HWodka, the innovations club of arable farmers in the southwest of the Netherlands, has set up the Gaos programme to take a closer look at routing during the potato planting process.
Gaos stands for Geo-Field-Optimisation-Service (in Dutch Geo-Akker-Optimalisatie-Service) and has been developed together with Wageningen University & Research.
Arable farmers at large and specialised companies in particular experience the problem of a limited number of workable days. This number of days is mostly limited by temperature. Planting potatoes in soil that is too cold causes problems with diseases and the crops’ uniformity.
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A growing group of arable farming companies in the Netherlands and Belgium grows more than 100 hectares of potatoes, sometime even several hundreds. - Photo: Joep van der Pal/Roel Dijkstra Fotografie
However, waiting too long for better temperatures is not an option either, because that limits the number of growth days and because of that, the maximum yield.
In addition to this, the soil’s moisture condition is very important, because it determines its load-bearing capacity. Especially at large companies with so-called all-in-one combinations of more than 20 tons, the soil’s load-bearing capacity is critical. Because of that, planning the most efficient way of planting is especially important for such companies. A growing group of arable farming companies in the Netherlands and Belgium grows more than 100 hectares of potatoes, sometime even several hundreds.
To be clear, this focus is aimed at large, tightly managed companies. There are companies where the question whether the potatoes are planted in time and properly is less important.
22 hectares in less than 3 days
Last week for example, I heard about a company led by 2 brothers in Drenthe, a province in the northeast of the Netherlands. Well-equipped as they are, they can plant their 22 hectares of potatoes in less than 3 days. “If we try really heard, we can even do it in 2”, they said.
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Especially at large companies with so-called all-in-one combinations of more than 20 tons, the soil’s load-bearing capacity is critical. - Photo: Fred Libochant/Roel Dijkstra Fotografie
Well, for these kinds of companies, finetuning the planting logistics and routing is not that necessary. However, gaining minutes many times can make the difference between getting things done in time or failing to do so.
Let’s just assume that the mechanisation trend for planting, or rather, all cultivation, is characterised by wanting to increase the work performance (hectares/man-hours). The success rate is determined by the combination of the machine’s weight (for soil compaction) and timeliness. This is a worldwide issue.
HWodka draws several conclusions after its research:
- To make more and better use of the limited number of workable days, the hectare output of the planting combination needs to increase. The current trend is characterised by an increase of the work performance by combining tasks in 1 cultivation. Sometimes, farmers focus on the hectare output so the risk of planting in less optimal conditions increases.
- Turning and filling often takes up more time than you realise. Steps can be made by automation, for example when an operator can operate the dumper combination from a distance. HWodka also has a field robot in mind that can take care of preparing the plant bed. When this is separated from the planting itself, the planter can drive faster: 2 up to 6 kilometers per hour.
- Small plots may sometimes be used for agricultural nature conservation, if the compensation is adequate.
- The additional information from Gaos, the cultivated area and the cultivation times, is especially useful when working on ‘strange’ plots. Moreover, if you know the exact planting distance and the 1.000 planter weight, you can calculate even more precisely how much seed potatoes are needed and whether or not the bunker is large enough to make 1 or more whole rounds.
HWodka’s chairman adds that strict planning beforehand is very important for the most efficient use of eventually autonomous machines: robots.