In-house validation of a visible and near infrared spectroscopy non-targeted method to support panel test of virgin olive oils.

In this study, an in-house validation of Visible and Near Infrared Spectroscopy was performed to distinguish between extra virgin olive oil (EVOO) and virgin olive oil (VOO). A total of 161 samples of olive oil of three different categories (EVOO, VOO and lampante (LOO)) were analysed by transflectance using a monochromator instrument. One-class models were initially developed using Partial Least Squares (PLS) Density Modelling to characterize EVOO and VOO category. Once the LOO samples were discriminated, linear and non-linear discriminant models were built to classify EVOO and VOO. Different data pre-treatments and variable selection algorithms were evaluated to establish the best models in terms of Correct Classification Rate (CCR). The best model, obtained after variable selection using PLS Discriminant Analysis, yielded CCR values of 82.35 % for EVOO and 66.67 % for VOO in external validation. These results confirmed that VIS + NIRS technology may be used to provide rapid, non-destructive preliminary screening of olive oil samples for categorization; suspect samples may then be analysed by official analytical methods.

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review.

Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.

Colostrum Quality Assessment in Dairy Goats: Use of an On-Farm Optical Refractometer.

Failure of passive immunity transfer is one of the main causes of increased susceptibility to infectious agents in newborn kids. To ensure successful transfer of passive immunity, kids need to be fed high-quality colostrum, containing an adequate concentration of IgG. This work evaluated the quality of colostrum obtained in the first 3 days postpartum from Malagueña dairy goats. The IgG concentration in colostrum was measured using an ELISA as a reference method, and it was estimated by optical refractometer. Colostrum composition in terms of fat and protein was also determined. The mean concentration of IgG was 36.6 ± 2.3 mg/mL, 22.4 ± 1.5 mg/mL and 8.4 ± 1.0 mg/mL on days 1, 2 and 3 after parturition, respectively. Brix values obtained using the optical refractometer were 23.2%, 18.6% and 14.1% for days 1, 2 and 3, respectively. In this population, 89% of goats produced high-quality colostrum with IgG concentrations of >20 mg/mL on the day of parturition, but this percentage declined dramatically over the following 2 days. The quality of the fresh colostrum estimated with the optical refractometer was positively correlated with those obtained using ELISA (r = 0.607, p = 0.001). This study highlights the importance of feeding first-day colostrum to newborn kids and demonstrates that the optical Brix refractometer is suitable for the on-farm estimation of IgG content in colostrum.

Optimisation of the predictive ability of NIR models to estimate nutritional parameters in elephant grass through LOCAL algorithms.

Elephant grass is a tropical forage widely used for livestock feed. The analytical techniques traditionally used for its nutritional evaluation are costly and time consuming. Alternatively, Near Infrared Spectroscopy (NIRS) technology has been used as a rapid analysis technique. However, in crops with high variability due to genetic improvement, predictive models quickly lose accuracy and must be recalibrated. The use of non-linear models such as LOCAL calibrations could mitigate these issues, although a number of parameters need to be optimized to obtain accurate results. The objective of this work was to compare the predictive results obtained with global NIRS calibrations and with LOCAL calibrations, paying special attention to the configuration parameters of the models. The results obtained showed that the prediction errors with the LOCAL models were between 1.6 and 17.5 % lower. The best results were obtained in most cases with a low number of selected samples (n = 100-250) and a high number of PLS terms (n = 20). This configuration allows a reduced computation time with high accuracy, becoming a valuable alternative for analytical determinations that require ruminal fluid, which would improve the welfare of the animals by avoiding the need to surgically prepare animals to estimate the nutritional value of the feeds.

Psychometric Properties of the Childbirth Expectation Questionnaire in a Sample of Spanish Pregnant Women / Las propiedades psicométricas del Cuestionario de Expectativas sobre el Parto en una muestra de mujeres españolas gestantes

Childbirth expectations during pregnancy are important factors related to birth satisfaction. The aim of this study is to validate the Childbirth Expectation Questionnaire (CEQ) in a sample of Spanish pregnant women; 231 women responded to the CEQ during their first trimester of pregnancy and 106 of them completed a re-test at the third trimester. Exploratory analyses with 1-to-6 factor solutions were carried out to investigate the internal structure of the CEQ. The three-factor solution (spousal support and control, medical support and environment, and labor pain and distress) showed the best properties in terms of model fit, number of items per factor, and item loadings. The internal consistency of scales was also good (.79 ≥ α ≤ .93). Test-retest analyses showed significant intercorrelations between expectations from the first to the third trimester of pregnancy. There is a need to assess childbirth expectations, and our results suggest that the CEQ is a valid and useful instrument to be used among Spanish pregnant women.

Las expectativas sobre el parto (evaluadas durante el embarazo) constituyen factores relevantes relacionados con la satisfacción del parto. El objetivo de este estudio es validar el Cuestionario de Expectativas sobre el Parto (CEQ según las siglas del nombre inglés) en una muestra de gestantes españolas. Un total de 231 mujeres cumplimentaron el CEQ durante el primer trimestre del embarazo y 106 de ellas cumplimentaron de nuevo el instrumento en el tercer trimestre. Se realizaron análisis exploratorios con soluciones factoriales de 1 a 6 factores para analizar la estructura interna del CEQ. La solución de tres factores (apoyo de la pareja y control, apoyo médico y ambiente y dolor durante el parto y malestar) mostró las mejores propiedades en cuanto a ajuste del modelo, número de ítems por factor y peso de los ítems. La consistencia interna de las escalas también fue buena (.79 ≥ α ≤ .93). Los análisis test-retest mostraron intercorrelaciones significativas entre las expectativas del primer y tercer trimestre del embarazo. Atendiendo a la necesidad de evaluar las expectativas sobre el parto, nuestros resultados sugieren que el CEQ es un instrumento válido y útil para ser utilizado en las gestantes españolas.

Transferring a large data library of fresh total mixed rations from a benchtop to 2 portable near-infrared spectrometers for on-farm real-time decisions.

This study was carried out using a spectral database consisting of 394 samples of fresh total mixed ration (TMR) from dairy farms located at Northern Spain. Cloning sets of different size and structure were evaluated for the transfer of the large TMR spectral database obtained on a Foss NIRSystems monochromator to 2 different portable near-infrared devices: one diode array instrument and another based on linear variable filters. The cloning matrix that produced the best matching between instruments was then used to transfer the TMR spectral library to the 2 portable instruments. Once the database had been transferred, calibration equations were developed to compare the predictive ability of the equations obtained in the benchtop and portable instruments. In comparison with the monochromator predictive ability, the calibration equations developed with the near-infrared portable instruments displayed a high and similar accuracy for most of the studied parameters related to TMR composition, enabling their use for predicting TMR quality at the farm level.

Recent Advances in Portable and Handheld NIR Spectrometers and Applications in Milk, Cheese and Dairy Powders.

Quality and safety monitoring in the dairy industry is required to ensure products meet a high-standard based on legislation and customer requirements. The need for non-destructive, low-cost and user-friendly process analytical technologies, targeted at operators (as the end-users) for routine product inspections is increasing. In recent years, the development and advances in sensing technologies have led to miniaturisation of near infrared (NIR) spectrometers to a new era. The new generation of miniaturised NIR analysers are designed as compact, small and lightweight devices with a low cost, providing a strong capability for on-site or on-farm product measurements. Applying portable and handheld NIR spectrometers in the dairy sector is increasing; however, little information is currently available on these applications and instrument performance. As a result, this review focuses on recent developments of handheld and portable NIR devices and its latest applications in the field of dairy, including chemical composition, on-site quality detection, and safety assurance (i.e., adulteration) in milk, cheese and dairy powders. Comparison of model performance between handheld and bench-top NIR spectrometers is also given. Lastly, challenges of current handheld/portable devices and future trends on implementing these devices in the dairy sector is discussed.

Fraud Detection in Batches of Sweet Almonds by Portable Near-Infrared Spectral Devices.

One of the key challenges for the almond industry is how to detect the presence of bitter almonds in commercial batches of sweet almonds. The main aim of this research is to assess the potential of near-infrared spectroscopy (NIRS) by means of using portable instruments in the industry to detect batches of sweet almonds which have been adulterated with bitter almonds. To achieve this, sweet almonds and non-sweet almonds (bitter almonds and mixtures of sweet almonds with different percentages (from 5% to 20%) of bitter almonds) were analysed using a new generation of portable spectrophotometers. Three strategies (only bitter almonds, bitter almonds and mixtures, and only mixtures) were used to optimise the construction of the non-sweet almond training set. Models developed using partial least squares-discriminant analysis (PLS-DA) correctly classified 86-100% of samples, depending on the instrument used and the strategy followed for constructing the non-sweet almond training set. These results confirm that NIR spectroscopy provides a reliable, accurate method for detecting the presence of bitter almonds in batches of sweet almonds, with up to 5% adulteration levels (lower levels should be tested in future studies), and that this technology can be readily used at the main steps of the production chain.

A longitudinal study exploring the evolution of pain during pregnancy and after delivery: does worry matter?

The aim of this study is to evaluate the evolution of pain through pregnancy until after delivery, as well as to explore the mediating role of pregnancy worries in this evolution of pain. We conducted a longitudinal cohort study. The convenience sample was evaluated on four separate occasions: in the first trimester of pregnancy (pain), during the third trimester (pain and worry), during labor (pain), and after birth (< 24 h; pain). The final sample included 120 pregnant women with a mean age of 31.29 years (SD = 4.9; range = [22, 42 years]). The results evidenced changes in pain over time (F = 13.31, p < .001). Pain severity increased in the third trimester compared to the first trimester (t = - 4.60; 95% CI = [- 1.31, - 0.52]; p < .001), while pain during the third trimester and pain after delivery were comparable (t = - 0.94; 95% CI = [- 1.02, 0.36]; p = .35). Pain during labor was uncorrelated with all other pain measures, so it was not included in the model. The results of the mediation analyses indicated a total effect of pain during pregnancy (first and third trimester) and worry on pain severity after delivery (B = 0.35; SE = 0.14; t = 2.43; 95% CI = [0.06, 0.65]; p = .017). Pregnancy worries (B = 0.14; SE = 0.07; 95% CI = [0.06, 0.29]), but not pain during the third trimester (B = 0.03; SE = 0.12; 95% CI = [- 0.17, 0.31]) mediated the relationship between pain during the first trimester and pain after delivery. These results support the need to reduce worry in pregnant mothers, especially when pain during the first trimester is high, to reduce the risk of pain after delivery.

Reduction of the Number of Samples for Cost-Effective Hyperspectral Grape Quality Predictive Models.

Developing chemometric models from near-infrared (NIR) spectra requires the use of a representative calibration set of the entire population. Therefore, generally, the calibration procedure requires a large number of resources. For that reason, there is a great interest in identifying the most spectrally representative samples within a large population set. In this study, principal component and hierarchical clustering analyses have been compared for their ability to provide different representative calibration sets. The calibration sets generated have been used to control the technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars. Finally, the accuracy and precision of the models obtained with these calibration sets resulted from the application of the selection algorithms studied have been compared with each other and with the whole set of samples using an external validation set. Most of the standard errors of prediction (SEP) in external validation obtained from the reduced data sets were not significantly different from those obtained using the whole data set. Moreover, sample subsets resulting from hierarchical clustering analysis appear to produce slightly better results.

Is the Association between Postpartum Depression and Early Maternal-Infant Relationships Contextually Determined by Avoidant Coping in the Mother?

This study analyzes the moderating role of avoidant coping (in early pregnancy) in the relationship between postpartum depressive (PPD) symptoms and maternal perceptions about mother-baby relations and self-confidence. Participants were 116 low-risk obstetric mothers (mean age = 31.2 years, SD = 3.95, range 23-42) who received care and gave birth at a Spanish public hospital. Measurements were made at two points in time: at first trimester of pregnancy (maternal avoidance coping) and four months after childbirth (PPD and maternal perceptions). Avoidant coping was associated with the perception of the baby as irritable and unstable (p = 0.003), including irritability during lactation (p = 0.041). Interaction effects of avoidant coping and postpartum depression were observed on the perception of the baby as irritable (p = 0.031) and with easy temperament (p = 0.002). Regarding the mother's self-confidence, avoidant coping was related to a lack of security in caring for the baby (p < 0.001) and had a moderating effect between PPD and mother's self-confidence (i.e., lack of security in caring for the baby, p =0.027; general security, p = 0.007). Interaction effects showed that the use of avoidant coping in the mother exacerbated the impact of PPD on the early mother-infant relationship.

An innovative non-targeted control system based on NIR spectral information for detecting non-compliant batches of sweet almonds.

Nowadays, there is growing awareness about the need to develop new methodologies to fight against deliberate fraud. This study explored the use of near infrared spectroscopy (NIRS) as an instantaneous, non-targeted method for detecting non-compliant products; in this case, when used to detect sweet almond batches adulterated with bitter almonds. For this purpose, we simulated the adulteration of batches by preparing four different types of mixed samples which contained 5%, 10%, 15% and 20% of bitter almonds, respectively, using 90 samples of sweet almonds and 50 samples of bitter almonds. For each of the adulteration percentages, 21 samples were produced. The samples were analysed using the Aurora and the Matrix-F spectrophotometers. The procedure initially constructed the desired standard or target using only the spectral information provided by the sweet almond population (control population). To achieve this, after principal components analysis, the spectral warning and action limits were calculated using the n-dimensional statistic Mahalanobis global distance. Next, the spectral distances from the product standard defined for those samples not belonging to the control population, including the adulterated sweet almonds, were calculated and represented as Shewhart control charts. The implementation of NIRS technology throughout the almond supply chain enabled to identify 87% (73/84) of the adulterated sweet almond batches. These findings suggest that NIRS technology and the use of spectral distances could enable to establish an innovative, non-targeted control system based only on spectral information to assess almond batches. This system allows to carry out conformity tests both in situ and online of the batches of almonds received and processed in the industry, as well as establishing fast, cost-efficient anti-fraud alert systems, which would help to reduce the number of batches to be analysed by expensive and time-consuming confirmatory methods.

Routine NIRS analysis methodology to predict quality and safety indexes in spinach plants during their growing season in the field.

Cultural practices and harvesting in spinach plants should be based not only on subjective indexes such as freshness and green colour, which are both related with the visual appearance of the plants, but also on objective indexes that can be quantified non-destructively. The aim of this research was to develop a methodology based on the use of near infrared spectroscopy to monitor routinely the growth process of the spinach plants in the field. Using the MicroNIR™ OnSite-W spectrophotometer, which is ideally suited for in situ analysis, 261 spinach plants were analysed. Initially, calibration models for dry matter, soluble solid and nitrate contents were developed using 1 spectrum per plant for dry matter content, and nine spectra per plant for the other two parameters. These models were then validated using the same number of spectra per plant as for calibration purposes. After that, to establish a procedure more suitable to routine analysis in the field, the models were validated with only one spectrum per plant and the suitability of the predictions was measured considering the global and neighbourhood Mahalanobis distances, whose control limit values were defined as inferior to 4.0 and 1.0, respectively. The results showed that once the calibration models were developed, only one spectrum per plant was enough to predict dry matter and nitrate contents successfully. Therefore, the methodology developed will allow us to monitor in real time the complete growth process and to take decisions about spinach cultivation based on internal quality and safety indexes.

Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy.

Iberian pig ham is one of several high value European food products that are the subject of significant attempts at fraud because of the high price differences between commercial categories. Iberian pig products are classified by the Spanish regulations into different categories, mainly depending on the feeding regime during the fattening phase and the race involved, being of Premium quality those products obtained from the animals fed with acorns and other natural resources. Most of the previous NIRS studies related to the Iberian pig have involved the use of at-line instruments to predict quantitative quality parameters. This paper explores the use of the NIR spectra (369 for training and 199 for validation) to classify samples according to the categories Premium (animals fed with acorn) and Non Premium (animals fed with compound feeds), using a MicroNIR™ Pro1700 microspectrometer to analyse individual carcasses in situ at the slaughterhouse line. Four discriminant methods were explored: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), Kernel Bayes and Logistic Regression. These are all discriminant methods that naturally produce classification probabilities to quantify the uncertainty of the results. Rules were tuned and methods compared using both classification error rates and a probability scoring rule. LDA gave the best results, attaining an overall accuracy of 93% and providing well-calibrated classification probabilities.

Predicting postpartum post-traumatic stress and depressive symptoms in low-risk women from distal and proximal factors: a biopsychosocial prospective study using structural equation modeling.

PURPOSE: Posttraumatic stress (PTSD) and depression (PPD) are common mental disorders in the postpartum that constitute a threat both to the mother and the baby. It is unclear whether both disorders share similar antecedents, which is important to plan efficient interventions. The goal of this study was to examine the contribution of set of biopsychosocial predictors on both PTSD and PPD. METHODS: The study design was prospective. The study was conducted at Hospital Universitario de Fuenlabrada, a public university hospital located in the south of Madrid (Spain). The sample was composed of 116 pregnant women with low pregnancy risk. STROBE reporting guidelines were followed. RESULTS: The multivariate results show that psychopathology severity assessed during the first trimester (ß = 0.50, p < .001) and the Apgar score 5 min after delivery (ß = - 0.19, p = .030) were the two variables to significantly contribute to postpartum depressive symptoms. Conversely, only satisfaction with home care after delivery was independently associated with postpartum posttraumatic stress (ß = - 0.26, p = .016). The proposed model explained 21.8% of the variance of postpartum depressive symptoms (p = .041) and 27.1% of the variance of posttraumatic stress symptoms (p = .014). CONCLUSION: Special attention should be given to shared and unique predictive factors of PDD and PTSD to develop effective prevention programs in perinatal care.

Welfare Quality® for dairy cows: towards a sensor-based assessment.

This Research Reflection addresses the possibilities for Welfare Quality® to evolve from an assessment method based on data gathered on punctual visits to the farm to an assessment method based on sensor data. This approach could provide continuous and objective data, while being less costly and time consuming. Precision Livestock Farming (PLF) technologies enabling the monitorisation of Welfare Quality® measures are reviewed and discussed. For those measures that cannot be assessed by current technologies, some options to be developed are proposed. Picturing future dairy farms, the need for multipurpose and non-invasive PLF technologies is stated, in order to avoid an excessive artificialisation of the production system. Social concerns regarding digitalisation are also discussed.

In situ ripening stages monitoring of Lamuyo pepper using a new-generation near-infrared spectroscopy sensor.

BACKGROUND: Near-infrared spectroscopy (NIRS) was used as a nondestructive sensor to assess the quality of freshly harvested Lamuyo peppers. One hundred and forty-four Lamuyo peppers, which were in a range of colors (green, chocolate, orange, and red) when harvested, were analyzed. In this study, the evolution of the main quality parameters during the harvest period was analyzed. Additionally, NIRS predictive models using a portable manual spectrophotometer to evaluate quality parameters together with color index were developed. Moreover, two procedures for taking near-infrared spectra were tested: (1) static, where point spectral readings were taken of around the equator of the fruit; (2) dynamic, where spectra were taken by scanning the entire length of the pepper. RESULTS: Green peppers and those harvested at the beginning of the campaign presented significantly lower values (P < 0.05) of dry matter, soluble solid contents, and titratable acidity, whereas those with red coloration and those harvested at the end of the campaign showed significantly higher values of these three quality parameters (P < 0.05). The predictive capacity of the NIRS models showed that the static mode proved to be the most suitable for measuring the quality of Lamuyo peppers. CONCLUSIONS: The viability of NIRS for measuring dry matter content and soluble solid contents in situ, using a new-generation NIRS sensor, was demonstrated. However, the high water content, the irregular shape of the fruit, and the fact that it is hollow inside all point to the need for using larger samples sets so as to increase the robustness of the models obtained. © 2019 Society of Chemical Industry.

Do maternal personality variables influence childbirth satisfaction? A longitudinal study in low-risk pregnancies.

To analyze the influence of maternal personality (big five personality, coping and childbirth expectations) on birth satisfaction. A longitudinal prospective design was used with 116 pregnant women during November 2014-December 2015 at a public hospital (Madrid, Spain) with three assessment stages: first trimester of pregnancy (personality factors), third trimester (childbirth expectations and coping strategies) and 48 hours after childbirth (labor satisfaction). The highest childbirth satisfaction scores were for professional support, support from partner and overall satisfaction. Higher childbirth satisfaction scores were found for vaginal births than for cesarean sections or instrumental births. Childbirth expectation dimensions showed the highest number of associations with childbirth satisfaction. Significant correlations were found between neuroticism and home assessment, agreeableness and environment, and openness to experience and overall satisfaction. Significant positive correlations were found between positive reappraisal and continuity, and negative correlations between avoidance coping and home assessment. Regression analyses showed the predictive role played by the type of birth, and the caregiving environment as childbirth expectation, and positive reappraisal and avoidance as coping strategies. These findings have important implications for health professionals who provide assistance to pregnant women through holistic models which include the assessment and adjustment of childbirth expectations.

Safety and quality issues in summer squashes using handheld portable NIRS sensors for real-time decision making and for on-vine monitoring.

BACKGROUND: Portable handheld near infrared spectroscopy (NIRS) instruments currently present enormous advantages in terms of size, weight, and robustness. They also provide fast, precise information that can be obtained in situ, and they represent a viable option for controlling vegetable safety and quality during the growth period. The aim of this research was to evaluate three handheld portable NIRS instruments for in situ and real-time analysis of intact summer squashes. Traditional methods were used to analyze 221 summer squashes, and this work was used to develop calibration models for morphological, safety, and quality parameters. The longitudinal distribution of nitrate content in summer squashes weighing over 400 g was also studied, and the evolution of this parameter during the harvest period was tracked to determine which summer squashes and which zones of the vegetables (peduncle, equatorial, or stylar) could be earmarked for baby-food production. RESULTS: The robustness of the calibration models confirmed the expectations raised by NIRS technology for morphological, safety, and quality control of individual summer squashes, and the models developed with the MicroNIR-1700 instrument were those that provided more accuracy and precision, being the peduncle zone the part with higher nitrate content. CONCLUSIONS: It is in the peduncle zone, therefore, where measurements of this parameter must be carried out to decide on the destination of the harvested product. Summer squashes picked at the end of the harvest are those that must be used for baby-food production. © 2019 Society of Chemical Industry.