Use of Electrical Coductivity Sensors to monitor Health Status and Quality of Milk in Dairy Goats

Intramammary infection (IMI) can adversely affect, in dairy goats, milk quality and milk yield leading to high economical losses. Although somatic cell count (SCC) and microbiological tests could be valid approaches to detect IMI, other methods of IMI early detection may be useful to detect infected animals and to improve milk quality.The aim of this study was to test a new multivariate model developed with the fuzzy logic technology and based on the milk EC - acquired on-line for each gland by dedicated sensors - and on new qualitative and quantitative indexes derived from the spectrum of the recorded signals.Results obtained showed that the fuzzy logic model tested could achive better results than those already reached in dairy goat research. Nevertheless, further experiment and more field data could be useful to reach the best possible accuracy that this multivariate approach could show

First Evaluation of Infrared Thermography as a Tool for the Monitoring of Udder Health Status in Farms of Dairy Cows

The aim of the present study was to test infrared thermography (IRT), under field conditions, as a possible tool for the evaluation of cow udder health status. Thermographic images (n. 310) from different farms (n. 3) were collected and evaluated using a dedicated software application to calculate automatically and in a standardized way, thermographic indices of each udder. Results obtained have confirmed a significant relationship between udder surface skin temperature (USST) and classes of somatic cell count in collected milk samples. Sensitivity and specificity in the classification of udder health were: 78.6% and 77.9%, respectively, considering a level of somatic cell count (SCC) of 200,000 cells/mL as a threshold to classify a subclinical mastitis or 71.4% and 71.6%, respectively when a threshold of 400,000 cells/mL was adopted. Even though the sensitivity and specificity were lower than in other published papers dealing with non-automated analysis of IRT images, they were considered acceptable as a first field application of this new and developing technology. Future research will permit further improvements in the use of IRT, at farm level. Such improvements could be attained through further image processing and enhancement, and the application of indicators developed and tested in the present study with the purpose of developing a monitoring system for the automatic and early detection of mastitis in individual animals on commercial farms

Retarded germination of Nicotiana tabacum seeds following insertion of exogenous DNA mimics the seed persistent behavior

Tobacco seeds show a coat-imposed dormancy in which the seed envelope tissues (testa and endosperm) impose a physical constraint on the radicle protrusion. The germination-limiting process is represented by the endosperm rupture which is induced by cell-wall weakening. Transgenic tobacco seeds, obtained by insertion of exogenous genes codifying for seed-based oral vaccines (F18 and VT2eB), showed retarded germination with respect to the wild type and modified the expression of endogenous proteins. Morphological and proteomic analyses of wild type and transgenic seeds revealed new insights into factors influencing seed germination. Our data showed that the interference of exogenous DNA influences the germination rather than the dormancy release, by modifying the maturation process. Dry seeds of F18 and VT2eB transgenic lines accumulated a higher amount of reserve and stressâ\u80\u93related proteins with respect to the wild type. Moreover, the storage proteins accumulated in tobacco F18 and VT2eB dry seeds have structural properties that do not enable the early limited proteolysis observed in the wild type. Morphological observations by electron and light microscopy revealed a retarded mobilization of the storage material from protein and lipid bodies in transgenic seeds, thus impairing water imbibition and embryo elongation. In addition, both F18 and VT2eB dry seeds are more rounded than the wild type. Both the morphological and biochemical characteristics of transgenic seeds mimic the seed persistent profile, in which their roundness enables them to be buried in the soil, while the higher content of storage material enables the hypocotyl to elongate more and the cotyledons to emerge

Evaluation of antigens stability of tobacco seeds as edible vaccine against VTEC strains

Plants have represent a promising alternative for biopharmaceutical proteins (Ma et al., 2003; Rossi et al., 2014). Many plant based edible vaccines have been shown to be effective in inducing local immune responses (Rossi et al., 2013). Edible vaccines can activate both mucosal and systemic immunity, as they come in contact with the digestive tract lining. This dual effect would provide first-line defense against pathogens invading through the mucosa. The antigens are released in the intestines are taken up by M cells that are present over the Payer’s patches (in the ileum) and the gut associated lymphoid tissue (GALT). Edible vaccines represent an important worldwide goal for the prevention of the enteric diseases, also in livestock. In particular, the enteric infections are a significant clinical problem in pigs. Verocytotoxic Escherichia (E.) coli strains are responsible for serious enterotoxaemia that causes important economic losses in the pig industry. The production of a vaccine for oral administration of transgenic seeds could be a practical and efficient system to prevent the infection and to reduce the antibiotic use. This study was focused on tobacco plants, previously transformed by agroinfection for the seed-specific expression of antigenic proteins (F18 adhesive fimbriae and the B subunit of the Vt2e toxin) as model of edible vaccines against verocytotoxic E. coli strains. The dietary administration of transgenic tobacco seeds promotes a significant increase in the number of mucosal IgA-producing cells of the tunica propria in both small and large intestine in mice (Rossi et al., 2013). A protective effect of oral administration of transgenic tobacco seeds was also observed against verocytotoxic Escherichia coli infection in piglets (Rossi et al., 2014). The aim of this study was to assess the seed-expression stability, that is a important requirement in the vaccine production, of F 18 and Vt2e-B heterologous genes into the progeny of transformed tobacco plants

Use of the Electronic Nose as a Screening Tool for the Recognition of Durum Wheat Naturally Contaminated by Deoxynivalenol: A Preliminary Approach

Fungal contamination and the presence of related toxins is a widespread problem. Mycotoxin contamination has prompted many countries to establish appropriate tolerance levels. For instance, with the Commission Regulation (EC) N. 1881/2006, the European Commission fixed the limits for the main mycotoxins (and other contaminants) in food. Although valid analytical methods are being developed for regulatory purposes, a need exists for alternative screening methods that can detect mould and mycotoxin contamination of cereal grains with high sample throughput. In this study, a commercial electronic nose (EN) equipped with metal-oxide-semiconductor (MOS) sensors was used in combination with a trap and the thermal desorption technique, with the adoption of Tenax TA as an adsorbent material to discriminate between durum wheat whole-grain samples naturally contaminated with deoxynivalenol (DON) and non-contaminated samples. Each wheat sample was analysed with the EN at four different desorption temperatures (i.e., 180 °C, 200 °C, 220 °C, and 240 °C) and without a desorption pre-treatment. A 20-sample and a 122-sample dataset were processed by means of principal component analysis (PCA) and classified via classification and regression trees (CART). Results, validated with two different methods, showed that it was possible to classify wheat samples into three clusters based on the DON content proposed by the European legislation: (a) non-contaminated; (b) contaminated below the limit (DON < 1,750 μg/kg); (c) contaminated above the limit (DON > 1,750 μg/kg), with a classification error rate in prediction of 0% (for the 20-sample dataset) and 3.28% (for the 122-sample dataset)

First Results of a Detection Sensor for the Monitoring of Laying Hens Reared in a Commercial Organic Egg Production Farm Based on the Use of Infrared Technology

The development of a monitoring system to identify the presence of laying hens, in a closed room of a free-range commercial organic egg production farm, was the aim of this study. This monitoring system was based on the infrared (IR) technology and had, as final target, a possible reduction of atmospheric ammonia levels and bacterial load. Tests were carried out for three weeks and involved 7 ISA (Institut de Sélection Animale) brown laying hens. The first 5 days was used to set up the detection sensor, while the other 15 days were used to evaluate the accuracy of the resulting monitoring system, in terms of sensitivity and specificity. The setup procedure included the evaluation of different color background (CB) thresholds, used to discriminate the information contents of the thermographic images. At the end of this procedure, a CB threshold equal to an increase of 3 °C from the floor temperature was chosen, and a cutoff level of 196 colored pixels was identified as the threshold to use to classify a positive case. The results of field tests showed that the developed monitoring system reached a fine detection accuracy (sensitivity = 97.9% and specificity = 94.9%) and the IR technology proved to be a possible solution for the development of a detection sensor necessary to reach the scope of this study

Improved Fuzzy Logic System to Evaluate Milk Electrical Conductivity Signals from On-Line Sensors to Monitor Dairy Goat Mastitis

The aim of this study was to develop and test a new fuzzy logic model for monitoring the udder health status (HS) of goats. The model evaluated, as input variables, the milk electrical conductivity (EC) signal, acquired on-line for each gland by a dedicated sensor, the bandwidth length and the frequency and amplitude of the first main peak of the Fourier frequency spectrum of the recorded milk EC signal. Two foremilk gland samples were collected from eight Saanen goats for six months at morning milking (lactation stages (LS): 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total of 5592 samples. Bacteriological analyses and somatic cell counts (SCC) were used to define the HS of the glands. With negative bacteriological analyses and SCC &lt; 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC &gt; 1,000,000 cells/mL, glands were classified as not healthy (NH). For each EC signal, an estimated EC value was calculated and a relative deviation was obtained. Furthermore, the Fourier frequency spectrum was evaluated and bandwidth length, frequency and amplitude of the first main peak were identified. Before using these indexes as input variables of the fuzzy logic model a linear mixed-effects model was developed to evaluate the acquired data considering the HS, LS and LS × HS as explanatory variables. Results showed that performance of a fuzzy logic model, in the monitoring of mammary gland HS, could be improved by the use of EC indexes derived from the Fourier frequency spectra of gland milk EC signals recorded by on-line EC sensors

Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations

Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens’ welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new “nest-usage-sensor” was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a “Multiple Nest Occupation Threshold” of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved

Evaluation of the Fourier Frequency Spectrum Peaks of Milk Electrical Conductivity Signals as Indexes to Monitor the Dairy Goats’ Health Status by On-Line Sensors

The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH) glands. Two foremilk gland samples from 42 Saanen goats, were collected for three consecutive weeks and for three different lactation stages (LS: 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total amount of 1512 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define the health status of the glands. With negative bacteriological analyses and SCC &lt; 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC &gt; 1,000,000 cells/mL, glands were classified as NH. For each milk EC signal, acquired on-line and for each gland considered, the Fourier frequency spectrum of the signal was calculated and three representative frequency peaks were identified. To evaluate data acquired a MIXED procedure was used considering the HS, LS and LS × HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland’s health status. Results also explained how the milk EC signals’ pattern change in case of NH glands. In fact, it is characterized by slower fluctuations (due to the lower frequencies of the peaks) and by an irregular trend (due to the higher amplitudes of all the main frequency peaks). Therefore, these frequency peaks could be used as new indexes to improve the performances of algorithms based on multivariate models which evaluate the health status of dairy goats through the use of gland milk EC sensors

Development and Testing of a Device to Increase the Level of Automation of a Conventional Milking Parlor through Vocal Commands

A portable wireless device with a “vocal commands” feature for activating the mechanical milking phase in conventional milking parlors was developed and tested to increase the level of automation in the milking procedures. The device was tested in the laboratory and in a milking parlor. Four professional milkers participated in the experiment. Before the start of the tests, a set of acoustic models with speaker-dependent commands defined for the project was acquired for each milker using a dedicated “milker training procedure”. Two experimental sessions were performed by each milker, with one session in the laboratory and a subsequent session in the milking parlor. The device performance was evaluated based on the accuracy demonstrated in the vocal command recognition task and rated using the word recognition rate (WRR). The data were expressed as %WRR and grouped based on the different cases evaluated. Mixed effects logistic regression modeling was used to evaluate the association between the %WRR and explanatory variables. The results indicated significant effects due to the location where the tests were performed. Higher values of the %WRR were found for tests performed in the laboratory, whereas lower values were found for tests performed in the milking parlor (due to the presence of background noise). Nevertheless, the general performance level achieved by the device was sufficient for increasing the automation level of conventional milking parlors