Visualizing the structural and chemical heterogeneity of fruit and vegetables using advanced imaging techniques: fundamentals, instrumental aspects, applications and future perspectives.

Fruit and vegetables (F&V) are vastly complicated products with highly diverse chemical and structural characteristics. Advanced imaging techniques either combine imaging with spectral information or can provide excellent tissue penetration, and enable the possibility to target, visualize and even qualify the chemical and physical (structural) heterogeneity within F&V. In this review, visible and/or near infrared hyperspectral imaging, Fourier transform infrared microspectroscopic imaging, Raman imaging, X-ray and magnetic resonance imaging to reveal chemical and structural information in a spatial context of F&V at the macro- (entire products), meso- (tissues), and micro- (individual cells) scales are comprehensively summarized. In addition, their basic concepts and operational procedures, particularly sample preparation and instrumental parameter adjustments, are addressed. Finally, future challenges and perspectives of these techniques are put forward. These imaging techniques are powerful tools to assess the biochemical and structural heterogeneity of F&V. Cost reduction, sensor fusion and data sharing platforms are future trends. More emphasis on aspects of knowledge and extension at the level of academia and research, especially on how to select techniques, choose operational parameters and prepare samples, are important to overcome barriers for the wider adoption of these techniques to improve the evaluation of F&V quality.

Hyperspectral imaging reveals chemical heterogeneity of fruit and vegetables.Imaging techniques provide spatial insights in fruit and vegetables at multiple scales.Future trends are cost reduction, sensor fusion and data sharing.Instrumental adjustment and sample preparation should receive more attention.

Spectroscopic and Theoretical Insights into H2 Activation on Uranium Monoxide: Homolytic H2 Cleavage Mediated by Intermediate OU(η2-H2).

Elucidating molecular-level interactions between dihydrogen (H2) and uranium oxides reveals fundamental insights into the intrinsic H2 activation mechanisms underlying processes such as heterogeneous catalysis over uranium oxides and corrosion of uranium induced by H2. Herein, the reactions of H2 with uranium monoxide (UO) molecules have been investigated via a combination of matrix-isolation infrared spectroscopy and quantum chemical calculations. A side-on bonded H2 complex, OU(η2-H2), is identified at 3733.7 and 800.3 cm-1. This species is regarded as a crucial intermediate along H2 activation pathways. Bonding analysis reveals cooperative U(π5f/6d) → H2(σ*) π// backdonation and U ← H2(σ) σ donation in OU(η2-H2) that facilitate the activation of the H2 moiety. Upon λ > 550 nm photoirradiation, OU(η2-H2) isomerizes into H2UO, indicating the homolytic H2 cleavage on UO. Mechanistic details of H2 adsorption and dissociation on UO molecules have been further elucidated.

Estimation of optical properties of turbid media using spatially resolved diffuse reflectance combined with LSTM-attention network.

The accurate estimation of the optical properties of turbid media by using a spatially resolved (SR) technique remains a challenging task due to measurement errors in the acquired spatially resolved diffuse reflectance (SRDR) and challenges in inversion model implementation. In this study, what we believe to be a novel data-driven model based on a long short-term memory network and attention mechanism (LSTM-attention network) combined with SRDR is proposed for the accurate estimation of the optical properties of turbid media. The proposed LSTM-attention network divides the SRDR profile into multiple consecutive and partially overlaps sub-intervals by using the sliding window technique, and uses the divided sub-intervals as the input of the LSTM modules. It then introduces an attention mechanism to evaluate the output of each module automatically and form a score coefficient, finally obtaining an accurate estimation of the optical properties. The proposed LSTM-attention network is trained with Monte Carlo (MC) simulation data to overcome the difficulty in preparing training (reference) samples with known optical properties. Experimental results of the MC simulation data showed that the mean relative error (MRE) with 5.59% for the absorption coefficient [with the mean absolute error (MAE) of 0.04 cm-1, coefficient of determination (R2) of 0.9982, and root mean square error (RMSE) of 0.058 cm-1] and 1.18% for the reduced scattering coefficient (with an MAE of 0.208 cm-1, R2 of 0.9996, and RMSE of 0.237 cm-1), which were significantly better than those of the three comparative models. The SRDR profiles of 36 liquid phantoms, collected using a hyperspectral imaging system that covered a wavelength range of 530-900 nm, were used to test the performance of the proposed model further. The results showed that the LSTM-attention model achieved the best performance (with the MRE of 14.89%, MAE of 0.022 cm-1, R2 of 0.9603, and RMSE of 0.026 cm-1 for the absorption coefficient; and the MRE of 9.76%, MAE of 0.732 cm-1, R2 of 0.9701, and RMSE of 1.470 cm-1for the reduced scattering coefficient). Therefore, SRDR combined with the LSTM-attention model provides an effective method for improving the estimation accuracy of the optical properties of turbid media.

C-O Bond Activation in Mononuclear Lanthanide Oxocarbonyl Complexes OLn(η2-CO) (Ln = La, Ce, Pr, and Nd).

Fundamental investigation of metal-CO interactions is of great importance for the development of high-performance catalysts to CO activation. Herein, a series of side-on bonded mononuclear lanthanide (Ln) oxocarbonyl complexes OLn(η2-CO) (Ln = La, Ce, Pr, and Nd) have been prepared and identified in solid argon matrices. The complexes exhibit uncommonly low C-O stretching bands near 1630 cm-1, indicating remarkable C-O bond activation in these Ln analogues. The η2-CO ligand in OLn(η2-CO) can be claimed as an anion on the basis of the experimental observations and quantum chemistry investigations, although the CO anion is commonly considered to be unstable with electron auto-detachment. The CO activation in OLn(η2-CO) is attributed to the photoinduced intramolecular charge transfer from LnO to CO rather than the generally accepted metal → CO π back-donation, which conforms to the traditional Dewar-Chatt-Duncanson motif. Energy decomposition analysis combined with natural orbitals for chemical valence calculations demonstrates that the bonding between LnO and η2-CO arises from the combination of dominant ionic forces (>76%) and normal Lewis "acid-base" interactions. The fundamental findings provide guidelines for the catalyst design of CO activation.

CO Oxidation to CO2 on Uranium Dioxide Molecules through Intermediate O2U(η1-CO).

Investigations on the reactions of uranium oxide molecules with CO offer new inspiration for the design of promising high-efficiency catalysts for CO activation using actinide materials. Herein, we contribute a combined matrix-isolation infrared spectroscopic and theoretical study of CO oxidation to CO2 on uranium dioxide (UO2) molecules in solid argon. The reaction intermediate O2U(η1-CO) is generated spontaneously at the bands of 1893.0, 870.6, and 801.3 cm-1 during codeposition and annealing. Upon the following irradiation, CO2 is substantially produced by the consumption of O2U(η1-CO), indicating the catalytic conversion of CO to CO2 through the intermediate O2U(η1-CO). In C18O isotopic substitution experiments, the yields of 16OC18O convincingly confirm that one of the oxygen atoms in CO2 derives from UO2. The reaction pathways are discussed based on the theoretical and experimental results.

A Novel Machine-Learning Framework Based on a Hierarchy of Dispute Models for the Identification of Fish Species Using Multi-Mode Spectroscopy.

Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis and polymerase chain reaction (PCR), are expensive and time-consuming, and require skilled technicians and specialized equipment. The combination of spectroscopy and machine learning presents a promising approach to overcome these challenges. In our study, we took a comprehensive approach by considering a total of 43 different fish species and employing three modes of spectroscopy: fluorescence (Fluor), and reflectance in the visible near-infrared (VNIR) and short-wave near-infrared (SWIR). To achieve higher accuracies, we developed a novel machine-learning framework, where groups of similar fish types were identified and specialized classifiers were trained for each group. The incorporation of global (single artificial intelligence for all species) and dispute classification models created a hierarchical decision process, yielding higher performances. For Fluor, VNIR, and SWIR, accuracies increased from 80%, 75%, and 49% to 83%, 81%, and 58%, respectively. Furthermore, certain species witnessed remarkable performance enhancements of up to 40% in single-mode identification. The fusion of all three spectroscopic modes further boosted the performance of the best single mode, averaged over all species, by 9%. Fish species mislabeling not only poses health-related risks due to contaminants, toxins, and allergens that could be life-threatening, but also gives rise to economic and environmental hazards and loss of nutritional benefits. Our proposed method can detect fish fraud as a real-time alternative to DNA barcoding and other standard methods. The hierarchical system of dispute models proposed in this work is a novel machine-learning tool not limited to this application, and can improve accuracy in any classification problem which contains a large number of classes.

Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence.

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and quadratic discriminant analyses, k-nearest neighbors, random forest, support vector machine, and linear regression, as well as ensemble and majority voting methods, were used to explore spectroscopy data measured on fillets and to train classification models to predict freshness. Our results show that multi-mode spectroscopy achieves 95% accuracy, improving the accuracies of the FL, VIS-NIR and SWIR single-mode spectroscopies by 26, 10 and 9%, respectively. We conclude that multi-mode spectroscopy and data fusion analysis has the potential to accurately assess freshness and predict shelf life for fish fillets and recommend this study be expanded to a larger number of species in the future.

Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review.

Food that contains lean meat powder (LMP) can cause human health issues, such as nausea, headaches, and even death for consumers. Traditional methods for detecting LMP residues in meat are often time-consuming and complex and lack sensitivity. This article provides a review of the research progress on the use of surface-enhanced Raman spectroscopy (SERS) technology for detecting residues of LMP in meat. The review also discusses several applications of SERS technology for detecting residues of LMP in meat, including the enhanced detection of LMP residues in meat based on single metal nanoparticles, combining metal nanoparticles with adsorbent materials, combining metal nanoparticles with immunizing and other chemicals, and combining the SERS technology with related techniques. As SERS technology continues to develop and improve, it is expected to become an even more widely used and effective tool for detecting residues of LMP in meat.

Matrix-Isolation Infrared Spectra and Electronic Structure Calculations for Dinitrogen Complexes with Uranium Trioxide Molecules UO3(η1-NN)1-4.

Investigations of the interactions of uranium trioxide (UO3) with other species are expected to provide a new perspective on its reaction and bonding behaviors. Herein, we present a combined matrix-isolation infrared spectroscopy and theoretical study of the geometries, vibrational frequencies, electronic structures, and bonding patterns for a series of dinitrogen (N2) complexes with UO3 moieties UO3(η1-NN)1-4. The complexes are prepared by reactions of laser-ablated uranium atoms with O2/N2 mixtures or laser-ablated UO3 molecules with N2 in solid argon. UO3(η1-NN)1-4 are classified as "nonclassical" metal-N2 complexes with increased Δν(N2) values according to the experimental observations and the computed blue-shifts of N-N stretching frequencies and N-N bond length contractions. Electronic structure analysis suggests that UO3(η1-NN)1-4 are σ-only complexes with a total lack of π-back-donation. The energy decomposition analysis combined with natural orbitals for chemical valence calculations reveal that the bonding between the UO3 moiety and N2 ligands in UO3(η1-NN)1-4 arises from the roughly equal electrostatic attractions and orbital mixings. The inspection of orbital interactions from pairwise contributions indicates that the strongest orbital stabilization comes from the σ-donations of the 4σ*- and 5σ-based ligand molecular orbitals (MOs) into the hybrid 7s/6dx2-y2 MO of the U center. The electron polarization induced by electrostatic effects in the Ninner ← Nouter direction provides complementary contributions to the orbital stabilization in UO3(η1-NN)1-4. In addition, the reactions of UO3 with N2 ligands and the origination of the nonclassical behavior in UO3(η1-NN)1-4 are discussed.

Insights into the Metal-CO Bond in O2M(η1-CO) (M = Cr, Mo, W, Nd, and U) Complexes.

Investigations on the structures and bonding properties of metal carbonyl compounds provide fundamental understandings on the origin of small-molecule activations. Herein, the geometry and bonding trends of a series of isovalent metal oxocarbonyl complexes O2M(η1-CO) (M = Cr, Mo, W, Nd, and U) were studied by combined matrix-isolation infrared spectroscopy and advanced quantum chemical calculations. The title complexes present red shift of C-O stretching bands in the range from 122 to 244 cm-1, indicating the difference of CO activation ability for the series of isovalent metal dioxides. Density functional theory calculations predict T-shaped structures with a C2v symmetry for all the title molecules. O2Nd(η1-CO) bears little resemblance to the other complexes in bonding characters because of the weak interactions between the NdO2 and CO moiety. For the other complexes, natural localized molecular orbital analysis reveals a gradual increase of covalent character in M-CO bonds along the metal series Cr → Mo → W→ U. Energy decomposition analysis with natural orbitals for chemical valence calculations demonstrates that the M-CO bonding patterns conform to the conventional Dewar-Chatt-Duncanson motif. The contributions from orbital interactions in total attractions increase from Cr (41.7%) to U (52.7%). The breakdown of the orbital term into pairwise interactions shows that contributions of the M ← CO σ donation decrease from Cr (59.2%) to U (28.4%), while the M → CO π* backdonation increases significantly from Cr (23.8%) to U (67.3%). The more effective overlap and the better energy matching of U 5f and U 6d valence orbitals with CO π* orbitals result in much stronger U → CO π backdonation than the other metal elements.

Intermediates of Carbon Monoxide Oxidation on Praseodymium Monoxide Molecules: Insights from Matrix-Isolation IR Spectroscopy and Quantum-Chemical Calculations.

Identifying reaction intermediates in gas-phase investigations will provide understanding for the related catalysts in fundamental aspects including bonding interactions of the reaction species, oxidation states (OSs) of the anchored atoms, and reaction mechanisms. Herein, carbon monoxide (CO) oxidation by praseodymium monoxide (PrO) molecules has been investigated as a model reaction in solid argon using matrix-isolation IR spectroscopy and quantum-chemical calculations. Two reaction intermediates, OPr(η1-CO) and OPr(η2-CO), have been trapped and characterized in argon matrixes. The intermediate OPr(η2-CO) shows an extremely low C-O stretching band at 1624.5 cm-1. Quantum-chemistry studies indicate that the bonding in OPr(η1-CO) is described as "donor-acceptor" interactions conforming to the Dewar-Chatt-Duncanson motif. However, the bonding in OPr(η2-CO) results evidently from a combination of dominant ionic forces and normal Lewis "acid-base" interactions. The electron density of the singly occupied bonding orbital is strongly polarized to the CO fragment in OPr(η2-CO). Electronic structure analysis suggests that the two captured species exhibit Pr(III) OSs. Besides, the pathways of CO oxidation have been discussed.

Handheld Multispectral Fluorescence Imaging System to Detect and Disinfect Surface Contamination.

Contamination inspection is an ongoing concern for food distributors, restaurant owners, caterers, and others who handle food. Food contamination must be prevented, and zero tolerance legal requirements and damage to the reputation of institutions or restaurants can be very costly. This paper introduces a new handheld fluorescence-based imaging system that can rapidly detect, disinfect, and document invisible organic residues and biofilms which may host pathogens. The contamination, sanitization inspection, and disinfection (CSI-D) system uses light at two fluorescence excitation wavelengths, ultraviolet C (UVC) at 275 nm and violet at 405 nm, for the detection of organic residues, including saliva and respiratory droplets. The 275 nm light is also utilized to disinfect pathogens commonly found within the contaminated residues. Efficacy testing of the neutralizing effects of the ultraviolet light was conducted for Aspergillus fumigatus, Streptococcus pneumoniae, and the influenza A virus (a fungus, a bacterium, and a virus, respectively, each commonly found in saliva and respiratory droplets). After the exposure to UVC light from the CSI-D, all three pathogens experienced deactivation (> 99.99%) in under ten seconds. Up to five-log reductions have also been shown within 10 s of UVC irradiation from the CSI-D system.

Detection of adulterated sugar with plastic packaging based on spatially offset Raman imaging.

BACKGROUND: The application of optical sensing technology in food adulteration detection has been extensively studied. However, due to the impact of packaging materials on the penetration depth of photons in foods and the interference from the optical properties of the packaging materials themselves, the use of optical sensing technology to detect packaged foods adulteration is still a well-known problem. RESULTS: The line-scan Raman imaging system was used to collect Raman hyperspectral images of adulterated sugars, made by mixing soft sugar and cheap glucose in seven different ratios. With the 0 and 3 mm (optimal offset distance) between line-laser source and scanning line, the Raman hyperspectral images of adulterated sugars covered by packaging plastic were acquired respectively. Using adulterated samples un-covered by packaging plastic as training samples, the Random Forest prediction model was developed, and excellent prediction performance was achieved for adulterated samples un-covered by packaging plastics. Compared with Raman data acquired with 0 mm offset distance, the performance of the prediction model was significantly improved, with 0.957 for coefficient of determination (R2 ), 0.413 for root mean square error of prediction (RMSEP), and 4.846 for residual predictive deviation (RPD), for adulterated samples with plastic packaging acquired with the 3 mm offset distance. CONCLUSIONS: The novel non-destructive method based on spatially offset Raman imaging technology, which can reduce the interference of packaging materials and enhance the signal of internal interesting materials, was proposed for detection of adulterated sugar with plastic packaging. The experiment results show that spatially offset imaging technology provides a candidate method for detecting adulteration of packaged foods. © 2021 Society of Chemical Industry.

Theoretical Insight into Coordination Chemistry of Am(VI) and Am(V) with Phenanthroline Ligand: Implications for High Oxidation State Based Minor Actinide Separation.

Despite continuing and burgeoning interest in americium (Am) coordination chemistry in recent years, investigations of the electronic structures and bonding chemistry of high oxidation state americium complexes and their implications for minor actinide separation remain relatively less explored to date. Here, we used density functional theory (DFT) to create high oxidation states of americium but experimentally feasible models of Am(V) and Am(VI) complexes of phenanthroline ligand (DAPhen) as [AmO2(L)]1+/2+ and [AmO3(L)]1+ (L = 2,9-bis[(N,N-dimethyl)-carbonyl]-1,10-phenanthroline (oxo-DAPhen, LO) and 2,9-bis[(N,N-dimethyl)-thio-carbonyl]-1,10-phenanthroline (thio-DAPhen, LS)), meanwhile comparing these with [UO2(L)]2+. On the basis of the calculations, the Am(V) and Am(VI) oxidation state are thermodynamically feasible and can be stabilized by DAPhen ligands. From a comparative study, the strength of thio-DAPhen in the separation of high oxidation state Am emerges better than does oxo-DAPhen, which relates to the nature, energy level, and spatial arrangement of their frontier orbitals. This study provides fundamental knowledge toward understanding the transuranic separations processes, which has implications in designing new, more selective extraction processes for the separation of Am from curium (Cm) as well as lanthanide.

Probing the Electronic Structure and Chemical Bonding of Uranium Nitride Complexes of NU-XO (X = C, N, O).

Uranium(III) compounds are very reactive and exhibit a broad range of chemical-bonding tendencies owing to the spatially diffused valence orbitals of uranium. A systematic study on the geometries, electronic structures, and chemical bonding of NU-XO (X = C, N, O) is performed using relativistic quantum chemistry approaches. The NU-CO and NU-NO complexes have an end-on structure, that is, (NU) (η1-CO) and (NU) (η1-NO), whereas NU-OO adopts a side-on ((NU) (η2-O2)) structure. The electronic structure analysis shows that UN exhibits efficient activation reactivity to molecules, especially to NO and O2, because of the significant U 7s/5f → XO 2π* electron transfer. Thus, the oxidation state of U is +V with the dianion ligand NO2- and O22- in NU-NO and NU-OO, respectively. Instead, U retains its usual +III oxidation state in NU-CO with a neutral CO ligand. The significant stability of NU-XO (X = C, N, O) is determined by the covalent U-X bonding which contains both X → U σ-, π-donation from the X lone pair and U 5f → XO 2π* back-donation contributions. The significant back-donation to the antibonding X-O 2π* orbital results in the obvious weakening of the X-O bonding.

Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror.

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm-1 of starch powder, and average increases of 2.04 times (for the band at 672 cm-1) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.

Through-packaging analysis of butter adulteration using line-scan spatially offset Raman spectroscopy.

Spectroscopic techniques for food quality analysis are limited to surface inspections and are highly affected by the superficial layers (skin or packaging material) of the food samples. The ability of spatially offset Raman spectroscopy (SORS) to obtain chemical information from below the surface of a sample makes it a promising candidate for the non-destructive analysis of the quality of packaged food. In the present study, we developed a line-scan SORS technique for obtaining the Raman spectra of packaged-food samples. This technique was used to quantify butter adulteration with margarine through two different types of packaging. Further, the significant commercial potential of the developed technique was demonstrated by its being able to discriminate between ten commercial varieties of butter and margarine whilst still in their original, unopened packaging. The results revealed that, while conventional backscattering Raman spectroscopy cannot penetrate the packaging, thus preventing its application to the quality analysis of packaged food, SORS analysis yielded excellent qualitative and quantitative analyses of butter samples. The partial least-square regression analysis predictive values for the SORS data exhibit correlation coefficient values of 0.95 and 0.92, associated with the prediction error 3.2 % and 3.9 % for cover-1 & 2, respectively. The developed system utilizes a laser line (ca. 14-cm wide) that enables the simultaneous collection of a large number of spectra from a sample. Thus, by averaging the spectra collected for a given sample, the signal-to-noise ratio of the final spectrum can be enhanced, which will then have a significant effect on the multivariate data analysis methods used for qualitative and/or qualitative analyses. This recently presented line-scan SORS technique could be applied to the development of high-throughput and real-time analysis techniques for determining the quality and authenticity various packaged agricultural products.

Ammonia Activation by Ce Atom: Matrix-Isolation FTIR and Theoretical Studies.

The activation of ammonia by cerium atom has been investigated in solid argon using infrared spectroscopy and density functional theoretical calculations. The results reveal that the spontaneous formation of CeNH3 complex on annealing is the initial step in the reactions of cerium atoms with ammonia. The CeNH3 complexes rearrange to generate the inserted HCeNH2 molecules on irradiation. A "triplet-singlet" spin conversion occurs along the reaction path in which HCeNH2 (3A″) isomerizes into H2CeNH (1A'). The H2CeNH molecules finally decompose to yield HCeN + H2 upon photolysis. The periodic trend and differences for the M + NH3 (M = Ti, Zr, Hf, Ce, Th) systems are discussed on the basis of the present and previous works. DFT calculations predict that the most stable ground state for HHfNH2 and HThNH2 is singlet due to the stronger relativistic effects in Hf and Th atoms, while that for HTiNH2, HZrNH2, and HCeNH2 is triplet. Besides, the H2-elimination process is different for Ce and M (Ti, Zr, Hf, Th) cases.

Pose Estimation of Sweet Pepper through Symmetry Axis Detection.

The space pose of fruits is necessary for accurate detachment in automatic harvesting. This study presents a novel pose estimation method for sweet pepper detachment. In this method, the normal to the local plane at each point in the sweet-pepper point cloud was first calculated. The point cloud was separated by a number of candidate planes, and the scores of each plane were then separately calculated using the scoring strategy. The plane with the lowest score was selected as the symmetry plane of the point cloud. The symmetry axis could be finally calculated from the selected symmetry plane, and the pose of sweet pepper in the space was obtained using the symmetry axis. The performance of the proposed method was evaluated by simulated and sweet-pepper cloud dataset tests. In the simulated test, the average angle error between the calculated symmetry and real axes was approximately 6.5°. In the sweet-pepper cloud dataset test, the average error was approximately 7.4° when the peduncle was removed. When the peduncle of sweet pepper was complete, the average error was approximately 6.9°. These results suggested that the proposed method was suitable for pose estimation of sweet peppers and could be adjusted for use with other fruits and vegetables.

A Simple Surface-Enhanced Raman Spectroscopic Method for on-Site Screening of Tetracycline Residue in Whole Milk.

Therapeutic and subtherapeutic use of veterinary drugs has increased the risk of residue contamination in animal food products. Antibiotics such as tetracycline are used for mastitis treatment of lactating cows. Milk expressed from treated cows before the withdrawal period has elapsed may contain tetracycline residue. This study developed a simple surface-enhanced Raman spectroscopic (SERS) method for on-site screening of tetracycline residue in milk and water. Six batches of silver colloid nanoparticles were prepared for surface enhancement measurement. Milk-tetracycline and water-tetracycline solutions were prepared at seven concentration levels (1000, 500, 100, 10, 1, 0.1, and 0.01 ppm) and spiked with silver colloid nanoparticles. A 785 nm Raman spectroscopic system was used for spectral measurement. Tetracycline vibrational modes were observed at 1285, 1317 and 1632 cm-1 in water-tetracycline solutions and 1322 and 1621 cm-1 (shifted from 1317 and 1632 cm-1, respectively) in milk-tetracycline solutions. Tetracycline residue concentration as low as 0.01 ppm was detected in both the solutions. The peak intensities at 1285 and 1322 cm-1 were used to estimate the tetracycline concentrations in water and milk with correlation coefficients of 0.92 for water and 0.88 for milk. Results indicate that this SERS method is a potential tool that can be used on-site at field production for qualitative and quantitative detection of tetracycline residues.