança ◽  
Katarzyna A. Sala ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Infrared Spectroscopy ◽  
Sensitivity And Specificity ◽  
Near Infrared Spectroscopy ◽  
High Throughput ◽  
Near Infrared ◽  
Field Conditions ◽  
Anopheles Coluzzii ◽  
Insect Vectors ◽  
Infection Status

AbstractThere is an urgent need for high throughput, affordable methods of detecting pathogens inside insect vectors to facilitate surveillance. Near-infrared spectroscopy (NIRS) has shown promise to detect arbovirus and malaria in the laboratory but has not been evaluated in field conditions. Here we investigate the ability of NIRS to identify Plasmodium falciparum in Anopheles coluzzii mosquitoes. NIRS models trained on laboratory-reared mosquitoes infected with wild malaria parasites can detect the parasite in comparable mosquitoes with moderate accuracy though fails to detect oocysts or sporozoites in naturally infected field caught mosquitoes. Models trained on field mosquitoes were unable to predict the infection status of other field mosquitoes. Restricting analyses to mosquitoes of uninfectious and highly-infectious status did improve predictions suggesting sensitivity and specificity may be better in mosquitoes with higher numbers of parasites. Detection of infection appears restricted to homogenous groups of mosquitoes diminishing NIRS utility for detecting malaria within mosquitoes.

Near Infrared Spectroscopy for High-Throughput Characterization of Shea Tree (Vitellaria paradoxa) Nut Fat Profiles

2010 ◽  
Vol 58 (13) ◽  
pp. 7811-7819 ◽  
Author(s):  
Fabrice Davrieux ◽  
François Allal ◽  
Georges Piombo ◽  
Bokary Kelly ◽  
John B. Okulo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
High Throughput ◽  
Near Infrared ◽  
Vitellaria Paradoxa ◽  
Shea Tree

scholarly journals Precise high-throughput online near-infrared spectroscopy assay to determine key cell wall features associated with sugarcane bagasse digestibility

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xinru Li ◽  
Fumin Ma ◽  
Chengping Liang ◽  
Maoyao Wang ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Cell Wall ◽  
Infrared Spectroscopy ◽  
Real Time ◽  
Near Infrared Spectroscopy ◽  
High Throughput ◽  
Large Scale ◽  
Near Infrared ◽  
Lignin Content ◽  
Cellulose Crystallinity ◽  
Sugarcane Germplasm

Abstract Background Sugarcane is one of the most crucial energy crops that produces high yields of sugar and lignocellulose. The cellulose crystallinity index (CrI) and lignin are the two kinds of key cell wall features that account for lignocellulose saccharification. Therefore, high-throughput screening of sugarcane germplasm with excellent cell wall features is considered a promising strategy to enhance bagasse digestibility. Recently, there has been research to explore near-infrared spectroscopy (NIRS) assays for the characterization of the corresponding wall features. However, due to the technical barriers of the offline strategy, it is difficult to apply for high-throughput real-time analyses. This study was therefore initiated to develop a high-throughput online NIRS assay to rapidly detect cellulose crystallinity, lignin content, and their related proportions in sugarcane, aiming to provide an efficient and feasible method for sugarcane cell wall feature evaluation. Results A total of 838 different sugarcane genotypes were collected at different growth stages during 2018 and 2019. A continuous variation distribution of the near-infrared spectrum was observed among these collections. Due to the very large diversity of CrI and lignin contents detected in the collected sugarcane samples, seven high-quality calibration models were developed through online NIRS calibration. All of the generated equations displayed coefficient of determination (R2) values greater than 0.8 and high ratio performance deviation (RPD) values of over 2.0 in calibration, internal cross-validation, and external validation. Remarkably, the equations for CrI and total lignin content exhibited RPD values as high as 2.56 and 2.55, respectively, indicating their excellent prediction capacity. An offline NIRS assay was also performed. Comparable calibration was observed between the offline and online NIRS analyses, suggesting that both strategies would be applicable to estimate cell wall characteristics. Nevertheless, as online NIRS assays offer tremendous advantages for large-scale real-time screening applications, it could be implied that they are a better option for high-throughput cell wall feature prediction. Conclusions This study, as an initial attempt, explored an online NIRS assay for the high-throughput assessment of key cell wall features in terms of CrI, lignin content, and their proportion in sugarcane. Consistent and precise calibration results were obtained with NIRS modeling, insinuating this strategy as a reliable approach for the large-scale screening of promising sugarcane germplasm for cell wall structure improvement and beyond.

scholarly journals A systematic high-throughput phenotyping assay for sugarcane stalk quality characterization by near-infrared spectroscopy

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Maoyao Wang ◽  
Xinru Li ◽  
Yinjuan Shen ◽  
Muhammad Adnan ◽  
Le Mao ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
High Throughput ◽  
Near Infrared ◽  
Soluble Sugar ◽  
Partial Least Square ◽  
Growth Stages ◽  
Sugarcane Stalk ◽  
High Throughput Phenotyping ◽  
Sugarcane Germplasm

Abstract Background Sugarcane (Saccharum officinarum L.) is an economically important crop with stalks as the harvest organs. Improvement in stalk quality is deemed a promising strategy for enhancing sugarcane production. However, the lack of efficient approaches for systematic evaluation of sugarcane germplasm largely limits improvements in stalk quality. This study is designed to develop a systematic near-infrared spectroscopy (NIRS) assay for high-throughput phenotyping of sugarcane stalk quality, thereby providing a feasible solution for precise evaluation of sugarcane germplasm. Results A total of 628 sugarcane accessions harvested at different growth stages before and after maturity were employed to take a high-throughput assay to determine sugarcane stalk quality. Based on high-performance anion chromatography (HPAEC-PAD), large variations in sugarcane stalk quality were detected in terms of biomass composition and the corresponding fundamental ratios. Online and offline NIRS modeling strategies were applied for multiple purpose calibration with partial least square (PLS) regression analysis. Consequently, 25 equations were generated with excellent determination coefficients (R2) and ratio performance deviation (RPD) values. Notably, for some observations, RPD values as high as 6.3 were observed, which indicated their exceptional performance and predictive capability. Conclusions This study provides a feasible method for consistent and high-throughput assessment of stalk quality in terms of moisture, soluble sugar, insoluble residue and the corresponding fundamental ratios. The proposed method permits large-scale screening of optimal sugarcane germplasm for sugarcane stalk quality breeding and beyond.

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