Raman Spectroscopy and Machine Learning for Agricultural Applications: Chemometric Assessment of Spectroscopic Signatures of Plants as the Essential Step Toward Digital Farming

Species identification of adult ixodid ticks by Raman spectroscopy of their feces

BACKGROUND

Ticks and tick-borne diseases pose significant challenges to cattle production, thus the species identification of ticks and knowledge on their presence, abundance, and dispersal are necessary for the development of effective control measures. The standard method of inspection for the presence of ticks is the visual and physical examination of restrained animals, but the limitations of human sight and touch can allow larval, nymphal, and unfed adult ticks to remain undetected due to their small size and site of attachment. However, Raman spectroscopy, an analytical tool widely used in agriculture and other sectors, shows promise for the identification of tick species in infested cattle. Raman spectroscopy is a non-invasive and efficient method that employs the interaction between molecules and light for the identification of the molecular constituents of specimens.

METHODS

Raman spectroscopy was employed to analyze the structure and composition of tick feces deposited on host skin and hair during blood-feeding. Feces of 12 species from a total of five genera and one subgenus of ixodid ticks were examined. Spectral data were subjected to partial least squares discriminant analysis, a machine-learning model. We also used Raman spectroscopy and the same analytical procedures to compare and evaluate feces of the horn fly Haematobia irritans after it fed on cattle.

RESULTS

Five genera and one sub-genus at overall true prediction rates ranging from 92.3 to 100% were identified from the Raman spectroscopy data of the tick feces. At the species level, Dermacentor albipictus, Dermacentor andersoni and Dermacentor variabilis at overall true prediction rates of 100, 99.3 and 100%, respectively, were identified. There were distinct differences between horn fly and tick feces with respect to blood and guanine vibrational frequencies. The overall true prediction rate for the separation of tick and horn fly feces was 98%.

CONCLUSIONS

Our findings highlight the utility of Raman spectroscopy for the reliable identification of tick species from their feces, and its potential application for the identification of ticks from infested cattle in the field.

Fourier-transform infrared spectroscopy: a universal optical sensing technique with auspicious application prospects in the diagnosis and management of autoimmune diseases

Autoimmune diseases (AIDs) are poorly understood clinical syndromes due to breakdown of immune tolerance towards specific types of self-antigens. They are generally associated with an inflammatory response mediated by lymphocytes T, autoantibodies or both. Ultimately, chronic inflammation culminates in tissue damages and clinical manifestations. AIDs affect 5% of the world population, and they represent the main cause of fatality in young to middle-aged females. In addition, the chronic nature of AIDs has a devastating impact on the patient's quality of life. It also places a heavy burden on the health care system. Establishing a rapid and accurate diagnosis is considered vital for an ideal medical management of these autoimmune disorders. However, for some AIDs, this task might be challenging. Vibrational spectroscopies, and more particularly Fourier-transform infrared (FTIR) spectroscopy, have emerged as universal analytical techniques with promising applications in the diagnosis of various types of malignancies and metabolic and infectious diseases. The high sensitivity of these optical sensing techniques and their minimal requirements for test reagents qualify them to be ideal analytical techniques. The aim of the current review is to explore the potential applications of FTIR spectroscopy in the diagnosis and management of most common AIDs. It also aims to demonstrate how this technique has contributed to deciphering the biochemical and physiopathological aspects of these chronic inflammatory diseases. The advantages that can be offered by this optical sensing technique over the traditional and gold standard methods used in the diagnosis of these autoimmune disorders have also been extensively discussed.

Raman imaging monitors the time-resolved response of A. thaliana to the artificial inhibition of PSII

The short-term (0-96 h) response of A. thaliana to the oxidative stress induced by PSII inhibitor metribuzin was examined using Raman spectroscopy. Whole leaves of wildtype (WT, Col-0) and ros1 mutant were scanned and changes in carotenoids were examined. Strong differences in Raman intensity distributions between WT and ros1 were observed. A stronger decrease of carotenoid v₁(C=C) band intensity across the leaf was observed in ros1 after 48 h of exposure to metribuzin. It can be assumed that higher sensitivity to oxidative stress in ros1 mutant results in significantly faster degradation of carotenoids.

Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases

Chronic liver diseases (CLDs) are a major public health problem. Despite the progress achieved in fighting against viral hepatitis, the emergence of non-alcoholic fatty liver disease might pose a serious challenge to the public's health in the coming decades. Medical management of CLDs represents a substantial burden on the public health infrastructures. The health care cost of these diseases is an additional burden that weighs heavily on the economies of developing countries. Effective management of CLDs requires the adoption of reliable and cost-effective screening and diagnosing methods to ensure early detection and accurate clinical assessment of these diseases. Vibrational spectroscopies have emerged as universal analytical methods with promising applications in various industrial and biomedical fields. These revolutionary analytical techniques rely on analyzing the interaction between a light beam and the test sample to generate a spectral fingerprint. This latter is defined by the analyte's chemical structure and the molecular vibrations of its functional groups. Raman spectroscopy and surface-enhanced Raman spectroscopy have been used in combination with various chemometric tests to diagnose a wide range of malignant, metabolic and infectious diseases. The aim of the current review is to cast light on the use of these optical sensing methods in the diagnosis of CLDs. The vast majority of research works that investigated the potential application of these spectroscopic techniques in screening and detecting CLDs were discussed here. The advantages and limitations of these modern analytical methods, as compared with the routine and gold standard diagnostic approaches, were also reviewed in details.

Non-Invasive and Confirmatory Differentiation of Hermaphrodite from Both Male and Female Cannabis Plants Using a Hand-Held Raman Spectrometer

Cannabis (Cannabis sativa L.) is a dioecious plant that produces both male and female inflorescences. In nature, male and female plants can be found with nearly equal frequency, which determines species out-crossing. In cannabis farming, only female plants are preferred due to their high yield of cannabinoids. In addition to unfavorable male plants, commercial production of cannabis faces the appearance of hermaphroditic inflorescences, species displaying both pistillate flowers and anthers. Such plants can out-cross female plants, simultaneously producing undesired seeds. The problem of hermaphroditic cannabis triggered a search for analytical tools that can be used for their rapid detection and identification. In this study, we investigate the potential of Raman spectroscopy (RS), an emerging sensing technique that can be used to probe plant biochemistry. Our results show that the biochemistry of male, female and hermaphroditic cannabis plants is drastically different which allows for their confirmatory identification using a hand-held Raman spectrometer. Furthermore, the coupling of machine learning approaches enables the identification of hermaphrodites with 98.7% accuracy, whereas both male and female plants can be identified with 100% accuracy. Considering the label-free, non-invasive and non-destructive nature of RS, the developed optical sensing approach can transform cannabis farming in the U.S. and overseas.