Raman-based identification of tick species (Ixodidae) by spectroscopic analysis of their feces.

Ticks are blood-feeding parasites that vector a large number of pathogens of medical and veterinary importance. There are strong connections between tick and pathogen species. Timely detection of certain tick species on cattle can cease the spread of numerous devastating diseases such as Bovine babiesiosis and anaplasmosis. Detection of ticks is currently performed by slow and laborious scout-based inspection of cattle. In this study, we investigated the possibility of identification of tick species (Ixodidae) based on spectroscopic signatures of their feces. We collected Raman spectra from individual grains of feces of seven different species of ticks. Our results show that Raman spectroscopy (RS) allows for highly accurate (above 90%) differentiation between tick species. Furthermore, RS can be used to predict the tick developmental stage and differentiate between nymphs, meta-nymphs and adult ticks. We have also demonstrated that diagnostics of tick species present on cattle can be achieved using a hand-held Raman spectrometer. These findings show that RS can be used for non-invasive, non-destructive and confirmatory on-site analysis of tick species present on cattle.

Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Salinity Stresses, Nitrogen, Phosphorus, and Potassium Deficiencies in Rice.

Proper management of nutrients in agricultural systems is critically important for maximizing crop yields while simultaneously minimizing the health and environmental impacts of pollution from fertilizers. These goals can be achieved by timely confirmatory diagnostics of nutrient deficiencies in plants, which enable precise administration of fertilizers and other supplementation in fields. Traditionally, nutrient diagnostics are performed by wet-laboratory analyses, which are both time- and labor-consuming. Unmanned aerial vehicle (UAV) and satellite imaging have offered a non-invasive alternative. However, these imaging approaches do not have sufficient specificity, and they are only capable of detecting symptomatic stages of nutrient deficiencies. Raman spectroscopy (RS) is a non-invasive and non-destructive technique that can be used for confirmatory detection and identification of both biotic and abiotic stresses on plants. Herein, we show the use of a hand-held Raman spectrometer for highly accurate pre-symptomatic diagnostics of nitrogen, phosphorus, and potassium deficiencies in rice (Oryza sativa). Moreover, we demonstrate that RS can also be used for pre symptomatic diagnostics of medium and high salinity stresses. A Raman-based analysis is fast (1 s required for spectral acquisition), portable (measurements can be taken directly in the field), and label-free (no chemicals are needed). These advantages will allow RS to transform agricultural practices, enabling precision agriculture in the near future.

Infrared analysis of hair dyeing and bleaching history.

Forensic examination of hair is commonly performed to trace its origin and make a connection between a suspect and a crime scene. Such examination is based on subjective microscopic analysis of hair. During the last decade, several spectroscopic approaches have been proposed to make forensic analysis of hair more robust and reliable. Surface-enhanced Raman and attenuated total internal reflection infrared spectroscopies allowed for detection and identification of dyes directly on hair and even differentiation between commercial brands of those colorants. However, these is a question that remains unanswered: can artificial dyes be detected on bleached hair or bleaching can be used to fully erase information about hair coloring? In this study, we report experimental results that provide a clear answer to this question. We show that infrared analysis can be used to differentiate between undyed bleached hair and hair that was colored with both permanent and semi-permanent dyes prior to bleaching. We also show that IR analysis can be used to distinguish between undyed unbleached and undyed bleached hair. We demonstrate that in combination with multivariate statistical analysis, IR analysis can be used to distinguish with 96-100% accuracy between those hair classes.

Raman Spectroscopy Enables Non-Invasive Identification of Peanut Genotypes and Value-Added Traits.

Identification of specific genotypes can be accomplished by visual recognition of their distinct phenotypical appearance, as well as DNA analysis. Visual identification (ID) of species is subjective and usually requires substantial taxonomic expertise. Genotyping and sequencing are destructive, time- and labor-consuming. In this study, we investigate the potential use of Raman spectroscopy (RS) as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of peanut genotypes. We show that chemometric analysis of peanut leaflet spectra provides accurate identification of different varieties. This same analysis can be used for prediction of nematode resistance and oleic-linoleic oil (O/L) ratio. Raman-based analysis of seeds provides accurate genotype identification in 95% of samples. Additionally, we present data on the identification of carbohydrates, proteins, fiber and other nutrients obtained from spectroscopic signatures of peanut seeds. These results demonstrate that RS allows for fast, accurate and non-invasive screening and selection of plants which can be used for precision breeding.

Non-invasive identification of potato varieties and prediction of the origin of tuber cultivation using spatially offset Raman spectroscopy.

High starch content, simplicity of cultivation, and high productivity make potatoes (Solanum tuberosum) a staple in the diet of people around the world. On average, potatoes are composed of 83% water and 12% carbohydrates, and the remaining 4% includes proteins, vitamins, and other trace elements. These proportions vary depending on the type of potato and location where they were cultivated. At the same time, the chemical composition determines the nutritional value of potato tubers and can be proved using various wet chemistry and spectroscopic methods. For instance, gravity measurements, as well as several different colorimetric assays, can be used to investigate the starch content. However, these approaches are indirect, often destructive, and time- and labor-consuming. This study reports on the use of Raman spectroscopy (RS) for completely non-invasive and non-destructive assessment of nutrient content of potato tubers. We also show that RS can be used to identify nine different potato varieties, as well as determine the origin of their cultivation. The portable nature of Raman-based identification of potato offers the possibility to perform such analysis directly upon potato harvesting to enable quick quality evaluation. Graphical abstract.

Non-invasive diagnostics of Liberibacter disease on tomatoes using a hand-held Raman spectrometer.

MAIN CONCLUSION: Hand-held Raman spectroscopy can be used for confirmatory, non-invasive and non-destructive detection and identification of two haplotypes of Liberibacter disease on tomatoes. Using this spectroscopic approach, structural changes in carotenoids, xylan, cellulose and pectin that are associ-ated with this bacterial disease can be determined. 'Candidatus Liberibacter solanacearum' (Lso) is a phloem-limited Gram-negative bacterium that infects crops worldwide. In North America, two haplotypes of Lso (LsoA and LsoB) are transmitted by the potato psyllid, Bactericera cockerelli (Sulc), and infect many solanaceous crops such as potato and tomato. Infected plants exhibit chlorosis, severe stunting, leaf cupping, and scorching. Polymerase chain reaction (PCR) and potato tuber frying are commonly used methods for diagnostics of the plant disease caused by Lso. However, they are time-consuming, costly, destructive to the sample, and often not sensitive enough to detect the pathogen in the early infection stage. Raman spectroscopy (RS) is a noninvasive, nondestructive, analytical technique, which probes chemical composition of analyzed samples. In this study, we demonstrate that Lso infection can be diagnosed by non-invasive spectroscopic analysis of tomato leaves three weeks following infection, before the development of aerial symptoms. In combination with chemometric analyses, Raman spectroscopy allows for 80% accurate diagnostics of Liberibacter disease caused by each of the two different haplotypes. This diagnostics approach is portable and sample agnostic, suggesting that it could be utilized for other crops and could be conducted autonomously.