Computers and Electronics in Agriculture
Improving neural networks classification through chaining
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
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A simple and reliable technology to automatically record the growth and water use of indeterminate tomato crops has been developed for use in commercial and research greenhouses. Using pairs of load cells and intensive data-handling techniques, up to 11 physiological and irrigation parameters may be measured simultaneously. One set of load cells measures the mass of the growing media sitting in a leachate collection trough, thereby enabling measurement of crop water use and five irrigation parameters. The other set is suspended from above to measure the mass of the plant canopy, and from that, 24h growth as well as the mass of harvested fruit. Data from the load cells are collected on a data logger, subjected to preliminary on-board processing, and recorded every 5min. The information is then relayed to a PC via short haul modems. Calculations are based on short-term changes in mass. Water use is expressed either as a rate per minute or as a cumulative total over 24h; growth is expressed as a 24h total. The use of mass threshold values automatically filters the data allowing a clean separation of small changes in water uptake or canopy mass from large changes due to irrigation, leaching, or fruit harvest. This method also allows the calculation of irrigation and leachate volumes, and harvested fruit mass. The extent of hydration (water content) of the plant canopy during the course of the day can also be inferred from the data. Additional information on percent media moisture and leachate percentage is collected and displayed automatically. Information is displayed every 5min, either graphically or in tables, and is also archived. Four independent sets of plants with up to 12 plants each can be accommodated on one data logger, and sensors for micro-climate measurements may also be incorporated. .