Soil is a complex and irreplaceable natural resource which varies hugely locally and nationally. While farmers sample their soil to learn about its nutrient levels to help manage their land, soil quality must also be monitored at national or regional scale. With growing populations and stricter legislation, such environmental surveys are becoming increasingly important to ensure sustainable land management, but current sampling methods can be time consuming, costly and produce insufficient results.
However, the new ‘intelligent computer program’ looks set to change this by enabling soil sampling to be tailored to local conditions, allowing land managers to obtain high quality information without over or under sampling.
The program has been designed by researchers at Rothamsted Research, with funding from a Biotechnology and Biological Sciences Research Council (BBSRC) Industrial Partnership Award with the Home-Grown Cereals Authority.
Dr Murray Lark, head of the Environmetics group which developed the software, explained: “Our program learns about the variation of the soil as it samples, and is therefore able to generate a sampling scheme that is tailored to local conditions and ensures that the sampling effort is used to greatest effect. Our program rapidly identifies where variation in the soil is complex and many samples are needed or where less sampling is needed because there are large patches of contrasting soil, so samples can be further apart.”
The underlying concept behind the program is the variogram – a mathematical model of how soil varies across an area. As sampling begins, the computer program is ignorant of the variogram and uses data from the sampling to reduce the level of uncertainty and to direct where subsequent samples should be taken. As data accumulate, this uncertainty is reduced.
Once the program has a sufficiently robust model of the spatial variation within the area, a final phase of sampling points is identified to ensure that the resulting map of the soil will be sufficiently precise.
Both computer simulations and practical trials have shown that this adaptive sampling scheme can converge from no initial knowledge to a reliable map of how soil varies. When tested on real landscapes, the scheme has reduced the number of sampling sites needed without any loss of accuracy.
Professor Julia Goodfellow, BBSRC Chief Executive, said: “This new program is a real breakthrough in modern land management and highlights the important role of a multidisciplinary systems approach to bioscience. By combining theory, computer modelling and experiments, scientists are producing useful and easier to apply outputs, such as this soil sampling program, which will ultimately benefit the wider public.”
Matt Goode | alfa
Algorithm could streamline harvesting of hand-picked crops
13.03.2018 | University of Illinois College of Engineering
A global conflict: agricultural production vs. biodiversity
06.03.2018 | Georg-August-Universität Göttingen
Animal photoreceptors capture light with photopigments. Researchers from the University of Göttingen have now discovered that these photopigments fulfill an...
On 15 March, the AWI research aeroplane Polar 5 will depart for Greenland. Concentrating on the furthest northeast region of the island, an international team...
The world’s second-largest ice shelf was the destination for a Polarstern expedition that ended in Punta Arenas, Chile on 14th March 2018. Oceanographers from...
At the 2018 ILA Berlin Air Show from April 25–29, the Fraunhofer Institute for Laser Technology ILT is showcasing extreme high-speed Laser Material Deposition (EHLA): A video documents how for metal components that are highly loaded, EHLA has already proved itself as an alternative to hard chrome plating, which is now allowed only under special conditions.
When the EU restricted the use of hexavalent chromium compounds to special applications requiring authorization, the move prompted a rethink in the surface...
At the ILA Berlin, hall 4, booth 202, Fraunhofer FHR will present two radar sensors for navigation support of drones. The sensors are valuable components in the implementation of autonomous flying drones: they function as obstacle detectors to prevent collisions. Radar sensors also operate reliably in restricted visibility, e.g. in foggy or dusty conditions. Due to their ability to measure distances with high precision, the radar sensors can also be used as altimeters when other sources of information such as barometers or GPS are not available or cannot operate optimally.
Drones play an increasingly important role in the area of logistics and services. Well-known logistic companies place great hope in these compact, aerial...
16.03.2018 | Event News
13.03.2018 | Event News
08.03.2018 | Event News
16.03.2018 | Earth Sciences
16.03.2018 | Physics and Astronomy
16.03.2018 | Life Sciences