Visible and near-infrared diffuse reflectance spectroscopy for fast qualitative and quantitative assessment of nectarine quality

[EN] Visible and near-infrared spectroscopy has been widely used as a non-invasive and rapid-assessment technique for the quality control of agricultural products. In this study, 325 samples of nectarines representing two commercial varieties, cv. 'Big Top' and cv. 'Magique', were analysed by visible and near-infrared diffuse reflectance spectroscopy (VIS-NIR). The spectral data were pre-treated and analysed to predict the internal quality of the samples and to discriminate between the two varieties. Good prediction of the internal quality of the samples, using partial least-squares regressions, was observed for both (R (2) (P) of 0.909 and 0.927 and RMSEP of 0.235 and 0.238 for cv. Big Top and Magique, respectively). Discriminant models, using linear discriminant and partial least-squares discriminant analyses, were built to classify the nectarines. Both methods provided good results with rates of 97.44 and 100% of correctly classified samples. The results indicated that visible and near-infrared techniques can be useful and simple methods for quality control and for the correct identification of nectarines in commercial lines as an alternative to the slower and less accurate manual classification.This work was partially funded by the Generalitat Valenciana through project AICO/2015/122 and by the INIA and FEDER funds through projects RTA2012-00062-C04-01 and 03, and RTA2015-00078-00-00. Victoria Lopez Cortes thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202). The authors are also grateful to Fruits de Ponent (Lerida) for providing the fruit.Cortes-Lopez, V.; Blasco Ivars, J.; Aleixos Borrás, MN.; Cubero García, S.; Talens Oliag, P. (2017). Visible and near-infrared diffuse reflectance spectroscopy for fast qualitative and quantitative assessment of nectarine quality. 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In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties

[EN] One of the most studied techniques for the non-destructive determination of the internal quality of fruits has been visible and nearinfrared (VIS-NIR) reflectance spectroscopy. This work evaluates a new non-destructive in-line VIS-NIR spectroscopy prototype for in-line identification of five apple varieties, with the advantage that it allows the spectra to be captured with the probe at the same distance from all the fruits regardless of their size. The prototype was tested using varieties with a similar appearance by acquiring the diffuse reflectance spectrum of the fruits travelling on the conveyor belt at a speed of 0.81 m/s which is nearly 1 fruit/s. Principal component analysis (PCA) was used to determine the variables that explain the most variance in the spectra. Seven principal components were then used to perform linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). QDA was found to be the best in-line classification method, achieving 98% and 85% success rates for red and yellow apple varieties, respectively. The results indicated that the in-line application of VIS-NIR spectroscopy that was developed is potentially feasible for the detection of apple varieties with an accuracy that is similar to or better than a laboratory system.This work was partially funded by the Generalitat Valenciana through project AICO/2015/122 and by INIA and FEDER funds through project RTA2015-00078-00-00. Victoria Cortes Lopez thanks the Spanish Ministry of Education, Culture and Sports for FPU grant (FPU13/04202).Cortes-Lopez, V.; Cubero-García, S.; Blasco Ivars, J.; Aleixos Borrás, MN.; Talens Oliag, P. (2019). In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties. Food and Bioprocess Technology. 12(6):1021-1030. https://doi.org/10.1007/s11947-019-02268-0S10211030126Aleixandre-Tudo, J. 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Classification of Apple varieties using near infrared reflectance spectroscopy and fuzzy discriminant C-Means clustering model. Journal of Food Process Engineering, 40, 1–7

A comparison between NIR and ATR-FTIR spectroscopy for varietal differentiation of Spanish intact almonds

[EN] The rapid and easy classification of almond varieties with similar morphology, different quality properties and, in most cases, different prices is interesting to protect both the almond industry and the consumers from fraud. Therefore, in this work, intact almond kernels from four Spanish varieties (`Guara¿, `Rumbeta¿, `Marcona¿ and `Planeta¿) were analysed using both near infrared (NIR) and attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. After spectra measurement, NIR and ATR-FTIR spectral data were pre-treated and employed to construct two classification methods (partial least square-discriminant analysis (PLS-DA) and quadratic discriminant analysis (QDA)) in order to check their ability to classify almonds according to their variety. The best overall accuracies (94.45%) were obtained with the PLS-DA model of ATR-FTIR and the QDA model of NIR data. These results confirm that both spectroscopic techniques, if the optimal statistical model is selected, are powerful tools to reliably discriminate almonds according to their varieties.Victoria Cortés López thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202). The authors wish to thank the cooperative Agricoop for kindly providing the samples used in the experiments. This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00.Cortes-Lopez, V.; Barat Baviera, JM.; Talens Oliag, P.; Blasco, J.; Lerma-García, MJ. (2018). A comparison between NIR and ATR-FTIR spectroscopy for varietal differentiation of Spanish intact almonds. Food Control. 94:241-248. https://doi.org/10.1016/j.foodcont.2018.07.020S2412489

Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review

[EN] Background: The increasing demand for quality assurance in agro-food production requires sophisticated analytical methods for in-line quality control. One of these techniques is visible and near-infrared (VIS-NIR) spectroscopy, which has low running costs, does not need sample preparation, and is non-destructive, environmentally friendly, and fast. Despite these advantages, only a limited amount of research has been conducted on VIS-NIR in-line applications to measure, control, and predict quality in fruits and vegetables. Scope and approach: The applicability of VIS-NIR spectroscopy for the off-line and in-line monitoring of quality in postharvest products has been addressed in this review. The document focuses on the comparison between the two processes for the same agro-food product, highlighting the main advantages and disadvantages, problems, solutions, and differences. Key findings and conclusions: VIS-NIR techniques, combined with chemometric methods, have shown great potential due to their fast detection speed, and the possibility of simultaneously predicting multiple quality parameters or distinguishing between products according to the objectives. Being able to automate processes is a great advantage compared to routine off-line analyses, mainly due to the savings achieved in time, material, and personnel. However, in numerous cases, in-line implementation has not been accomplished in the corresponding studies, hence the scarcity of real in-line applications. Recent demands, together with the advances being made in the technology and a reduction in the price of equipment, makes VIS-NIR technology an analytical alternative for continuous real-time food quality controls, which will become predominant in the next few years.This work was partially funded by INIA and FEDER funds through research project RTA2015-00078-00-00.Victoria Cortés López thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202).Cortes-Lopez, V.; Blasco Ivars, J.; Aleixos Borrás, MN.; Cubero-García, S.; Talens Oliag, P. (2019). Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review. Trends in Food Science & Technology. 85:138-148. https://doi.org/10.1016/j.tifs.2019.01.015S1381488

Clinical benefit of glasdegib plus low-dose cytarabine in patients with de novo and secondary acute myeloid leukemia: long-term analysis of a phase II randomized trial

This analysis from the phase II BRIGHT AML 1003 trial reports the long-term efficacy and safety of glasdegib + low-dose cytarabine (LDAC) in patients with acute myeloid leukemia ineligible for intensive chemotherapy. The multicenter, open-label study randomized (2:1) patients to receive glasdegib + LDAC (de novo, n = 38; secondary acute myeloid leukemia, n = 40) or LDAC alone (de novo, n = 18; secondary acute myeloid leukemia, n = 20). At the time of analysis, 90% of patients had died, with the longest follow-up since randomization 36 months. The combination of glasdegib and LDAC conferred superior overall survival (OS) versus LDAC alone; hazard ratio (HR) 0.495; (95% confidence interval [CI] 0.325–0.752); p = 0.0004; median OS was 8.3 versus 4.3 months. Improvement in OS was consistent across cytogenetic risk groups. In a post-hoc subgroup analysis, a survival trend with glasdegib + LDAC was observed in patients with de novo acute myeloid leukemia (HR 0.720; 95% CI 0.395– 1.312; p = 0.14; median OS 6.6 vs 4.3 months) and secondary acute myeloid leukemia (HR 0.287; 95% CI 0.151–0.548; p < 0.0001; median OS 9.1 vs 4.1 months). The incidence of adverse events in the glasdegib + LDAC arm decreased after 90 days’ therapy: 83.7% versus 98.7% during the first 90 days. Glasdegib + LDAC versus LDAC alone continued to demonstrate superior OS in patients with acute myeloid leukemia; the clinical benefit with glasdegib + LDAC was particularly prominent in patients with secondary acute myeloid leukemia. ClinicalTrials.gov identifier: NCT01546038

Integration of simultaneous tactile sensing and visible and near-infrared reflectance spectroscopy in a robot gripper for mango quality assessment

[EN] Development of non-destructive tools for determining mango ripeness would improve the quality of industrial production of the postharvest processes. This study addresses the creation of a new sensor that combines the capability of obtaining mechanical and optical properties of the fruit simultaneously. It has been integrated into a robot gripper that can handle the fruit obtaining non-destructive measurements of firmness, incorporating two spectrometer probes to simultaneously obtain reflectance properties in the visible and near-infrared, and two accelerometers attached to the rear side of two fingers. Partial least square regression was applied to different combinations of the spectral data obtained from the different sensors to determine the combination that provides the best results. Best prediction of ripening index was achieved using both spectral measurements and two finger accelerometer signals, with R2 P ¿ 0:832 and RMSEP of 0.520. These results demonstrate that simultaneous measurement and analysis of the data fusion set improve the robot gripper features, allowing assessment of the quality of the mangoes during pick and place operations.This work has been partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) and FEDER through research projects RTA2012-00062-C04-01, RTA2012-00062-C04-02, RTA2012-00062-C04-03, and by the Conselleria d' Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. V. Cortes thanks the Spanish MEC for the FPU grant (FPU13/04202).Cortes-Lopez, V.; Blanes Campos, C.; Blasco Ivars, J.; Ortiz Sánchez, MC.; Aleixos Borrás, MN.; Mellado Arteche, M.; Cubero García, S.... (2017). Integration of simultaneous tactile sensing and visible and near-infrared reflectance spectroscopy in a robot gripper for mango quality assessment. Biosystems Engineering. 162:112-123. doi:10.1016/j.biosystemseng.2017.08.005S11212316

Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy

[EN] Early control of fruit quality requires reliable and rapid determination techniques. Therefore, the food industry has a growing interest in non-destructive methods such as spectroscopy. The aim of this study was to evaluate the feasibility of visible and near-infrared (NIR) spectroscopy, in combination with multivariate analysis techniques, to predict the level and changes of astringency in intact and in the flesh of half cut persimmon fruits. The fruits were harvested and exposed to different treatments with 95 % CO2 at 20 ºC for 0, 6, 12, 18 and 24 h to obtain samples with different levels of astringency. A set of 98 fruits was used to develop the predictive models based on their spectral data and another external set of 42 fruit samples was used to validate the models. The models were created using the partial least squares regression (PLSR), support vector machine (SVM) and least squares support vector machine (LS-SVM). In general, the models with the best performance were those which included standard normal variate (SNV) in the pre-processing. The best model was the PLSR developed with SNV along with the first derivative (1-Der) pre-processing, created using the data obtained at six measurement points of the intact fruits and all wavelengths (R2=0.904 and RPD=3.26). Later, a successive projection algorithm (SPA) was applied to select the most effective wavelengths (EWs). Using the six points of measurement of the intact fruit and SNV together with the direct orthogonal signal correction (DOSC) pre-processing in the NIR spectra, 41 EWs were selected, achieving an R2 of 0.915 and an RPD of 3.46 for the PLSR model. These results suggest that this technology has potential for use as a feasible and cost-effective method for the non-destructive determination of astringency in persimmon fruits.This work has been partially funded by the Institute Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) through research projects RTA2012-00062-004-01/03, RTA2013-00043-C02, and RTA2015-00078-00-00 with the support of European FEDER funds, and by the Conselleria d' Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. V. Cortes thanks the Spanish MEC for the FPU grant (FPU13/04202).Cortés López, V.; Rodríguez Ortega, A.; Blasco Ivars, J.; Rey Solaz, B.; Besada, C.; Cubero García, S.; Salvador, A.... (2017). Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy. JOURNAL OF FOOD ENGINEERING. 204:27-37. doi:10.1016/j.jfoodeng.2017.02.017S273720

Insights into Structure-Activity Relationships of Somatostatin Analogs Containing Mesitylalanine.

The non-natural amino acid mesitylalanine (2,4,6-trimethyl-L-phenylalanine; Msa) has an electron-richer and a more conformationally restricted side-chain than that of its natural phenylalanine counterpart. Taking these properties into account, we have synthesized ten somatostatin analogs containing Msa residues in different key positions to modify the intrinsic conformational flexibility of the natural hormone. We have measured the binding affinity of these analogs and correlated it with the main conformations they populate in solution. NMR and computational analysis revealed that analogs containing one Msa residue were conformationally more restricted than somatostatin under similar experimental conditions. Furthermore, we were able to characterize the presence of a hairpin at the pharmacophore region and a non-covalent interaction between aromatic residues 6 and 11. In all cases, the inclusion of a D-Trp in the eighth position further stabilized the main conformation. Some of these peptides bound selectively to one or two somatostatin receptors with similar or even higher affinity than the natural hormone. However, we also found that multiple incorporations of Msa residues increased the life span of the peptides in serum but with a loss of conformational rigidity and binding affinity

Assessing Viral Abundance and Community Composition in Four Contrasting Regions of the Southern Ocean

We explored how changes of viral abundance and community composition among four contrasting regions in the Southern Ocean relied on physicochemical and microbiological traits. During January–February 2015, we visited areas north and south of the South Orkney Islands (NSO and SSO) characterized by low temperature and salinity and high inorganic nutrient concentration, north of South Georgia Island (NSG) and west of Anvers Island (WA), which have relatively higher temperatures and lower inorganic nutrient concentrations. Surface viral abundance (VA) was highest in NSG (21.50 ± 10.70 × 106 viruses mL−1) and lowest in SSO (2.96 ± 1.48 × 106 viruses mL−1). VA was positively correlated with temperature, prokaryote abundance and prokaryotic heterotrophic production, chlorophyll a, diatoms, haptophytes, fluorescent organic matter, and isoprene concentration, and was negatively correlated with inorganic nutrients (NO3−, SiO42−, PO43−), and dimethyl sulfide (DMS) concentrations. Viral communities determined by randomly amplified polymorphic DNA–polymerase chain reaction (RAPD-PCR) were grouped according to the sampling location, being more similar within them than among regions. The first two axes of a canonical correspondence analysis, including physicochemical (temperature, salinity, inorganic nutrients—NO3−, SiO42−, and dimethyl sulfoniopropionate -DMSP- and isoprene concentrations) and microbiological (chlorophyll a, haptophytes and diatom, and prokaryote abundance and prokaryotic heterotrophic production) factors accounted for 62.9% of the variance. The first axis, temperature-related, accounted for 33.8%; the second one, salinity-related, accounted for 29.1%. Thus, different environmental situations likely select different hosts for viruses, leading to distinct viral communities.En prens

Marine Carbonyl Sulfide (OCS) and Carbon Disulfide (CS\u3csub\u3e2\u3c/sub\u3e): A Compilation of Measurements in Seawater and the Marine Boundary Layer

Carbonyl sulfide (OCS) and carbon disulfide (CS2) are volatile sulfur gases that are naturally formed in seawater and exchanged with the atmosphere. OCS is the most abundant sulfur gas in the atmosphere, and CS2 is its most important precursor. They have attracted increased interest due to their direct (OCS) or indirect (CS2 via oxidation to OCS) contribution to the stratospheric sulfate aerosol layer. Furthermore, OCS serves as a proxy to constrain terrestrial CO2uptake by vegetation. Oceanic emissions of both gases contribute a major part to their atmospheric concentration. Here we present a database of previously published and unpublished (mainly shipborne) measurements in seawater and the marine boundary layer for both gases, available at https://doi.org/10.1594/PANGAEA.905430 (Lennartz et al., 2019). The database contains original measurements as well as data digitalized from figures in publications from 42 measurement campaigns, i.e., cruises or time series stations, ranging from 1982 to 2019. OCS data cover all ocean basins except for the Arctic Ocean, as well as all months of the year, while the CS2 dataset shows large gaps in spatial and temporal coverage. Concentrations are consistent across different sampling and analysis techniques for OCS. The database is intended to support the identification of global spatial and temporal patterns and to facilitate the evaluation of model simulations