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Raman spectroscopy, a fast, non-invasive, and label-free optical technique, has significantly advanced plant and food studies and precision agriculture by providing detailed molecular insights into biological tissues. Utilizing the Raman scattering effect generates unique spectral fingerprints that comprehensively analyze tissue composition, concentration, and molecular structure. These fingerprints are obtained without chemical additives or extensive sample preparation, making Raman spectroscopy particularly suitable for in-field applications. Technological enhancements such as surface-enhanced Raman scattering, Fourier-transform-Raman spectroscopy, and chemometrics have increased Raman spectroscopy sensitivity and precision. These and other advancements enable real-time monitoring of compound translocation within plants and improve the detection of chemical and biological contaminants, essential for food safety and crop optimization. Integrating Raman spectroscopy into agronomic practices is transformative and marks a shift toward more sustainable farming activities. It assesses crop quality - as well as the quality of the food that originated from crop production - early plant stress detection and supports targeted breeding programs. Advanced data processing techniques and machine learning integration efficiently handle complex spectral data, providing a dynamic and detailed view of food conditions and plant health under varying environmental and biological stresses. As global agriculture faces the dual challenges of increasing productivity and sustainability, Raman spectroscopy stands out as an indispensable tool, enhancing farming practices' precision, food safety, and environmental compatibility. This review is intended to select and briefly comment on outstanding literature to give researchers, students, and consultants a reference for works of literature in Raman spectroscopy mainly focused on plant, food, and agronomic sciences. © 2024 Society of Chemical Industry.

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BACKGROUND: Currently, the potential of FT-IR spectroscopy for rapid diagnosis of many pathologies has been demonstrated by numerous research studies including those targeting COVID-19 detection. However, the number of clinicians aware of this potential and who are willing to use spectroscopy in their clinics and hospitals is still negligible. In addition, lack of awareness creates a huge gap between clinicians and researchers involved in clinical translation of current FT-IR technology hence hindering initiatives to bring basic and applied research together for the direct benefit of patients. METHODS: Knowledge and medical training on FT-IR on the side of clinicians should be one of the first steps to be able to integrate it into the list of complementary exams which may be requested by health professionals. Countless FT-IR applications could have a life-changing impact on patients' lives, especially screening and diagnostic tests involving biofluids such as blood, saliva and urine which are routinely non-invasively or minimally-invasively. RESULTS: Blood may be the most difficult to obtain by the invasive method of collection, but much can be evaluated in its components, and areas such as hematology, infectiology, oncology and endocrinology can be directly benefited. Urine with a relatively simple collection method can provide pertinent information from the entire urinary system, including the actual condition of the kidneys. Saliva collection can be simpler for the patient and can provide information on diseases affecting the mouth and digestive system and can be used to diagnose diseases such as oral cancer in its early-stages. An unavoidable second step is the active involvement of industries to design robust and portable instruments for specific purposes, as the medical community requires user-friendly instruments of advanced computational algorithms. A third step resides in the legal situation involving the global use of the technique as a new diagnostic modality. CONCLUSIONS: It is important to note that decentralized funds for variety of technologies hinders the training of clinical and medical professionals for the use of newly arising technologies and affect the engagement of these professionals with technology developers. As a result of decentralized funding, research efforts are spread out over a range of technologies which take a long time to get validated and translated to the clinic. Partnership over similar groups of technologies and efforts to test the same technologies while overcoming barriers posed to technology validation in different areas around the globe may benefit the clinical/medical, research and industry community globally.

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The adjustments that occur during photosynthesis are correlated with morphological, biochemical, and photochemical changes during leaf development. Therefore, monitoring leaves, especially when pigment accumulation occurs, is crucial for monitoring organelles, cells, tissue, and whole-plant levels. However, accurately measuring these changes can be challenging. Thus, this study tests three hypotheses, whereby reflectance hyperspectroscopy and chlorophyll a fluorescence kinetics analyses can improve our understanding of the photosynthetic process in Codiaeum variegatum (L.) A. Juss, a plant with variegated leaves and different pigments. The analyses include morphological and pigment profiling, hyperspectral data, chlorophyll a fluorescence curves, and multivariate analyses using 23 JIP test parameters and 34 different vegetation indexes. The results show that photochemical reflectance index (PRI) is a useful vegetation index (VI) for monitoring biochemical and photochemical changes in leaves, as it strongly correlates with chlorophyll and nonphotochemical dissipation (Kn) parameters in chloroplasts. In addition, some vegetation indexes, such as the pigment-specific simple ratio (PSSRc), anthocyanin reflectance index (ARI1), ratio analysis of reflectance spectra (RARS), and structurally insensitive pigment index (SIPI), are highly correlated with morphological parameters and pigment levels, while PRI, moisture stress index (MSI), normalized difference photosynthetic (PVR), fluorescence ratio (FR), and normalized difference vegetation index (NDVI) are associated with photochemical components of photosynthesis. Combined with the JIP test analysis, our results showed that decreased damage to energy transfer in the electron transport chain is correlated with the accumulation of carotenoids, anthocyanins, flavonoids, and phenolic compounds in the leaves. Phenomenological energy flux modelling shows the highest changes in the photosynthetic apparatus based on PRI and SIPI when analyzed with Pearson's correlation, the hyperspectral vegetation index (HVI) algorithm, and the partial least squares (PLS) to select the most responsive wavelengths. These findings are significant for monitoring nonuniform leaves, particularly when leaves display high variation in pigment profiling in variegated and colorful leaves. This is the first study on the rapid and precise detection of morphological, biochemical, and photochemical changes combined with vegetation indexes for different optical spectroscopy techniques.

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Aim: The dose response in growth inhibition of Staphylococcus aureus treated with colloidal copper oxide nanoparticles (CuO-NP) was evaluated. Methods: An in vitro microbial viability assay was conducted with CuO-NP concentrations spreading over the 0.4-848.0 µg/ml range. The dose-response curve was modeled with a double Hill equation. UV-Visible absorption and photoluminescence spectroscopies allowed tracking concentration-dependent modifications in CuO-NP. Results: Two specific phases separated by the critical concentration of 26.5 µg/ml were observed in the dose-response curve, with each exhibiting proper IC50 parameters, Hill coefficients and relative amplitudes. Spectroscopy techniques reveal the occurrence of a concentration-triggered aggregation of CuO-NP starting from this critical concentration. Conclusion: The findings demonstrate a dose-related change in S. aureus sensitivity to CuO-NP, which probably arises from the aggregation of this agent.

Antibacterial agents are often used to stop the growth of bacteria such as Staphylococcus aureus (S. aureus). Copper oxide nanoparticles (CuO-NP) stand as a promising candidate for this purpose. Generally, the agent´s effectiveness is inspected following a dose-response curve in which de agent´s antibacterial response is plotted against its dose (concentration). In this work, employing an extended mathematical interpretation we were capable of discerning experimentally the existence of two stages of dose-response (biphasic dose-response) in the treatment of S. aureus with CuO-NP. These results in combination with insights from spectroscopic techniques lead to the understanding that the biphasic behavior arises from the aggregation of CuO-NP at high concentrations. Therefore, according to the adopted concentration to treat S. aureus, the agent can behave as a dispersed nanoparticle or as an aggregated nanoparticle. In summary, understanding whether antibacterial agents transform as a function of concentration is important in determining their practical applications.

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Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

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Prevention of secondary damage is an important goal in the treatment of severe neurological conditions, such as major head trauma or stroke. However, there is currently a lack of non-invasive methods for monitoring cerebral physiology. Diffuse optical methods have been proposed as an inexpensive, non-invasive bedside monitor capable of providing neurophysiology information in neurocritical patients. However, the reliability of the technique to provide accurate longitudinal measurement during the clinical evolution of a patient remains largely unaddressed. Here, we report on the translation of a hybrid diffuse optical system combining frequency domain diffuse optical spectroscopy (FD-DOS) and diffuse correlation spectroscopy (DCS) for real-time monitoring of cerebral physiology in a neuro intensive care unit (neuro-ICU). More specifically, we present a case study of a patient admitted with a high-grade aneurysmal subarachnoid hemorrhage, who was monitored throughout hospitalization. We show that the neurophysiological parameters measured by diffuse optics at the bedside are consistent with the clinical evolution of the patient at all the different stages following its brain lesion. These data provide support for clinical translation of DOS/DCS as a useful biomarker of neurophysiology in the neuro-ICU, particularly in locations where other clinical resources are limited.

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Optical spectroscopy techniques are crucial for the evaluation and use of quantum dots (QDs) in life and materials science. In that context, the fluorescence quantum yield (Φf) is an essential parameter in the assessment of the luminescent features of QDs. The fluorescence quantum yield can be defined as the ratio of the number of emitted photons to the number of absorbed photons by a luminescent material. In this chapter, we describe absolute and relative methods to measure the fluorescence quantum yield of QDs in solution phase. The advantages and limitations of the techniques are reviewed.

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The thermoxidation of biodiesel was monitored using different spectroscopic techniques: UV-Vis and MIR absorption, Raman spectroscopy, and visible fluorescence. As the oxidation progressed, the UV-Vis absorption spectra showed an increase in the spectral range between 34,000 and 26,000 cm-1, while two main fluorescence bands (under ultraviolet excitation) were observed at around 21,000 and 15,000 cm-1. The UV-Vis absorption and fluorescence intensities presented opposite behavior during the processes, irrespective of the temperature used (90, 140, or 190 °C). These effects could be explained by the consumption of natural antioxidants, followed by the formation of primary oxidation compounds. The Raman and MIR absorption results indicated the existence of a cis-trans isomerization effect, followed by the formation of hydroperoxides during the oxidation, with the behavior being the same as that revealed by the UV-Vis absorption and fluorescence analyses. The comparison, under the same conditions, of different spectroscopy techniques that can be used to monitor the stages of thermoxidation of soybean biofuel provides important information for selection of an appropriate technique for evaluating biodiesel integrity.

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The spectrum of the 0-0 band of the [Formula: see text] electronic transition of the N2 molecule presents a considerable difference in its distribution of intensities, as a function of the wave number, when the emission spectrum by glow discharge is compared to an amplified spontaneous emission (ASE) regime spectrum, commonly known as the N2 "laser". In the present paper, this particularity, due to gain of the transition, is analyzed from an experimental and theoretical point of view, and for the first time has its experimental and theoretical intensities fully compared. An experimental rotational spectrum is obtained for this transition and a model for the ASE intensities has been carried out in order to retrieve the experimental conditions. The theoretical calculations of the gain have been carried out through a model proposed by other authors, as explained in the article. For the comparison among the ASE experimental and theoretical intensities, the fast and slow relaxation approximations proposed have been used, being the first one that best reproduces the experimental spectrum. For the first time, the experimental and theoretical spectra are compared directly, allowing the precise determination of the vibrational coefficient of inversion and temperature, showing the possible problems arising from the approximation. A good agreement between experimental and theoretical results is observed showing the reasonable validity of the model for the gain.

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The bioactivity of propolis against several pathogens is well established, leading to the extensive consumption of that bee product to prevent diseases. Brazilian green propolis, collected by the species Apis mellifera, is one of the most consumed in the world. The chemical composition of green propolis is complex and it has been shown that it displays antioxidant, antimicrobial, anti-inflammatory and antitumor activities, especially due to the high content of Artepillin C. The molecule is a derivative of cinnamic acid with two prenylated groups, responsible for the improvement of the affinity of the compound for lipophilic environment. A carboxylic group (COOH) is also present in the molecule, making it a pH-sensitive compound and the pH-dependent structure of Artepillin C, may modulate its biological activity related to interactions with the cellular membrane of organisms and tissues. Molecular properties of Artepillin C on aqueous solution were examined by optical absorption, steady state and time-resolved fluorescence spectroscopies. Acid-base titration based on the spectral position of the near UV absorption band, resulted in the pKa value of 4.65 for the carboxylic group in Artepillin C. In acidic pH, below the pKa value, an absorption band raised around 350nm at Artepillin C concentration above 50µM, due to aggregation of the molecule. In neutral pH, with excitation at 310nm, Artepillin C presents dual emission at 400 and 450nm. In pH close to the pKa, the optical spectra show contribution from both protonated and deprotonated species. A three-exponential function was necessary to fit the intensity decays at the different pHs, dominated by a very short lifetime component, around 0.060ns. The fast decay resulted in emission before fluorescence depolarization, and in values of fluorescence anisotropy higher than could be expected for monomeric forms of the compound. The results give fundamental knowledge about the protonation-deprotonation state of the molecule, that may be relevant in processes mediated by biological membranes.

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PURPOSE: Near-infrared diffuse optical spectroscopy (DOS) has been recently used to predict neoadjuvant chemotherapy response (NAC). In the present study, we explore the change in blood-oxygen content using DOS to predict NAC response against breast cancer. MATERIALS AND METHODS: A total of 20 patients were enrolled and underwent DOS scan with blood-oxygen detection before each treatment cycle. The first DOS scan was performed before NAC treatment (pretreatment), and subsequent scans were performed after each NAC treatment circle. Changes in blood content and oxygen content by DOS were evaluated and compared with tumor size, and their changes were analyzed in response versus nonresponse group. RESULTS: Thirteen patients were classified into response and seven patients into nonresponse group. The tumor blood content value (-1.06 ± 0.43) and oxygen content value (0.48 ± 0.17) of DOS at pretreatment was significantly different from presurgery in response group (P < 0.05), but not in nonresponse group. In response group, the percentage change in blood content (median 91.19%) was significantly larger than tumor size (median 48.89%) (P = 0.0035), while in oxygen content (median 47.11%) is not (P = 0.2815). Comparing each cycle, the percentage change in blood content could distinguish responder from non-responder as early as after the first treatment cycle (19.1 versus 6.6%, P = 0.0265). Blood content percentage sensitivity was 76.9% and specificity was 85.7% (AUC 0.912), while oxygen content percentage sensitivity was 76.9% and specificity was 71.4% (AUC 0.797). CONCLUSION: Both blood and oxygen content measured by DOS could be used to discriminate responder to the treatment versus non-responder. Among the two, percentage change of blood content was more precise and earlier than that of oxygen content to predicted breast tumor response. The percentage change in blood content could distinguish responder from non-responder after the first treatment cycle.

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