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Food safety control is a key issue in the food and agriculture industries. For such purposes, developing miniaturized analytical methods is critical for enabling the rapid and sensitive detection of food supplements, allergens, and pollutants. Here, a novel bioanalytical methodology based on DNA-functionalized gold nanoparticles (AuNPs) and colorimetric detection was developed to detect the presence of sesame (a major allergen) through sesame seed DNA as a target, in food samples. The presence of sesame DNA induces controlled nanoparticle aggregation/desegregation, resulting in a color change (from blue to red) proportional to sesame DNA concentration. The incorporation of multicomponent nucleic acid enzymes (MNAzymes) in this strategy has been carried out to perform an isothermal signal amplification strategy to improve the sensitivity of detection. Also, open-source software for color analysis was used to ensure an unbiased visual color-change detection, enhancing detection accuracy and sensitivity and opening the possibility of performing a simple and decentralized analyte detection. The method successfully detected the presence of sesame DNA in sesame seed, sesame oil, olive oil, and sunflower oil. In brief, the developed approach constitutes a simple and affordable alternative to perform a highly sensitive detection of DNA in food without complex methodologies or the requirement of expensive instrumentation.

Sustainable dairy farms are characterised by the self-production of forage for animal feed. These farms are sometimes located near industrial areas, entailing a risk of food chain contamination with hazardous metals and polycyclic aromatic hydrocarbons (PAHs). Accordingly, evaluating the impact of pollution on forage and milk is of great interest. In this study, the effects of industrial factors on sustainable forage from 43 dairy farms and possible correlations between inorganic elements and PAHs were studied. Spearman's correlation and principal component analysis (PCA) were performed for the forage and milk. Most of the inorganic elements in the forage were below the maximum residual limits for cadmium (Cd) and lead (Pb), established in EU 2013/1275 and EU 2019/1869, respectively. However, arsenic (As) and mercury (Hg) levels were above their respective limits in the forage (EU 2019/1869). No milk samples exceeded the maximum residual limits for Pb (EU 488/2014) or Cd (EU 1881/2006) in dairy products. Heavy-weight PAHs (HW-PAHs, four or more aromatic rings) were detected in forage but not in milk. In the forage samples, HW-PAHs were positively correlated with Zn and Cd. In addition, some hazardous metals (chromium (Cr), iron (Fe), As, Hg, and Pb) also were positively correlated with Zn and Cd. Interestingly, no correlations were found between forage pollutants and milk, suggesting that these pollutants have a low transfer rate to milk. The PCA results highlighted the predominant contribution of PAHs to the global variance in forage samples collected at different distances from industrial areas. In milk, the contributions of hazardous metals and PAHs were more balanced than in forages. Finally, when distances to potential pollution sources were included in the PCA of forage samples, a negative correlation was observed between the former and the concentrations of HW-PAHs, Cd, and Zn, suggesting that thermal power plants and steel factory emissions were the main sources of polluting forage in this area.

One of the most consumed foods is milk and milk products, and guaranteeing the suitability of these products is one of the major concerns in our society. This has led to the development of numerous sensors to enhance quality controls in the food chain. However, this is not a simple task, because it is necessary to establish the parameters to be analyzed and often, not only one compound is responsible for food contamination or degradation. To attempt to address this problem, a multiplex analysis together with a non-directed (e.g., general parameters such as pH) analysis are the most relevant alternatives to identifying the safety of dairy food. In recent years, the use of new technologies in the development of devices/platforms with optical or electrochemical signals has accelerated and intensified the pursuit of systems that provide a simple, rapid, cost-effective, and/or multiparametric response to the presence of contaminants, markers of various diseases, and/or indicators of safety levels. However, achieving the simultaneous determination of two or more analytes in situ, in a single measurement, and in real time, using only one working ‘real sensor’, remains one of the most daunting challenges, primarily due to the complexity of the sample matrix. To address these requirements, different approaches have been explored. The state of the art on food safety sensors will be summarized in this review including optical, electrochemical, and other sensor-based detection methods such as magnetoelastic or mass-based sensors.

Food safety and quality are the first steps in the food chain. This work reports a miniaturized, low-cost, and easy-to-use near-infrared spectroscopy (NIRS) measurement system for alfalfa quality control. This is a significant challenge for dairy farm technicians and producers who need rapid and reliable knowledge of the forage quality on their farms. In most cases, the instrumentation suitable for these specifications is expensive and difficult to operate. The core of the proposed NIR spectroscopy measurement system is Texas Instruments’ NIRscan Nano evaluation module (EVM) spectrometer. This module has a large sensing area and high resolution, suitable for forage samples. To evaluate the feasibility of the prototype for analyzing agrifood samples, different ways of presenting the sample, intact or ground, were tested. The final objective of the research is not just to check the efficiency of the proposed system. It is also to determine the characteristics of the measurement system, and how to improve them for alfalfa quality control.

Potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs) frequently coexist in soils near industrial areas and sometimes in environmental compartments directly linked to feed (forage) and food (milk) production. However, the distribution of these pollutants along the dairy farm production chain is unclear. Here, we analyzed soil, forage, and milk samples from 16 livestock farms in Spain: several PTEs and PAHs were quantified. Farms were compared in terms of whether they were close to (5 km) industrial areas. The results showed that PTEs and PAHs were enriched in the soils and forages from farms close to industrial areas, but not in the milk. In the soil, the maximum concentrations of PTEs reached 141, 46.1, 3.67, 6.11, and 138 mg kg−1 for chromium, arsenic, cadmium, mercury, and lead, respectively, while fluoranthene (172.8 µg kg−1) and benzo(b)fluoranthene (177.4 µg kg−1) were the most abundant PAHs. Principal component analysis of the soil PTEs suggested common pollution sources for iron, arsenic, and lead. In the forage, the maximum contents of chromium, arsenic, cadmium, mercury, and lead were 32.8, 7.87, 1.31, 0.47, and 7.85 mg kg−1, respectively. The PAH found in the highest concentration in the feed forage was pyrene (120 µg kg−1). In the milk, the maximum PTE levels were much lower than in the soil or the feed forages: 74.1, 16.1, 0.12, 0.28, and 2.7 µg kg−1 for chromium, arsenic, cadmium, mercury, and lead, respectively. Neither of the two milk samples exceeded the 20 µg kg−1 limit for lead set in EU 1881/2006. Pyrene was the most abundant PAH found in the milk (39.4 µg kg−1), while high molecular weight PAHs were not detected. For PTEs, the results showed that soil–forage transfer factors were higher than forage–milk ratios. Our results suggest that soils and forages around farms near industries, as well as the milk produced from those farms, have generally low levels of PTE and PAH contaminants.

Adulterations of olive oil are performed by adding seed oils to this high-quality product, which are cheaper than olive oils. Food safety controls have been established by the European Union to avoid these episodes. Most of these methodologies require expensive equipment, time-consuming procedures, and expert personnel to execute. Near-infrared spectroscopy (NIRS) technology has many applications in the food processing industry. It analyzes food safety and quality parameters along the food chain. Using principal component analysis (PCA), the differences and similarities between olive oil and seed oils (sesame, sunflower, and flax oil) have been evaluated. To quantify the percentage of adulterated seed oil in olive oils, partial least squares (PLS) have been employed. A total of 96 samples of olive oil adulterated with seed oils were prepared. These samples were used to build a spectra library covering various mixtures containing seed oils and olive oil contents. Eighteen chemometric models were developed by combining the first and second derivatives with Standard Normal Variable (SNV) for scatter correction to classify and quantify seed oil adulteration and percentage. The results obtained for all seed oils show excellent coefficients of determination for calibration higher than 0.80. Because the instrumental aspects are not generally sufficiently addressed in the articles, we include a specific section on some key aspects of developing a high-performance and cost-effective NIR spectroscopy solution for fraud detection in olive oil. First, spectroscopy architectures are introduced, especially the Texas Instruments Digital Light Processing (DLP) technology for spectroscopy that has been used in this work. These results demonstrate that the portable prototype can be used as an effective tool to detect food fraud in liquid samples.

Breast milk is an optimal food that covers all the nutritional needs of the newborn. It is a dynamic fluid whose composition varies with lactation period. The neonatal units of hospitals have human milk banks, a service that analyzes, stores, and distributes donated human milk. This milk is used to feed premature infants (born before 32 weeks of gestation or weighing less than 1500 g) whose mothers, for some reason, cannot feed them with their own milk. Here, we aimed to develop near-infrared spectroscopy (NIRS) measures for the analysis of breast milk. For this purpose, we used a portable NIRS instrument scanning in the range of 1396–2396 nm to collect the spectra of milk samples. Then, different chemometrics were calculated to develop 18 calibration models with and without using derivatives and the standard normal variate. Once the calibration models were developed, the best treatments were selected according to the correlation coefficients (r2) and prediction errors (SECVs). The best results for the assayed macronutrients were obtained when no pre-treatment was applied to the NIR spectra of fat (r2 = 0.841, SECV = 0.51), raw protein (r2 = 0.512, SECV = 0.21), and carbohydrates (r2 = 0.741, SECV = 1.35). SNV plus the first derivative was applied to obtain satisfactory results for energy (r2 = 0.830, SECV = 9.60) quantification. The interpretation of the obtained results showed the richness of the NIRS spectra; moreover, the presence of specific bands for fat provided excellent statistics in quantitative models. These results demonstrated the ability of portable NIRS sensors in a methodology developed for the quality control of macronutrients in breast milk.

Aflatoxin M1 (AFM1) is one of the most widespread aflatoxins that can be present in the milk of lactating mammals. It can cause carcinogenicity, mutagenesis, teratogenesis, genotoxicity and immunosuppression. The WHO recommends reducing the AFM1 concentration in food products, so the European Commission has set a maximum allowable limit of 0.05 µg L−1 in milk and its products. Thus, there is a need to develop new methodologies to satisfy the demand for reliable, cost-effective, robust and sensitive AFM1 routine controls. In the present work, a competitive phosphorescent immunosensor for AFM1 quantification in milk, based on antibody–antigen recognition and Mn:ZnS quantum dots (d-QDs) as photoluminescent labels, has been developed. Two different assay strategies based on the use of d-QDs as labels of secondary antibodies (direct assay), or of a derivative species of the antigen AFM1-Bovine Serum Albumin (indirect assay) were compared in terms of analytical performance for AFM1 quantification. The best analytical results were obtained with the immunoassay format that uses d-QDs as tags of secondary antibodies (direct assay), and said design was finally selected. The selected immunosensor provided a detection limit for AFM1 quantification of only 0.002 µg L−1, which greatly satisfied the maximum tolerable limit of AFM1 in milk of 0.05 µg L−1. The accuracy, calculated as recovery of AFM1 in fortified skimmed milk samples, ranged from 81 to 90%, with relative standard deviations from 3% to 14%. These results bring to light the good performance of such phosphorescent biosensors as simple and fast alternatives to conventional chromatographic analytical methods.

Less than 30% of dairy cattle’s nitrogen ingested is retained in milk. Therefore, large amounts of nitrogen can be excreted in manure and urine with a potential environmental impact. In addition, some legume forages can be more susceptible to proteolysis during the silage process than grasses, and dairy cows fed these legume silages would excrete a larger quantity of nitrogen in slurry. The objectives of this work were to evaluate the amount of nitrogen excretion in dairy cows fed different protein levels and legume silages with a view to improve the slurry quality as a co-product that can be used as fertilizer. Two double 3 × 3 Latin square trials were carried out in order to study three different protein levels (high, medium, and low) and three different silages (grass, faba bean, and field pea). Dry matter intake, milk production, and composition were not affected by treatments. The excretion of ammonia-N in the urine was almost four times lower in the diet with the lowest protein level. The ammonia-N in the urine was twice as high with the pea silage than faba bean and grass silages. In conclusion, the diet containing 13% of protein meets the protein requirement for lactating cows producing 31 kg daily, with low nitrogen excretion in the urine, and the main pathway for the excretion of surplus nitrogen from legume silages is through urine and the metabolization of pea silage protein goes toward ammonia-N.

There is a growing interest in the development of sensitive, portable, and low-cost instrumentation for optical chemical (bio)sensing. Such instrumentation can allow real-time decision-making for industry, farmers, and researchers. The combination of optical fiber schemes, luminescence spectroscopy techniques, and new materials for sensor immobilization has allowed the growth of optical sensors. This article focuses on the development of low-cost optoelectronic instrumentation and measurement strategies for optical chemical (bio)sensing. Most of the articles in this field have focused on the chemical sensors themselves, although few have covered the design process for optoelectronic instrumentation. This article tries to fill this gap by presenting designs for real applications, as carried out by the authors. We also offer an introduction to the optical devices and optical measurement techniques used in this field to allow a full understanding of the applications.

A portable instrumental system was designed for the routine environmental monitoring of toxic volatile organic compounds (VOCs) in atmospheric conditions based on changes in the photoluminescence emission of semiconductor nanoparticles (quantum dots) entrapped in a sol-gel matrix as the solid sensing material. The sol-gel sensing material displayed a long-lived phosphorescent emission, which is quenched in the presence of trace levels of a volatile organic compound (acetone) in gaseous atmospheres. The developed instrument could measure and process the changes in the photoluminescence of the sensing material after exposure to gaseous acetone. The developed prototype device consists of a deep-ultraviolet ligtht-emitting diode (UV LED), which excites the chemical sensing material; an optical filter to remove scattered light and other non-desirable wavelengths; a photomultiplier tube (PMT) to convert the phosphorescence emission of the sensor phase to an electrical signal; and a microcontroller to correlate the signal with the analyte concentration. The developed prototype was evaluated for its ability to measure low levels of gaseous acetone in contaminated atmospheres with high sensitivity (detection limit: 9 ppm). The obtained results show the feasibility of this type of instrument for environmental analytical control purposes.

A total of 220 faecal pig and poultry samples, collected from different experimental trials were employed with the aim to demonstrate the suitability of Near Infrared Reflectance Spectroscopy (NIRS) technology for estimation of gross calorific value on faeces as output products in energy balances studies. NIR spectra from dried and grounded faeces samples were analyzed using a Foss NIRSystem 6500 instrument, scanning over the wavelength range 400-2500 nm. Validation studies for quantitative analytical models were carried out to estimate the relevance of method performance associated to reference values to obtain an appropriate, accuracy and precision. The results for prediction of gross calorific value (GCV) of NIRS calibrations obtained for individual species showed high correlation coefficients comparing chemical analysis and NIRS predictions, ranged from 0.92 to 0.97 for poultry and pig. For external validation, the ratio between the standard error of cross validation (SECV) and the standard error of prediction (SEP) varied between 0.73 and 0.86 for poultry and pig respectively, indicating a sufficiently precision of calibrations. In addition a global model to estimate GCV in both species was developed and externally validated. It showed correlation coefficients of 0.99 for calibration, 0.98 for cross-validation and 0.97 for external validation. Finally, relative uncertainty was calculated for NIRS developed prediction models with the final value when applying individual NIRS species model of 1.3% and 1.5% for NIRS global prediction. This study suggests that NIRS is a suitable and accurate method for the determination of GCV in faeces, decreasing cost, timeless and for convenient handling of unpleasant samples.

This study examines the relationship between subclinical ketosis (SCK) in dairy cows and the butyric acid content of the silage used in their feeding. Twenty commercial farms were monitored over a period of 12 months. The feed at each farm and the silages used in its ration were sampled monthly for proximal analysis and for volatile fatty acid analysis. A total of 2857 urine samples were taken from 1112 cows to examine the ketonuria from about 30 days prepartum to 100 postpartum. Wide variation was recorded in the quality of silages used in the preparation of diets. Approximately 80% of the urine samples analyzed had no detectable ketone bodies, 16% returned values indicative of slight SCK, and the remainder, 4%, showed symptoms of ketosis. Most of the cases of hyperkenuria were associated with the butyric acid content of the silage used (r2=0.56; P

There is a growing interest in the development of sensitive, portable, and low-cost instrumentation for optical chemical (bio)sensing. Such instrumentation can allow real-time decision-making for industry, farmers, and researchers. The combination of optical fiber schemes, luminescence spectroscopy techniques, and new materials for sensor immobilization has allowed the growth of optical sensors. This article focuses on the development of low-cost optoelectronic instrumentation and measurement strategies for optical chemical (bio)sensing. Most of the articles in this field have focused on the chemical sensors themselves, although few have covered the design process for optoelectronic instrumentation. This article tries to fill this gap by presenting designs for real applications, as carried out by the authors. We also offer an introduction to the optical devices and optical measurement techniques used in this field to allow a full understanding of the applications. [ABSTRACT FROM AUTHOR]