" THE MAIN OBJECTIVE OF THE PROPOSAL IS TO OBTAIN INFORMATION ON SOME OF THE PHYSIOLOGICAL MECHANISMS INVOLVED IN THE REGULATION OF FEEDING IN FISH AND TO KNOW HOW SEVERAL FACTORS RELATED TO AQUACULTURE PRODUCTION ALTERING WELFARE CAN INTERFERE WITH THEM, AND THEREFORE ALTER FOOD INTAKE. WE AIM TO CONTINUE THE STUDIES CONDUCTED TO DATE BY THE RESEARCH GROUP THAT ALLOWED TO CONTRIBUTE TO THE SCIENTIFIC BASIS OF THE IMPACT OF NUTRIENT SENSING SYSTEMS, THE CIRCADIAN SYSTEM, AND STRESS SIGNALS ON THE INTEGRATED RESPONSE OF FOOD INTAKE IN FISH.

FUTUREDAIRY4 Robotic Milking – 600 and Beyond (RM600+) 2014-2017 RM600+ is focused on building knowledge around incorporating Automatic Milking into large scale farming operations. In particular, attention is placed on pasture-based systems (>50% diet provided as grazed forage) and operating with voluntary cow traffic. Robotically milking 600+ cows is new, but necessary territory for the techonology and the system that surrounds it. The scale of the operation plus the impact of large herd dynamics (eg.

Objectives The overall aim of the proposed research is to explore the benefits of closely meeting the changing nutrient requirements of individual sows during gestation and across parities, in a group housing system and using computer controlled electronic sow feeders. Specific objectives are to determine the effect of meeting the estimated nutrient requirements of individual (parity 1, 2 or 3) sows on: 1.Sow welfare and reproductive performance: sow behaviour, injuries and health, litter size at birth, mean and average piglet weight at birth and weaning, sow feed intake and body weight c

The focus of this project is to develop and enable an intelligent system that will apply precision management to whole farm grassland and grazing systems. The goal is to optimize grass quality, utilization efficiency, and ultimately profitability, with minimal labour requirement and maximum objectivity. To precisely allocate to the cow herd the absolutely correct area of grass, it is necessary to have an accurate ‘real-time’ measure of grass quality (as well as quantity).

Profitability on grass-based systems is driven by degree of grass utilization. This is influenced by increased growth and optimum management of that growth. Frequent measurement of grass parameters, e.g. herbage yield, height, density will facilitate increased herbage production and utilization. However, traditionally such measurement on farms is limited. The potential use of ICT for grass measurement is dramatic.

The main goal is to optimise the feeding strategy for grazing cattle and to improve the methods of pasture management. An in the frame of the project developed pasture robot and a modified automatic grazing system (AGS) will be integrated into existing herd management software (HMS), providing an optimal feeding strategy for cattle and pasture maintenance. A robot will be redesigned and sensors for detection of biomass, cowpats etc. and actuators, a mulcher and a seeder, will be implemented.