Marcella Guarino

Evaluation of simplified covering systems to reduce gaseous emissions from livestock manure storage

Ammonia, methane, and carbon dioxide are the primary atmospheric emissions from cattle and pig farms. A significant part of these emissions is produced by the decomposition of slurry organic matter during manure storage and treatment phases. Present solutions to contain emissions from storage lagoons generally involve reducing the free surface of the slurry by covering it either with permanent fixed structures or temporary floating ones. This study investigated the effectiveness of five simple floating covers in reducing emissions from pig and cattle slurry. The coverings included vegetable oil (a mixture of rapeseed and soybean oil), expanded clay, chopped maize stalks, chopped wheat straw, and chopped wood chips. All were tested at two different thicknesses: 70 and 140 mm for solid coverings, and 3 and 9 mm for liquid. Slurry samples covered with the above-mentioned materials were placed in nine stainless steel airtight cylinders measuring 190 dm3. Gaseous and odor concentrations in the headspace were monitored using a Bruel & Kjaer 1302 multi-gas monitor and a T07 olfactometer. The flotation aptitude of the different coverings was also tested. Results revealed substantial differences in ammonia emission reduction efficiency (1% to 100%) and odor abatement (0% to 90%), and high levels of reduction efficiency were achieved by all the tested covers at the higher thickness. However, equally valid results were not obtained for methane emissions reduction. In regard to flotation aptitude and cover deterioration on slurry, expanded clay and wood chips demonstrated long-term resistance to both deterioration and sinking.

DUST CONCENTRATION AND MORTALITY DISTRIBUTION IN AN ENCLOSED LAYING HOUSE

Dust concentration was monitored in a commercial enclosed laying unit that housed 56,000 laying hens. The hens were confined in stair-step cages with five rows and four tiers. The unit measured 12 × 150 m and was ventilated with a negative pressure fan system. Dust concentration data were collected three times a day for three one-week periods (in April, May, and June). The data were collected in three different points of the laying house: (point A – located in the last aisle in front of the third group of fans; point B – located in the third aisle at the end of the house; and point C – located in the first aisle in the same transversal section of point A). All three sampling sites were fitted with two sampling stations. One station recorded the total dust (TD) and the other recorded the respirable fraction (RF); and one data logger recorded temperature and relative humidity. In the same months mortality was recorded. The results show that dust concentration was significantly higher during the period of feed distribution (TD = 1.94 mg/m3, RF = 0.31 mg/m3) and scraper cleaning (TD = 1.90 mg/m3, RF = 0.28 mg/m3), than during the night (TD = 0.74 mg/m3, RF = 0.22 mg/m3) and in point A (TD = 1.72 mg/m3, RF = 0.31 mg/m3). Moreover, the quantification of the effect of TD and RF on bird mortality showed that one point increase of TD and RF brings about, respectively, two and nine more dead birds.

Online detection of an emotional response of a horse during physical activity.

The objective of this research was to develop a non-invasive method to detect an emotional response of a horse to novelty during physical activity. Two horses performed 20 trials each, in which the horses heart rate (HR) and physical activity were continuously measured. The relationship between the horses physical activity and HR was described by a mathematical model allowing online decomposition of the horses HR into a physical component and a component containing information about its emotional state. Exposure to the novel object resulted in an increase in the emotional component of HR, which allowed automatic detection of an emotional response of the horse in 33/40 trials. In the remaining seven trials no stable model could be built or data were missing. The results show that model-based decomposition of HR can be a useful tool for quantification of certain aspects of temperament.

Yearly emission factors of ammonia and particulate matter from three laying-hen housing systems

The aim of the present study was to measure the concentration of ammonia and particulate matter (PM) that passes through a size‐selective inlet with a 50% cut‐off at 10-μm aerodynamic-equivalent diameter (PM10) and emissions into atmosphere in the following three types of laying-hen houses: traditional battery cages with aerated open-manure storage (BSP) and two best available technique (BAT) housing types, namely, an aviary-system housing (ASH) and a vertical tiered cage with manure belts and forced-air drying (VTC). Measurements were taken continuously for a period of 1 year in each house. Ammonia concentration was measured continuously in each house using an infrared photoacoustic detector with a 15-min sampling interval. PM10 was measured continuously using a scatter light photometer, corrected by the traditional gravimetric-technique concentration to lower the measurement error. The same instrument was also used to collect PM10 through a traditional gravimetric technique. This procedure was performed to adjust the particulate matter-specific gravity of PM that is typical and specific for every animal house. PM10 and ammonia measurements were carried out together with measurements of inside and outside temperature, inside and outside relative humidity and ventilation rate. For the high PM10 concentrations measured in the ASH house during a preliminary survey, concentrations of total suspended particles (TSP) and fine PM (particles <2.5 microns) were also measured to evaluate the dustiness in the building during the working hours. The ammonia concentration was 5.37 mg/m3 in the traditional BSP house (the reference for cage-housing system), 4.95 mg/m3 in the VTC and 3.85 mg/m3 in the ASH. The ammonia-emission factors were 15.445 mg/h.hen place (0.135 kg/year.hen place) for BSP, 8.258 mg/h.hen place (0.072 kg/year.hen place) for VTC, and 23.704 mg/h.hen place (0.208 kg/year.hen place) for ASH. Ammonia emission-reduction efficiency of VTC v. the BSP was 53%, according to thresholds assessed by Integrated Prevention Pollution Control. The ammonia-reduction efficiency of ASH v. that of the standard Reference Housing system for non-cage housing was 68%. Average yearly PM10 concentration was remarkably higher in the ASH, with 0.215 mg/m3 v. 0.108 mg/m3 for the VTC and 0.094 mg/m3 for BSP. In the ASH, the concentration of total suspended particles (TSP) was 0.444 mg/m3 and that of PM2.5 was 0.032 mg/m3. In this facility, a great variation of PM10 concentration occurred in the morning hours. Recorded values for the PM10 emission were 0.433 mg/h.hen for BSP and 0.081 mg/h.hen for VTC, while the ASH showed the highest PM10 emission (1.230 mg/h.hen), with clear peaks occurring in the morning hours during daily farming operations.

Image-processing technique to measure pig activity in response to climatic variation in a pig barn

In the past decades, the increasing scale of intensive pig farms led farmers to use automatic tools to monitor the welfare and health of their animals. Visual observation and manual monitoring, usually practiced in small-scale farms, is unreliable in large-scale husbandry, and is expensive and time consuming. Environmental parameters are crucial information for the efficient management of piggery buildings, as they have a significant effect on production efficiency, health and welfare of confined animals. The aim of the present study was to evaluate the relationship between pig activity and environmental parameters in a pig building by means of image analysis. The barn for 350 fattening pigs was open-space, mechanically ventilated and subdivided into 16 pens with fully slatted floor. The room was equipped to monitor the ventilation rate, internal and external temperature and relative humidity every minute. For the experiments, two adjacent pens were selected, each 5.9 by 2.6 m, with ~16 pigs in each. Pigs were continuously monitored during 30 days using an infrared-sensitive CCD camera that was mounted 5 m above the floor. Recorded data were processed in real time by Eyenamic, an innovative software that continuously and automatically registers the behaviour of a group of animals, intended as the activity and occupation indices of the pigs. A preliminary virtual subdivision of the two pens in four zones (two zones for each pen) was performed to evaluate differences in activity/occupation indices in ‘front’ and ‘back’ zones of the pen. Recorded images were visually observed in the laboratory to estimate pig activity type in relation to the indices calculated by Eyenamic software. The occupation index showed higher values (up to 0.75 units) in Zones 1 and 4 placed near the corridor. There was a significant relation between pig occupation index measured in the two pens and ventilation rate, temperature and humidity. The interaction between ventilation and humidity and temperature and humidity significantly affected pig movements during the day. Pigs tended to stay in the part of the pen far from the external wall, where air velocity was higher, probably because this is a ‘central zone’ in the barn, characterised by a reasonable air movement (~0.30 m/s). On the contrary, the part of the pen nearest to the external wall, characterised by a humid floor surface and by a limited air speed, was occupied by animals at the trough mainly during feeding times and for defecation and urination.

Cough sound description in relation to respiratory diseases in dairy calves.

Cough can be a biomarker in case of respiratory diseases. By monitoring and analyzing cough sounds through automatic devices, the farmer can obtain an early warning about a developing outbreak of respiratory infections. Cough sounds can be characterized by particular acoustic features (amplitude, frequency and duration) that are obtained by sound recording, labeling and analytic procedures. Based on these features, it might be possible to develop an automated cough recognition system. The aim of the study described in this paper is to investigate whether it is possible to discriminate cough sounds from other frequently occurring sounds in youngstock stables. Nasal swabs and blood were taken to identify the microbiological agents responsible for the respiratory problems. The collected cough sounds were compared to metal rack sounds, which are very common sounds in cattle farming, to identify acoustic differences between them. Results show that the length of cough sounds was significantly different from metal rack sounds (0.34 versus 0.37 s, P<0.05). Also, the analysis of amplitude and fundamental frequency showed significant differences between both types of sounds (resp. 0.21 and 0.18; 1326 and 3868 HZ). This indicates that it is possible discriminate cough sounds from other sounds and that cough sound can be used as a non-invasively diagnostic tool for respiratory diseases in youngstock groups.

Technical note: Validation of a commercial system for the continuous and automated monitoring of dairy cow activity

Current farm sizes do not allow the precise identification and tracking of individual cows and their health and behavioral records. Currently, the application of information technology within intensive dairy farming takes a key role in proper routine management to improve animal welfare and to enhance the comfort of dairy cows. An existing application based on information technology is represented by the GEA CowView system (GEA Farm Technologies, Bönen, Germany). This system is able to detect and monitor animal behavioral activities based on positioning, through the creation of a virtual map of the barn that outlines all the areas where cows have access. The aim of this study was to validate the accuracy, sensitivity, and specificity of data provided by the CowView system. The validation was performed by comparing data automatically obtained from the CowView system with those obtained by a manual labeling procedure performed on video recordings. Data used for the comparisons were represented by the zone-related activities performed by the selected dairy cows and were classified into 2 categories: activity and localization. The duration in seconds of each of the activities/localizations detected both with the manual labeling and with the automated system were used to evaluate the correlation coefficients among data; and subsequently the accuracy, sensitivity, specificity, and positive and negative predictive values of the automated monitoring system were calculated. The results of this validation study showed that the CowView automated monitoring system is able to identify the cow localization/position (alley, trough, cubicles) with high reliability in relation to the zone-related activities performed by dairy cows (accuracy higher than 95%). The results obtained support the CowView system as an innovative potential solution for the easier management of dairy cows.

An innovative approach to predict the growth in intensive poultry farming

Chicken weight provides information about growth and feed conversion of the flock.We record and analyse broiler vocalisations under normal farm conditions.We find a significant correlation between frequency of sounds and weight of the birds.The more the birds grow, the lower the frequency of the sounds emitted by the animals.Young chicks vocalise at high frequency under non-stress condition. Chicken weight provides information about growth and feed conversion of the flock in order to identify deviations from the expected homogeneous growth trend of the birds. This paper proposes a novel method to automatically measure the growth rate of broiler chickens by sound analysis.Through the application of process engineering, Precision Livestock Farming (PLF) can combine audio and video information into on-line automated tools that can be used to control, monitor and model the behaviour, health and production of animals and their biological response.The aim of this study was to record and analyse broiler vocalisations under normal farm conditions, to identify the relation between animal sounds and their weight. Recordings were made at regular intervals, during the entire life of birds, in order to evaluate the variation of frequency and bandwidth of the sounds emitted by the animals.Two experimental trials were carried out in an indoor reared broiler farm; the audio recording procedures lasted for 38days. The recordings were made, in an automated, non-invasive and non-intrusive way and without disturbing the animals in to the broiler house. Once a week, 50 birds were selected at random and their weight recorded in order to follow the growth trend in the birds.Sound recordings were manually analysed and labelled using the Adobe� Audition� CS6 software.Analysing the sounds recorded, it was possible to find a significant correlation (P<0.001) between the frequencies of the vocalisations recorded and the weight of the broilers.The results explained how the frequency of the sounds emitted by the animals was inversely proportional to the age and to the weight of the broilers; the more they grow, the lower the frequency of the sounds emitted by the animals.This preliminary study, conducted in an indoor reared broiler farm, shows how this method based on the identification of specific frequencies of the sounds, linked to the age and to the weight of the birds, might be used as an early warning method/system to evaluate the health and welfare status of the animals at farm level. This is the basis for a further development of an automated growth monitoring tool.

LabeLLing the behaviour of pigLets and activity monitoring from video as a tooL of assessing interest in different environmentaL enrichments

Abstract The aim of this study was to explore the preference and the duration of interest of weaned pigs to two different types of environmental enrichments using labelling techniques and activity monitoring. Two pens each housing 14 Dalland piglets were monitored using a video camera. The videos were labelled during the weaning phase from 30 to 60 days of age. During this time, the video recording software continuously calculated the activity index of the pigs. To detect pig exploratory and playing behaviour, a wooden block and chain enrichment were introduced into each pen for 30 days. Each video frame was manually labelled during the Day 1, 5 and 30 (24 hours a day) for each pen using the Labelling Tool software. To identify the duration and frequency of interactive episodes with environmental enrichments, pig behaviour was labelled as either: no activity, interacting with chain or interacting with the wooden block. The mean duration of interactive episodes for the chain was greater than for the wooden block (P<0.001), while the frequency of interactive episodes was 28.8% higher for the wooden block than for the chain. By day 5, the mean duration of interaction episodes decreased in both pens and by day 30, only a few interaction episodes were observed. The number of interactive episodes were strictly related to the activity index and depended on the time of the day. The peaks of the mean number of interactive episodes calculated for all days of observations corresponded to the peaks of the mean activity index. Streszczenie Celem badań było sprawdzenie preferencji oraz czasu trwania zainteresowania prosiąt odsadzonych dwoma typami elementów wzbogacających środowisko kojca. Użyto do tego technik analizy obrazu oraz monitoringu aktywności zwierząt. Dwa kojce z 14 prosiętami rasy Dalland (24 prosięta) w wieku od 30 do 60 dni były monitorowane za pomocą kamery. Indeks aktywności prosiąt został obliczony podczas rejestracji nagrań wideo przez oprogramowanie do automatycznego pomiaru aktywności zwierząt. W kojcu został umieszczony na 30 dni drewniany pieniek oraz łańcuch w celu wykrycia zachowań eksploracyjnych i zabawy. Każda klatka zarejestrowanego filmu wideo została przeanalizowana w 1., 5. oraz 30. dniu (24 godziny na dzień) eksperymentu za pomocą oprogramowania do analizy obrazu. W celu zidentyfikowania czasu trwania i częstotliwości interakcji z elementami wzbogacającymi środowisko kojca zachowanie zwierząt zostało oznaczone jako brak aktywności, interakcja z łańcuchem lub interakcja z drewnianym pieńkiem. Zainteresowanie łańcuchem średnio było dłuższe (P<0.001) niż drewnianym pieńkiem. Częstotliwość zabawy drewnianym pieńkiem była 28.8% wyższa niż łańcuchem. Średni czas interakcji z elementami wzbogacającymi środowisko kojca uległ skróceniu w piątym dniu eksperymentu, w obu kojcach. W trzydziestym dniu eksperymentu zauważono ich tylko kilka. Liczba interakcji z elementami wzbogacającymi środowisko kojca była ściśle powiązana z wartością indeksu aktywności zarejestrowanym przez oprogramowanie i zależała od pory dnia. W każdym dniu prowadzonej obserwacji wzrost średniej liczby interakcji odpowiadał wzrostowi średniej wartości indeksu aktywności.

Time-series analysis for online recognition and localization of sick pig (Sus scrofa) cough sounds

This paper considers the online localization of sick animals in pig houses. It presents an automated online recognition and localization procedure for sick pig cough sounds. The instantaneous energy of the signal is initially used to detect and extract individual sounds from a continuous recording and their duration is used as a preclassifier. Autoregression (AR) analysis is then employed to calculate an estimate of the sound signal, and the parameters of the estimated signal are subsequently evaluated to identify the sick cough sounds. It is shown that the distribution of just three AR parameters provides an adequate classifier for sick pig coughs. A localization technique based on the time difference of arrival is evaluated on field data and is shown that it is of acceptable accuracy for this particular application. The algorithm is applied on continuous recordings from a pig house to evaluate its effectiveness. The correct identification ratio ranged from 73% (27% false positive identifications) to 93% (7% false positive identifications) depending on the position of the microphone that was used for the recording. Although the false negative identifications are about 50% it is shown that this accuracy can be enough for the purpose of this tool. Finally, it is suggested that the presented application can be used to online monitor the welfare in a pig house, and provide early diagnosis of a cough hazard and faster treatment of sick animals.