THE GOAL OF THIS COORDINATED PROJECT IS TO PROVIDE THE KNOWLEDGE, CONCEPTS AND TECHNOLOGICAL TOOLS REQUIRED IN THE DEVELOPMENT OF INTEGRATED WEED MANAGEMENT SYSTEMS (IWMS). THE PROJECT IS STRUCTURED AROUND TWO SCENARIOS: THE DRY-LAND CEREAL PRODUCTION SYSTEMS PREVAILING IN CENTRAL SPAIN AND THE VINEYARD SYSTEMS MORE WIDELY USED IN THESE SAME AREAS, BASED ON THE USE OF DEFICIT IRRIGATION.

This project is funded by the innovation program of the Federal Ministry of Food and Agriculture (BMEL), funding agency is the Federal Office for Agriculture and Food (BLE). Orchestration of Process Chains for data-driven Resource Optimization in Agricultural Business and Engineering Environmentally sustainable and economically efficient operation of agricultural processes depends heavily on farm management and controlling systems. However, practical usage of these systems suffers from diverse, non-compatible implementations across collaboration machinery.

This project is funded by the innovation program of the Federal Ministry of Food and Agriculture (BMEL), funding agency is the Federal Office for Agriculture and Food (BLE). Collaborative project: Development of a low-priced miniaturized mid-infrared (MIR)-Sensor for integrated area-wide slurry management According to the guideline of the BMEL about promoting innovations in agricultural engineering, the project aims to develop low-priced miniaturized mid-infrared (MIR)-Sensors as well as the accompanying control technology and a data infrastructure for the realization of an area-wide slu

Research objectives Use hyperspectral data from UAV platform for crop/weed discrimination Generation of spraying task /application maps for SSWM and validation The research will focus on two kind of weeds i.e. thistles in grassland and bindweeds in maize fields for case study. Field aerial hyperspectral images of thistles will be collected at the different growth stages and different flight height. The aerial images of bindweeds will also be taken in the early growth stage in the maize fields.

Remote sensing using small unmanned airborne systems (sUAS) is a rapidly emerging technology. sUAS-based remote sensing offers possibilities for cost-efficient data capture with desired spatial and temporal resolutions, offering completely new business opportunities in various application fields. The sUAS markets are expected to grow explosively. Examples of key applications include surveying and mapping, precision agriculture and forestry, water quality monitoring, energy and power, infrastructure, law enforcement, public safety, and science and education.

Precision Agriculture is becoming a hot topic in the research community as intrigued stakeholders investigate novel ways to improve farming practices with the introduction of sensing and communication technologies. Recently there has been particular interest in the use of unmanned aerial vehicles (drones) for observing large areas of farmland that would otherwise be done on foot or in a relatively large wheel-based vehicle.

FATIMA addresses effective and efficient monitoring and management of agricultural resources to achieve optimum crop yield and quality in a sustainable environment. It covers both ends of the scale relevant for food production, viz., precision farming and the perspective of a sustainable agriculture in the context of integrated agri-environment management.

Information about the weed population in fields is important for determining the optimal herbicides for the fields. A system based on images is presented that can provide support in determining the species and density of the weeds. Firstly, plants are segmented from the soil. Plants that after the segmentation are divided in multiple parts are selected manually and a cost image is created by weighting pixels according to their relationship to plant. This relationship is based on the colours of pixels and the weighting of nearby pixels.

Development of vision technologi for detection of weeds in early development stage. Implementation in a weeding robot with thermal destruction of weeds. Suitable for production of organic food.

Research, domains and case projects While some questions in the core disciplines will be addressed using traditional research approaches, many of the main activities in the partnership will be orchestrated in a number of case projects. A project will have a clear business potential and address challenges that can be met using the knowledge, methods and services of the core. Most of the initially defined projects fall within the three domains, but cross-cutting projects and new opportunities are expected to appear during the partnership.

The overall objective of FUTUREMILQ is to devlop technologies and concepts that can ensure a future high food quality from existing and future milking systems. The purpose is to develop new methods for measurement of quality decreasing free acids, to develop a fast method for analysis of secific types of spores and to develop systems for monitoring and early warning.

The objectives of this project are: 1. Generate adequate information to understand the relationship between Somatic Cell Count (SCC), Diffrential Cell Count (DCC) and mastitis (intramammary infections) in dairy herds. 2. Develop guidelines to cost effective monitoring and control of mastitis in dairy cattle herds that should be offered with the commercail DCC product 3. Develop a commercial DCC product that will be used to automate the counting of DCC

The aim of this project is to develop an irrigation management help tool for farmers based on the analysis and the state of the crop assessment (soil or sustrate), offering advice on the frecuency and last of the irrigation. The system make this kind of decision by itself based on the information obtained.

SAGIRA project has developed a system to analyze information from farming sensors, georeferenced, with specicialised stock and with an interface display which show the result data overprinted on the real images (augmented reality with mobile devices). This technology allows users to make relations between elements, not only pay attention on characteristics of them, as historically. Furthermore, users can check data using these relations and attributes. It is useful to optimization of water resources in crops and pesticides and fertilizers.

Summary This project builds on the current RIRDC project: PRJ007477, Rice NIR and Remote Sensing. It involves maintaining the NIR instrument at Yanco and updating the panicle initiation (PI) tissue, grain and straw nitrogen calibrations. The instrument and calibrations are used to determine the PI tissue nitrogen (N) content of the samples submitted to the NIR Tissue Test Service. The NIR, using numerous calibrations, is also used to analyse grain, straw and tissue samples in several other RIRDC research projects.