Crop production (cereal)

The use case consists of three production phases in crop production: Seeding and fertilising, Spraying in plant protection and harvesting. The seeding and fertilizing are performed in the spring in a combined process where the seeds and the fertiliser are applied simultaneously in a combined seeder. The seeding process is initiated by a decision support system, which alerts the farmer about the suitable seeding time and conditions. The seeding operation begins by planning the seeding operations. Seeding and fertilization work tasks are planned according to the seeding plan, soil and environmental conditions in the field. The production history of the field and previous operations is utilized in the planning process. The generated variable rate application (VRA) task is used in the seeding and fertilisation operation. The work process is monitored and recorded for evaluation and utilization in the later field operations and phases.

The spraying process is initiated by plant disease alert service. The system receives plant disease alert from disease prognosis service. A spraying plan is generated using disease and weather forecasts, farming history, while observing legislative and production standard restrictions. A spraying task is generated according to spraying plan and environmental conditions. The generated spraying task is used in the seeding and fertilisation operation. The work process is monitored and recorded for evaluation and utilization in the later field operations and phases.

Harvesting process is initiated by a decision support system, which alerts the farmer about the predicted crop readiness for harvesting and suitable harvesting conditions. A harvesting plan is generated using crop readiness forecast, crop dryness estimates, farming history and weather forecasts. Harvest work and process is recorded and monitored for future use and for evaluation of works. Field yield is measured and mapped.

USE CASE – Precision Livestock Farming (PLF)

The Maaninka CowLab facility and software combined with collected data on plant production, grassland and environment will be used to produce new information about milk production and animal health status by deploying the CLAFIS technology with new and improved algorithms. The PLF use case will combine feed and animal related information where/when ever necessary (or possible) to create predictive models for real time animal health status production estimates. Early warning systems will be integrated and deployed during sensitive production periods e.g. in dairy cow’s transition period from dry period via calving to milking period with the aim of detecting the most common health problems, such as lameness and mastitis, which cause loss of profit. For this demonstration, the early detection of these unwanted conditions will initiate faster treatment and prevent prolonged income losses. The aim of this demonstration is to predict animal’s production potential with models created from the created database so that it can help optimize the input/output ratio of dairy farm.