Classifying vocal responses of broilers to environmental stressors via artificial neural network.

Detecting early-stage stress in broiler farms is crucial for optimising growth rates and animal well-being. This study aims to classify various stress calls in broilers exposed to cold, heat, or wind, using acoustic signal processing and a transformer artificial neural network (ANN). Two consecutive trials were conducted with varying amounts of collected data, and three ANN models with the same architecture but different parameters were examined.

Synchronizing food availability with the natural rhythm substantially improves reproduction and extends healthspan in laying hens.

Disrupted sleep due to nighttime eating can raise various concerns, impacting both physical health and overall well-being. Nevertheless, there is a lack of direct evidence linking nighttime eating with the female reproduction system, possibly due to the absence of suitable models. Here, we use the laying hen, a diurnal animal maintained under ad libitum feeding, as a vertebrate model to quantify the impact of nighttime eating on reproduction and aging.

Review: Exploring the use of precision livestock farming for small ruminant welfare management.

Small ruminant (sheep and goat) production of meat and milk is undertaken in diverse topographical and climatic environments and the systems range from extensive to intensive. This could lead to different types of welfare compromise, which need to be managed. Implementing Precision Livestock Farming (PLF) and other new or innovative technologies could help to manage or monitor animal welfare.

Biometric identification of dairy cows via real-time facial recognition.

Biometrics methods, which currently identify humans, can potentially identify dairy cows. Given that animal movements cannot be easily controlled, identification accuracy and system robustness are challenging when deploying an animal biometrics recognition system on a real farm. Our proposed method performs multiple-cow face detection and face classification from videos by adjusting recent state-of-the-art deep-learning methods.

Machine vision-based automatic lamb identification and drinking activity in a commercial farm.

Using ear tags, farmers can track specific data for individual lambs such as age, medical records, body condition scores, genetic abnormalities; to make data-based decisions. However, automatic reading of ear tags using Radio Frequency Identification requires (a) an antenna, (b) a reader, (c) comparable reading standards; consequently, such a system can be expensive and impractical for a large group of lambs, especially in situations where animals are not required to have a compulsory Electronic identification, contrary to the case in Europe, where it is mandatory. Therefore, this paper proposes a machine vision system for indoor animals to identify individual lambs using existing ear tags.

Short Communication: The effect of age on young sheep biometric identification.

Biometric identification provides an important tool for precision livestock farming. This study investigates the effect of weight gain and sheep maturation on recognition performance. Sheep facial identification was implemented using two convolutional neural network (CNN) called Faster R-CNN, and ResNet50V2, equipped with the state-of-art Additive Angular Margin (ArcFace) loss function.

A machine vision system to predict individual cow feed intake of different feeds in a cowshed.

Data on individual feed intake of dairy cows, an important variable for farm management, are currently unavailable in commercial dairies. A real-time machine vision system including models that are able to adapt to multiple types of feed was developed to predict individual feed intake of dairy cows. Using a Red-Green-Blue-Depth (RGBD) camera, images of feed piles of two different feed types (lactating cows' feed and heifers' feed) were acquired in a research dairy farm, for a range of feed weights under varied configurations and illuminations.

Design a system for measuring individual cow feed intake in commercial dairies.

Monitoring individual cow feed intake is necessary for calculating the cow individual feed efficiency. The cost and maintenance time necessary for research systems make them impractical for most of the commercial producers. We developed a measurement system with producer convenience and low investment as key design criteria.

Advancements in sensor technology and decision support intelligent tools to assist smart livestock farming.

Remote monitoring, modern data collection through sensors, rapid data transfer, and vast data storage through the Internet of Things (IoT) have advanced precision livestock farming (PLF) in the last 20 yr. PLF is relevant to many fields of livestock production, including aerial- and satellite-based measurement of pasture's forage quantity and quality; body weight and composition and physiological assessments; on-animal devices to monitor location, activity, and behaviors in grazing and foraging environments; early detection of lameness and other diseases; milk yield and composition; reproductive measurements and calving diseases; and feed intake and greenhouse gas emissions, to name just a few. There are many possibilities to improve animal production through PLF, but the combination of PLF and computer modeling is necessary to facilitate on-farm applicability.

Dynamic cooling strategy based on individual animal response mitigated heat stress in dairy cows.

Technological progress enables individual cow's temperatures to be measured in real time, using a bolus sensor inserted into the rumen (reticulorumen). However, current cooling systems often work at a constant schedule based on the ambient temperature and not on monitoring the animal itself. This study hypothesized that tailoring the cooling management to the cow's thermal reaction can mitigate heat stress.

Effect of forage-to-concentrate ratio on production efficiency of low-efficient high-yielding lactating cows.

Feed is usually the costliest input in lactating cow's farms. Therefore, the developing of methods for a better adjustment of feed intake to cow's energetic needs in order to improve efficiency is desired. The aim of this study was to improve feed efficiency of low-efficient (LE) cows through a moderate increase in diet forage-to-concentrate ratio.

A machine vision system to detect and count laying hens in battery cages.

Manually counting hens in battery cages on large commercial poultry farms is a challenging task: time-consuming and often inaccurate. Therefore, the aim of this study was to develop a machine vision system that automatically counts the number of hens in battery cages. Automatically counting hens can help a regulatory agency or inspecting officer to estimate the number of living birds in a cage and, thus animal density, to ensure that they conform to government regulations or quality certification requirements.

Cooling management effects on dry matter intake, metabolic hormones levels and welfare parameters in dairy cows during heat stress.

This research paper addresses the hypothesis that intensive cooling management during the summer improves the secretion of metabolic hormones in dairy cows. To test this hypothesis, we characterized the effect of different cooling managements on the different ghrelin isoforms and leptin secretion of 20 Israeli-Holstein dairy cows during 5 weeks during heat stress. The cows were divided into two groups: one was exposed to 5 cooling sessions per day (5 CS) and the other to 8 cooling sessions per day (8 CS).

Dietary restriction improved feed efficiency of inefficient lactating cows.

The aim of this study was to reduce voluntary dry matter intake (DMI) to increase feeding efficiency of preclassified inefficient (INE) dairy cows through restricted feeding. We studied the effects of dietary restriction on eating behavior, milk and energy-corrected milk (ECM) production, in vivo digestibility, energy balance, and measures of feed efficiency [residual feed intake (RFI) and ECM/DMI]. Before the experiment, 12 pairs of cows were classified as INE.

Assessing the potential of photogrammetry to monitor feed intake of dairy cows.

We address the hypothesis that individual cow feed intake can be measured in commercial farms through the use of a photogrammetry method. Feed intake and feed efficiency have a significant economic value for the farmer. A common method for measuring feed mass in research is a feed mass weighing system, which is excessively expensive for commercial farms.

Effect of lactation trimester and parity on eating behavior, milk production and efficiency traits of dairy cows.

There is absence knowledge about the effects of lactation trimester and parity on eating behavior, production and efficiency of dairy cows. Objective of this study was to identify and characterize in 340 dairy cows, the 20% high efficient (HE), 20% low efficient (LE) and 60% mid efficient (ME) cows according to their individual residual feed intake (RFI) values, within and between lactation trimesters and between 1st and 2nd parities. Efficiency effect within each lactation trimester, was exhibited in daily dry matter intake (DMI), eating rate and meal size, that were the highest in LE cows, moderate in the ME cows and lowest in the HE group.

Smart Animal Agriculture: Application of Real-Time Sensors to Improve Animal Well-Being and Production.

Consumption of animal products such as meat, milk, and eggs in first-world countries has leveled off, but it is rising precipitously in developing countries. Agriculture will have to increase its output to meet demand, opening the door to increased automation and technological innovation; intensified, sustainable farming; and precision livestock farming (PLF) applications. Early indicators of medical problems, which use sensors to alert cattle farmers early concerning individual animals that need special care, are proliferating.

Eating behavior, milk production, rumination, and digestibility characteristics of high- and low-efficiency lactating cows fed a low-roughage diet.

This study aimed to identify individual characteristics differing among high-efficiency (HEf; upper 20%, n = 31), low-efficiency (LEf; lower 20%, n = 31), and mid-efficiency (MEf, 60% n = 93) lactating cows. Primiparous (37) and multiparous (118) high-producing milking cows at 30 to 180 d in milk were fed individually a low-roughage diet [31.6% of dry matter (DM)] for 4 wk.

Consistency of feed efficiency ranking and mechanisms associated with inter-animal variation among growing calves.

This study investigated the possible mechanisms for explaining interanimal variation in efficiency of feed utilization in intact male Holstein calves. Additionally, we examined whether the feed efficiency (FE) ranking of calves (n = 26) changed due to age and/or diet quality. Calves were evaluated during three periods (P1, P2, and P3) while fed a high-quality diet (calculated mobilizable energy [ME] of 11.

A flexible control system designed for lab-scale simulations and optimization of composting processes.

Understanding and optimization of composting processes can benefit from the use of controlled simulators of various scales. The Agricultural Research Organization Composting Simulator (ARO-CS) was recently built and it is flexibly automated by means of a programmable logic controller (PLC). Temperature, carbon dioxide, oxygen and airflow are monitored and controlled in seven 9-l reactors that are mounted into separate 80-l water baths.

Towards practical application of sensors for monitoring animal health: the effect of post-calving health problems on rumination duration, activity and milk yield.

Three sources of sensory data: cow's individual rumination duration, activity and milk yield were evaluated as possible indicators for clinical diagnosis, focusing on post-calving health problems such as ketosis and metritis. Data were collected from a computerised dairy-management system on a commercial dairy farm with Israeli Holstein cows. In the analysis, 300 healthy and 403 sick multiparous cows were studied during the first 3 weeks after calving.

Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis.

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow.

Development of automatic body condition scoring using a low-cost 3-dimensional Kinect camera.

Body condition scoring (BCS) is a farm-management tool for estimating dairy cows' energy reserves. Today, BCS is performed manually by experts. This paper presents a 3-dimensional algorithm that provides a topographical understanding of the cow's body to estimate BCS.

A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot.

Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors.