Episode 33: Combating arsenic in groundwater and rice
Mason Stahl, associate professor at Union College, is using machine learning and direct sampling to help mitigate dangerous levels of arsenic in our food.
Study groundwater recharge, nutrient or contaminant leaching, and the influence of land management practices on water retention and drainage across a larger area with affordable, easy to use instruments.
Plant growth, microbial activity, nutrient availability and transport, soil erosion, soil compaction, soil respiration, water infiltration and drainage are all dependent on soil moisture. Measure the amount of water, its availability, and predict where it will move with our water content and water potential sensors.
Track groundwater recharge, water flows through canals or channels, or solute concentration using all-in-one sensors. Combining these sensors with a remote data logger allows you monitor water quality and levels across a wide area without frequent site visits.
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Measure the movement and distribution of water in the soil to inform water management, predict soil behavior under a variety of moisture conditions, measure groundwater recharge, or optimize agricultural practices for efficient water usage. Field instruments like the SATURO set the standard for simple, accurate, and time-efficient data collection.
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Avoid costly field visits by accessing your data from any web-connected device. Analyze it with ZENTRA’s built-in visualization tools, and easily share insights without tracking down log files on individual computers.
Streamline your laboratory analyses and reduce human error using the innovative LABROS soil science laboratory collection. Perform automated particle size analysis, generate soil moisture release curves, or measure thermal and hydraulic conductivity with METER laboratory instruments designed to produce accurate analyses in a fraction of the time of other methods.
Even better, LABROS instruments can be combined to perform all of these analyses from a single sample, saving time and reducing measurement errors due to variations in sample characteristics.
– Prof. Masaru Mizoguchi, Department of Global Agricultural Sciences | The University of Tokyo
Mason Stahl, associate professor at Union College, is using machine learning and direct sampling to help mitigate dangerous levels of arsenic in our food.
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