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.

Potential of Stainless Steel Slag Waste in Manufacturing Self-Compacting Concrete.

The volume of slags generated from the steel industry is a source of possible resources which is constantly increasing. Specifically, in the production of stainless steel, specific and singular slags with unique characteristics are obtained, which allows considering an approach aimed at their use in new recycling ways. This work shows the feasibility of using stainless steel slag as a substitute for limestone filler in the manufacture of self-compacting concrete. The influence of different treatments applied to slags on physical and chemical properties was studied. On the other hand, the mechanical behaviour, as well as the durability acquired in self-compacting concrete, has been analysed. Very encouraging results were obtained, since this research demonstrates the possible application of this stainless steel slag as a construction material, improving sustainability and promoting circular economy processes, which are achieved through the minimisation of the waste disposal and accumulation.

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.

Pre-harvest screening on-vine of spinach quality and safety using NIRS technology.

The study sought to perform a non-destructive and in-situ quality evaluation of spinach plants using near infrared (NIR) spectroscopy in order to establish its suitability for different uses once harvested. Modified partial least square (MPLS) regression models using NIR spectra of intact spinach leaves were developed for nitrate, ascorbic acid and soluble solid contents. The residual predictive deviation (RPD) values were 1.29, 1.21 and 2.54 for nitrate, ascorbic acid and soluble solid contents, respectively. Later, this predictive capacity increased for nitrate content (RPDcv = 1.63) when new models were developed, taking into account the influence on the robustness of the model exercised by the simultaneity between the NIR and laboratory analyses. Subsequently, using partial least squares discriminant analysis (PLS-DA), the ability of NIRS technology to classify spinach as a function of nitrate content was tested. PLS-DA yielded percentages of correctly classified samples ranging from 73.08-76.92% for the class 'spinach able to be used fresh' to 85.71-73.08% for the class 'preserved, deep-frozen or frozen spinach, both for unbalanced and balanced models respectively, based on NH signal associated with proteins. Overall, the data supports the capability of NIR spectroscopy to establish the final destination of the production of spinach analysed on the plant, as a screening tool for important safety and quality parameters.