Identification tools as part of Feedsafety research: the case of ragwort

Ragwort (Senecio jacobaea) and related species of the genus Senecio are the main source of pyrrolizidine alkaloids. These plants grow in road verges, meadows and production fields and they show up in parties of roughage: grass and alfalfa. Monitoring can be carried out during the field production and harvesting stages. The final objective is to reject parties with a too high contamination level. Identification tools can support the decision to accept or refuse materials for the food production chain. A ragwort model has been developed for the mobile application Determinator. This identification model includes the relevant objects (species of the genus Senecio), and a range of so called confusing objects in order to minimise the chance of false positive identifications

Measurement uncertainty for detection of visual impurities in granular feed and food materials in relation to the investigated amount of material

The presence is regulated of visually detectable seeds from a selection of toxic plants and fungi mycelium bodies (sclerotia) in feed (Directive 2002/32/EC) and in food (Regulation (EC) 1881/2006). Homogenisation as typical for chemical analyses is not applicable, and dedicated approaches are needed for visual examination methods. Visual methods require two parameters to characterise measurement uncertainties for both unit counts and unit weights. A new approach is to divide approximately 2 kg of sample material into four subsamples of approximately 500 g and to separately examine the four subsamples for numbers and particle weights of seeds or sclerotia. This study is the first to produce datasets on inhomogeneity among subsamples of a sample for visually detectable undesirable substances. Analytical thresholds were calculated from a simulation model and bootstrap procedures based on our data. The analytical thresholds assuring a controlled false-negative rate of 5% for decisions in compliance with legal limits depend on the diversity of the unit counts and weights, the level of the legal limit and the amount of material examined initially in the step-wise approach, either one or two subsamples. A procedure is proposed for examination in practice where only two subsamples, or alternatively even only one subsample, would be examined. If the resulting level of contamination exceeds the relevant threshold additional subsamples need to be examined as well. In most of the investigated cases, analytical thresholds could be established for the examination of just one subsample (500 g) taken from a sample of 2 kg. However, for ergot sclerotia in food with a legal limit of 200 mg kg−1, at least two subsamples (1000 g) need to be examined in the first step. Other groups of visually detectable undesirable substances exist which need further attention

Measurement uncertainty for detection of visual impurities in granular feed and food materials in relation to the investigated amount of material

The presence is regulated of visually detectable seeds from a selection of toxic plants and fungi mycelium bodies (sclerotia) in feed (Directive 2002/32/EC) and in food (Regulation (EC) 1881/2006). Homogenisation as typical for chemical analyses is not applicable, and dedicated approaches are needed for visual examination methods. Visual methods require two parameters to characterise measurement uncertainties for both unit counts and unit weights. A new approach is to divide approximately 2 kg of sample material into four subsamples of approximately 500 g and to separately examine the four subsamples for numbers and particle weights of seeds or sclerotia. This study is the first to produce datasets on inhomogeneity among subsamples of a sample for visually detectable undesirable substances. Analytical thresholds were calculated from a simulation model and bootstrap procedures based on our data. The analytical thresholds assuring a controlled false-negative rate of 5% for decisions in compliance with legal limits depend on the diversity of the unit counts and weights, the level of the legal limit and the amount of material examined initially in the step-wise approach, either one or two subsamples. A procedure is proposed for examination in practice where only two subsamples, or alternatively even only one subsample, would be examined. If the resulting level of contamination exceeds the relevant threshold additional subsamples need to be examined as well. In most of the investigated cases, analytical thresholds could be established for the examination of just one subsample (500 g) taken from a sample of 2 kg. However, for ergot sclerotia in food with a legal limit of 200 mg kg−1, at least two subsamples (1000 g) need to be examined in the first step. Other groups of visually detectable undesirable substances exist which need further attention

Specificity of a novel TaqMan PCR method for detection of poultry DNA

After the Bovine Spongiform Encephalopathy (BSE) crisis emerged in 1985/1986, all processed animal proteins (PAPs) were finally banned for use in animal feed in the European Union. To partially lift this feed ban, paths for re-introduction of PAPs from species other than ruminants e.g. pig and poultry, are described in the Transmissible Spongiform Encephalopathies (TSE) Roadmap 2. Cannibalism, however, is still not allowed. Specific detection methods for pig and poultry meal and PAPs are prerequisites for reintroduction of pig and poultry processed animal proteins into animal feed. Developing a sensitive PCR method that specifically detects the taxonomically diverse and therefore artificial group ‘poultry’ and that does not detect other birds at the same time is a challenge. Here, a novel TaqMan PCR method for poultry detection is presented. The specificity of the poultry method against target and non-target species has been extensively investigated. The efficiency, linearity and sensitivity was tested using dilution series of chicken, turkey, duck and goose DNA isolated from meat and autoclaved meat as a model system for PAPs

Hyperspectral imaging as a novel system for the authentication of spices : A nutmeg case study

This study deals with the development of Nutmeg (Myristica fragrans Houtt.) authentication methodology using hyperspectral imaging. Fifteen authentic samples, seven adulterant materials (i.e. 1 pericarp, 1 shell, and 5 spent samples) and 31 retail samples were used for this purpose. Furthermore, another set of adulterated nutmeg samples were artificially prepared by mixing authentic material with spent powder (5–60%). A new handheld hyperspectral imaging system was applied to obtain hyperspectral information of nutmeg powder samples in the wavelength region of 400–1000 nm. Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Artificial Neural Network (ANN) models were applied for exploring the data, constructing the models, and authenticating the retail samples. The PCA showed successful spatial separation of authentic samples from adulterant materials. An ANN model predicted and showed the ability to detect adulteration at levels as low as 5% of added product-own material which was more accurate than PLS-DA model. Microscopic analysis was applied for comparison with hyperspectral imaging and to verify possible sample modification. It was concluded that the method applied here has good potential for the development of a visual quality control procedure for nutmeg powder authentication.</p

Hyperspectral imaging as a novel system for the authentication of spices : A nutmeg case study

This study deals with the development of Nutmeg (Myristica fragrans Houtt.) authentication methodology using hyperspectral imaging. Fifteen authentic samples, seven adulterant materials (i.e. 1 pericarp, 1 shell, and 5 spent samples) and 31 retail samples were used for this purpose. Furthermore, another set of adulterated nutmeg samples were artificially prepared by mixing authentic material with spent powder (5–60%). A new handheld hyperspectral imaging system was applied to obtain hyperspectral information of nutmeg powder samples in the wavelength region of 400–1000 nm. Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Artificial Neural Network (ANN) models were applied for exploring the data, constructing the models, and authenticating the retail samples. The PCA showed successful spatial separation of authentic samples from adulterant materials. An ANN model predicted and showed the ability to detect adulteration at levels as low as 5% of added product-own material which was more accurate than PLS-DA model. Microscopic analysis was applied for comparison with hyperspectral imaging and to verify possible sample modification. It was concluded that the method applied here has good potential for the development of a visual quality control procedure for nutmeg powder authentication.</p

The use of animal by-products in a circular bioeconomy: Time for a TSE road map 3?

In 2005 and 2010, the European Commission (EC) published two subsequent ‘Road Maps’ to provide options for relaxation of the bans on the application of animal proteins in feed. Since then, the food production system has changed considerably and demands for more sustainability and circularity are growing louder. Many relaxations envisioned in the second Road Map have by now been implemented, such as the use of processed animal proteins (PAPs) from poultry in pig feed and vice versa. However, some legislative changes, in particular concerning insects, had not been foreseen. In this article, we present a new vision on legislation for increased and improved use of animal by-products. Six current legislative principles are discussed for the bans on animal by-products as feed ingredients: feed bans; categorization of farmed animals; prohibition unless explicitly approved; approved processing techniques, the categorization of animal by-products, and monitoring methods. We provide a proposal for new guiding principles and future directions, and several concrete options for further relaxations. We argue that biological nature of farmed animals in terms of dietary preferences should be better recognised, that legal zero-tolerance limits should be expanded if safe, and that legislation should be revised and simplified

Applicability of the poultry qPCR method to detect DNA of poultry processed animal protein materials

After the Bovine Spongiform Encephalitis (BSE) crisis most processed animal proteins (PAPs) were banned from use in animal feed. For the foreseen reintroduction of pork PAPs in poultry feed, and poultry PAPs in pork feed and to comply with the species-to-species ban that prohibits cannibalism, a sensitive and specific TaqMan PCR detection method for poultry DNA has been designed and published. This poultry method is able to detect DNA of chicken, turkey, duck and geese in one PCR reaction. PAPs however, are a difficult and variable matrix. Therefore, the usability of the poultry method was investigated on a range of different poultry PAPs. It was shown that the poultry detection method is capable of detecting poultry DNA in eight out of nine different poultry PAPs mixed at a 0.1% level in chicken feed. The method can also detect at least 0.1% poultry PAPs mixed in pork PAPs. These results show that the poultry method fulfils the 0.1% detection limit requirement in the EU legislation.</p

Applicability of the poultry qPCR method to detect DNA of poultry processed animal protein materials

After the Bovine Spongiform Encephalitis (BSE) crisis most processed animal proteins (PAPs) were banned from use in animal feed. For the foreseen reintroduction of pork PAPs in poultry feed, and poultry PAPs in pork feed and to comply with the species-to-species ban that prohibits cannibalism, a sensitive and specific TaqMan PCR detection method for poultry DNA has been designed and published. This poultry method is able to detect DNA of chicken, turkey, duck and geese in one PCR reaction. PAPs however, are a difficult and variable matrix. Therefore, the usability of the poultry method was investigated on a range of different poultry PAPs. It was shown that the poultry detection method is capable of detecting poultry DNA in eight out of nine different poultry PAPs mixed at a 0.1% level in chicken feed. The method can also detect at least 0.1% poultry PAPs mixed in pork PAPs. These results show that the poultry method fulfils the 0.1% detection limit requirement in the EU legislation.</p