Field Ops: Stem Water Potential
Vitidore’s field operations team collects a variety of field data, for the purpose of providing helpful information to farmers as well as to help build our machine-learning system for modeling soil carbon. This is part of a series about what we do and how it furthers the goals of sustainable agriculture.
Stem water potential (SWP) readings measure plant water status, a metric for water stress in crops. It is analogous to blood pressure in humans, with a higher value indicating more stress- i.e. less water available to the plant. Vitidore began measuring SWP in cash crops in order to assess the effects of the Oakville bluegrass cover crop on wine grape and nut crops, hypothesizing that the grass could improve their plant water status, particularly during extreme heat events.
Before SWP data collection starts, Vitidore’s field operations team collaborates with growers to identify “control” and “treatment” vines to inform the design of the experiment. Control vines vary between research locations, reflecting the normal management of each vineyard, and all treatment vines are surrounded on both sides by a permanent stand of Oakville Bluegrass.
During the SWP data collection season, Vitidore’s team members conduct bi-weekly visits to each research site with a pressure chamber, also known as a pressure bomb.
A pressure bomb is a portable piece of equipment used to collect SWP readings. The pressure chamber applies pressure to a leaf picked off the vine. The cut end of the stem (the petiole) is exposed outside the chamber. The amount of pressure needed to cause water to appear at the cut surface of the petiole indicates how much tension the leaf is experiencing on its water supply. The pressure value corresponds with the tension value, which indicates the degree of water stress.
Vitidore’s team selects shaded leaves for each tagged vine or tree to bag following crop-specific criteria, allowing the leaves to reach equilibrium before taking a reading. Conditions (date, weather, field notes, photos, etc.) are recorded along with SWP readings, which are then used as inputs for training our machine learning system. One of our ongoing goals is to be able to model both soil carbon sequestration and plant water status (along with other sustainability metrics) using this software modeling system.
