Turn the Tap: Integrated Research to Support Sustainable Irrigation Practices on Northeast Vegetable Farms

Final report for LNE19-391R

Project Type: Research Only
Funds awarded in 2019: $124,982.00
Projected End Date: 09/30/2022
Grant Recipient: University of Vermont
Region: Northeast
State: Vermont
Project Leader:
Dr. Joshua Faulkner
University of Vermont Extension
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Project Information


One of the most challenging effects of climate change for farmers in the northeastern United States is the increasing variability of precipitation and temperature. Changing rainfall patterns during the growing season is of particular concern for producers of annual vegetable crops, as many of these crops have shallow root systems and rely on consistent soil water availability in upper horizons of the soil. While relying on ambient precipitation was an adequate strategy for growing annual vegetables in the past, farmers increasingly rely upon irrigation. However, irrigation scheduling can be difficult in variable soils and under variable weather conditions. Soil moisture sensors are a potentially useful tool for Northeast farmers, as they provide information about soil water conditions in real-time. This information can be used by farmers to time irrigation applications and avoid overuse of water. 

This project explored whether using soil moisture sensors led to improved crop outcomes (yield, quality) and water quality outcomes (leachate amounts and nitrate contamination) in diversified vegetable cropping systems. Specifically, we looked at four different “cues to irrigate”, or ways that farm managers decide to turn irrigation water on and off. These included timers (which received irritation every day), feeling the soil (a common practice), using soil moisture sensors, and a control treatment that received no irrigation but only ambient precipitation. The objectives of our work were: (1) to develop best practices for deploying soil moisture sensors on diversified farms in the Northeast and using sensor data to inform irrigation decisions; and (2) to develop a better understanding about what Northeast farmers need from soil moisture monitoring systems to enable them to use it effectively.

Through a field trial conducted over two years in two locations, and four farmer focus groups, we found the following: (1) the amount of water used in the feel of soil and soil moisture sensor treatments was very similar, likely because both were assessed on a daily basis. As a result, there were few meaningful differences in crop yield or quality, or in leachate amount and nitrate contamination, between these two treatments. The timer treatment resulted in some negative crop quality and yield outcomes, and intuitively excessive leachate in one research site (with sandy soils). Soil characteristics and ambient precipitation was responsible for the biggest differences between research sites, as one site was located on a sandy soil and the other in a clay soil.  

Through farmer focus groups, we documented a concern for water use efficiency and an interest in soil moisture sensors. Attending a workshop where soil water dynamics and soil moisture sensing tools were discussed led to an increased interest in this technology. However, farmer willingness to purchase soil moisture sensing tools (hardware and software) is contingent upon improved yields, which our field trial fails to demonstrate.

The primary mode of outreach for this project was through the four workshops associated with the focus groups. In addition, we developed two fact sheets and gave several presentations at grower conferences and meetings. One scholarly publication on a topic that grew out of this project has already been published, and a second is in development. This project supported one masters student who successfully defended her thesis in 2022. 

Project Objective:

Project objectives from proposal:

(1) Develop best practices for deploying soil moisture sensors on diversified farms in the NE and using sensor data to inform irrigation decisions.

(2) Develop a better understanding about what NE farmers need from soil moisture monitoring systems to enable them to use it effectively.


The northeastern (NE) U.S., inclusive of 13 states, has a growing vegetable industry. There has been an 84% increase in the number of farms in all sectors since 1992. NE Farms tend to be small (93 acres average compared to 234 acres nationally) and highly diversified. In 2012, there were 26,491 produce operations in the NE, together harvesting from 402,378 acres and reporting over $1B in annual sales. Many NE vegetable growers use irrigation. Despite the benefits of soil moisture sensing technology to increase water use efficiency and decrease nutrient applications, widespread adoption is not evident in the NE vegetable sector. Our project explored why and sought to demonstrate the ecological and economic benefits to investing in soil moisture technology as a sustainability-guided approach to on-farm water management.

Efficient water use is an important component of sustainable vegetable production for several reasons. First, applying the right amount of water helps to maximize crop yields/quality. Second, over-application of water leaches nutrients away from the root zone, which costs farmers money and can impair public waterways. Third, shifting precipitation patterns associated with climate change have led to both too much rain and too little rain, sometimes in the same growing season. Soil moisture sensors have great potential to help vegetable growers increase irrigation efficiency.

Results from our preliminary research suggest an opportunity to expand use of soil moisture technology in the NE. In on-farm trials in 2018, we found that on one farm alone, water was overapplied in zones that used drip irrigation (at a rate of 92,000 gal/acre), and underapplied in overhead irrigation zones (100,000 gal/acre). Data collected from soil moisture sensors corroborated this. Mid-season results shared with the host-farmer led to a quick management adjustment to water applications. In 2013, only 215 farms (out of 4,098) in the New England Water Resource Region reported using soil moisture sensors. 

NE farmers (like those in other regions) often don’t know how much water their crops need, how water affects nutrient mobility, or how much water they apply when they irrigate. In 2017, our team conducted a survey that showed that most respondents use crop condition (89%) and/or the feel of the soil (83%) as their primary cues to irrigate. Unfortunately, by the time crops show signs of water stress or the soil feels dry, yield potential/crop quality have already significantly decreased. Much of the research and outreach that has been done on soil moisture technology has been conducted in other U.S. regions (e.g., the Southeast or Northern Plains) or other crop sectors (e.g., ornamental horticulture, commodity crops). However, NE vegetable farms are different from these other cropping systems and geographies due to their small size, high diversity, and hilly topography. These characteristics of NE farms influence the degree to which soil moisture technology, as currently designed, are useable. Our field trials evaluated economic and ecological benefits of soil moisture technology in a NE climate in a simulated diversified vegetable cropping system, and by doing provided useful information to growers.


Click linked name(s) to expand/collapse or show everyone's info
  • Dr. Joshua Faulkner (Researcher)
  • Rebecca Maden (Educator and Researcher)



Our project has two hypotheses and two research questions:
H1: Use of soil moisture monitoring systems (a) improves vegetable yield/product quality, (b) decreases nutrient leaching, and (c) reduces water applied per unit harvested.
H2: Following exposure and education, farmers will demonstrate changes in knowledge, attitudes, and awareness related to soil moisture technology.
RQ1: What are the current barriers that keep NE farmers from investing in soil moisture sensing technology?
RQ2: What changes to current tools/data systems should be made to increase their usefulness for NE vegetable growers?

Materials and methods:


Note: All research activities were put on hold in 2020 due to COVID-19 restrictions to the UVM Horticultural Research and Education Center, where our plots were located. We requested (and were granted) an extension on this grant due to the pandemic. In 2021, we expanded the study, adding a study site and extending the time frame, at the University of Maine Rogers Farm using funding from the University of Maine Agricultural and Forestry Experiment Station (MAFES). We believe that replicating the study on a different soil type in a different part of New England enhanced the quality of our data and the generalizability of our findings. 

Plot preparation and fertility: This research was at conducted at two locations: Rogers Farm, University of Maine, Old Town, ME (44.93° N, 68.70 W, 42 m) in 2021 and 2022 and Horticultural Research and Education Center, University of Vermont, S. Burlington, VT (44.43° N, 73.21° W, 67 m) in 2019 and 2021.  The soil at the Maine site was a Pushaw silt loam (fine-silty, mixed, semiactive, nonacid, frigid Aeric Epiaquepts) and an Adams Windsor loamy sand (Adams: sandy, isotic, frigid Typic Haplorthods; Windsor: mixed, mesic Typic Udipsamments) at the Vermont site (USDA NRCS, 2016).  Zero-tension lysimeters based on the Zotarelli et al. (2007) design was installed in a trench 60 cm deep to allow leachate sampling below the mature crop rooting zones.  After installation the trenches were back filled with the excavated soil. Collected leachate was extracted through a sampling tube extending above the soil surface using a portable vacuum pump. Nine raised bed plots that were 2m by 3m with 0.5 m buffer borders on all sides were hand-built to incorporate the randomized block design of three treatments with three replicates.  Each installation measuring 600 square feet. Prior to plot installation, Modified Morgans soil tests were conducted to determine nutrient needs. At the time of installation, fertilizers were added based on soil test results. Rows were then marked, irrigation installed, and the beds were covered with black plastic mulch. Each plot included four of the following: tomatoes (Early Girl), cucumbers (Marketmore), and bell peppers (Olympus F1). 

Daily irrigation protocol: The irrigation water source at both sites provided 103 kPa of pressure to the system.  The mainline was split into two header pipe for the two irrigation treatments, each fitted with a timer and a Netafim flow meter.  Within each irrigated 2m by 3m plot, six lines of drip tape with 28 cm emitter spacing were installed.  Water applied to the irrigated treatment plots were recorded weekly from the two flow meters installed in the treatment header pipes.  Ambient precipitation was estimated using NOAA weather station data located at the Bangor International Airport (16.5 km from the Maine study site) and the Burlington International Airport (6.1 km form the Vermont study site).   

Two irrigation scheduling approaches and a control treatment were investigated.  Treatment 1 was the control which received no irrigation.  Treatment 2 was based on the feel of the soil, assessed daily, to initiate irrigation.  This is a common approach used by growers in the NE (Schattman et al., 2018) and nationally (Hrozencik et al, 2021).  Treatment 3 irrigation was initiated when soil tensiometer reading reached 20 kPa of water tension.  Irrometer Watermark model 200SS sensors (Riverside, CA) were installed at 30 cm and 60 cm depths on all nine plots at both sites.  The Maine site used a cellular-based data logging system (IRROcloud IC-10) and the Vermont site used a WiFi-based (Irrometer Irromesh) for hourly data logging and archiving.  Soil temperature probes were also installed in the plots for temperature self-compensation of the soil moisture sensors.  Total liters applied to each plot was used for the presentation of results.  All treatments received ambient precipitation.

Soil collection and testing: Soil samples were taken at 12” depths on a weekly basis starting 6/03/2019. 6 random cores were taken per plot, mixed and collected in cotton bags. The soil bags were kept in a dark container until they were brought to the lab. The samples were dried at 55 degrees overnight to preserve nitrates present in the soil mixtures until analysis could be completed. 

Lab Protocol for Soils: The soil samples were placed in souffle cups, ground and put through a 10mm sieve to remove rocks and larger soil debris. 4 grams of sample were weighed out into 100mL erlenmeyer flasks fixed on wooden structures 12 at a time, including a quality control nitrate sample soil and a sample duplicate. 20mL of 1M KCl solution was added to each flask before the samples are shaken for 15 minutes. The samples were poured through filters rinsed with DI water into test tubes. Once filtered, the solution is poured into Lachat tubes and covered with parafilm until lab analysis.

Leachate collection and testing: Leachate samples were collected weekly in addition to soils. A vacuum pump and battery were used to draw the samples into a collection bottle with attaching tubes. Once pumped, the lysimeter volumes were measured and recorded using graduated cylinders and 1000mL pitchers, depending on volume. 50 mL samples from lysimeter draws were stored in plastic test tubes and frozen until analysis.

Lab Protocols for Leachate Samples: Each sample was pipetted into Lachat tubes for nitrate analysis to approximately ¾ full. The first 40 samples ran above the maximum detection set by the Lachat (10mg/ L) and were diluted 10x with DI water. Two months later, the second round did not require dilution, since they were within the detection limits of 10mg/ L and 0.2mg/ L on their own. 

Yield and quality of vegetable crops: Vegetables were harvested on a twice-weekly schedule from July through early-October. Vegetables were harvested by plot, weighted and counted. Quality was evaluated using United States Department of Agriculture (USDA) Agriculture Marketing Service (AMS) guidelines, specifically color uniformity, gloss, size and shape uniformity, defects, and firmness. Quality and yield were averaged across plots in each treatment to determine daily metrics. 



Focus groups were conducted with growers at four regional conferences in 2019-2020 (prior to the COVID-19 pandemic). The conferences we attended were the Pennsylvania Association for Sustainable Agriculture (PASA) annual conference, the Vermont Vegetable and Berry Growers Association (VVGBA) annual meeting, the New England Vegetable and Berry Growers Association bi-annual conference, and the Maine Organic Farmers and Gardeners Association (MOFGA) Farmer to Farmer Conference. At all sessions, growers were offered monetary stipends and lunch for attending the special session. Focus group sessions were designed to be preceded by an educational presentation, followed by an open discussion about grower thoughts on using soil moisture sensors in their irrigation management systems. Attendees were asked to fill out pre- and post-workshop questionnaires to assess the effects of the event on their perceptions and willingness to invest in soil moisture monitoring systems. Outreach was conducted through conference organizers. Despite incentives and multiple rounds of outreach, attendance was smaller than expected (and hoped for). Between 4 focus groups there were 22 participants.

Research results and discussion:

Our results are drawn from data collected in VT in 2019/2021, and ME in 2021/2022. Analysis is being finalized as of this final report, though many of our findings are presented below. All data will be included in a manuscript submitted for scholarly review and publication in winter 2022/spring 2023. Below is a summary of our analysis to date.

Soil parameters: 


Table 1.  Selected chemical and physical properties of the Maine and Vermont soils used in the study. 


Soil parameter 






Organic matter (%) 



CEC (cmol(+) kg-1 soil) 



Extractable P (mg kg-1 soil) 



Extractable K (mg kg-1 soil) 



Extractable Ca (mg kg-1 soil) 



Extractable Mg (mg kg-1 soil) 



Extractable S (mg kg-1 soil) 



Extractable B (mg kg-1 soil) 



Extractable Cu (mg kg-1 soil) 



Extractable Fe (mg kg-1 soil) 



Extractable Mn (mg kg-1 soil) 



Extractable Zn (mg kg-1 soil) 



Water use: In Vermont and Maine, the amount of water used in each treatment was significantly different from the control treatment (R2 =0.540, P < 0.001), as was expected. Timer treatments received significantly more water than the control treatment (R2 = 0.61, P <0.001), as did the feel of soil treatment (R2 = 0.61, P = 0.004). However, soil moisture sensor treatments did not significantly differ from the control treatment (R2 = 0.61, P=0.052). In Vermont, the soil moisture sensor had an estimated coefficient of 68.6 gallons of water where the timer treatment and feel of soil treatment has an estimated coefficient of 787.9 and 102.9 respectively. A Tukey post hoc test established that the timer treatment used statistically more water than all other treatments, while the feel of soil and soil moisture sensor did not statistically differ from one another. Analysis of the Maine data is ongoing.

N in leachate: Vermont leachate data showed that the timer treatment (R2 = 0.32, P< 0.001) and the feel of soil treatment (R2 = 0.32, P=0.0453) were different from plots in the control treatment. The timer treatment plots leached 74% more water than the control treatment plots, and 90-94% more water than feel of soil or soil moisture sensors plots. There was no leachate collected from the control treatment in Vermont in 2019, and all leachate collected from the control treatment in 2021 came from one plot (indicative of a leak in the irrigation system). In Maine, there was no difference in the amount of leachate collected between treatments. There was leachate collected from all plots, with the largest amount from the timer treatment, with an average of 3.936 L per plot over the 2021 growing season. Meanwhile, the control treatment plots averaged 1.333 L. There were several periods in 2021 in Maine in which the trial was saturated, with standing water. The soil texture caused slow drainage, and during this period leachate collected was similar across treatments.

Table 2.  The number of lysimeter samples collected, total volume, and total nitrate content in the leachate for the four irrigation cue treatments at the Maine and Vermont study sites.  NOTE: At the time of this report, we are awaiting test results for Maine 2022.



Maine 2021 

Maine 2022 

Vermont 2019 

Vermont 2021 


Sample Count 

Volume (L) 

Total Nitrate Content (mg) 

Sample Count 

Volume (L) 

Total Nitrate Content (mg) 

Sample Count 

Volume (L) 

Total Nitrate Content (mg) 

Sample Count 

Volume (L) 

Total Nitrate Content (mg) 













4.4 (28.9) 


























22.2 (88.8)  













4.9 (21.5) 

In Vermont, irrigation had a large effect on nitrogen-in-leachate. The timer treatment plots had significantly greater concentration of nitrate in the leachate and significantly fewer nitrates in the soil than those samples taken from control plots (R2 = 0.034, P = 0.0163). The amount of irrigation water that drained through the soil both increased the amount of water leaving the root zone and transported N. Soil moisture sensor plots had significantly fewer soil nitrates in leachate than control plots (R2 = 0.034, P = 0.039) but did not differ in the amount of leachate collected.   

Nitrogen lost to leachate was calculated: total nitrates lost per lysimeter area (NL) was determined by multiplying the volume of leachate (L) and the concentration of nitrate in the leachate (NinL). Once total nitrogen loss (NL) was calculated, this value was multiplied by the square feet of a plot (Psqft) then divided by the square feed of the lysimeter (Lsqft). This resulted in nitrogen lost in whole plot (NP). The NP was then multiplied by 100 and divided by the amount of nitrogen to each plot (F), equaling the total N lost through leaching (LostN). A GLM established differences between each treatment compared to the control. In Maine, no treatment lost statistically more N to leachate than the control. In Vermont, all plots with irrigation lost more N to leachate compared to control. However, it should be noted that in 2019 there was no leachate collected from control plots and therefore we could not conduct a comparison to other treatments.


Cucumbers: Cucumber yields in Vermont and Maine were statistically different in 2021 (R2 = 0.772, P < 0.0001), therefore the results for the two sites are presented separately. In Maine, there were no statistically significant differences in cucumber yield between any of the treatments. The control treatment had a mean of 56 individual cucumbers (36lbs), averaged within treatments for the growing season; the timer treatments yielded a mean of 55 cucumbers (34lbs). The feel of soil and soil moisture sensor treatments yielded a mean of 61 (38lbs) and 63 (39lbs) cucumbers respectively. This indicates that in Maine in 2021, none of the irrigated treatments outperformed the control treatment. In Vermont across both years, there was also no statistically significant difference in number of fruit when comparing irrigated treatments to the control treatment. However, control, timer and soil moisture sensor treatments had the low number of fruits with a mean of 91 (64lbs), 94 (68lbs), and 85 (62lbs) cucumbers averaged within treatment, while the feel of soil plots yielded a mean of 133 cucumbers (124lbs). 

In Vermont in 2019, the feel of soil treatment yielded more cucumbers than the control treatment (R2 = 0.55, P = 0.036). This could be due to 20 cB being a suboptimal soil dryness threshold for cucumbers, or that the soil moisture sensors were not at an optimal depth for assessing soil moisture for cucumbers. Cucumbers have relatively shallow roots compared to tomatoes and peppers, and sensor placement was likely lower than cucumber roots reached. In 2021, there was no difference in yield between any of the treatments. The likely difference in trends between the two years was the seasonal distribution of precipitation. In 2019, the majority of precipitation occurred in spring and early summer, prior to the growing season. 

It is worth noting that total precipitation across the 2021 growing season was relatively evenly distributed in Maine, which likely diminished the effects that different irrigation treatments had on cucumber yield at this site. Additionally, there are contradictory findings presented in prior studies on the effects of irrigation in cucumbers. Some suggest that key physiological indicators of cucumber development (e.g., leaf elongation and stomatal conductance) are less affected by soil water depletion than one may expect. In other words, it would take an extended, or several successive dry periods before physiological harm would be observed. In the case of the research presented in this present study, it is also possible that cucumber water uptake, and by extension plant fitness and yield, was affected more by environmental factors such as temperature or disease rather than irrigation treatment.

Peppers: Of the three crops included in this trial, peppers had the most variable yield across all treatments in both sites and both years. A GLM with gaussian distribution showed that Maine and Vermont sites in 2021 were not statistically different from each other (R2 = 0.477, P = 0.361); therefore, data was pooled for analysis. Both years in Vermont were also statistically similar, therefore yield data was again pooled (R2 = 0.293, P = 0.318). All years and sites were also analyzed separately.

Pooled data from Maine and Vermont in 2021 indicated all irrigated treatments yielded less than the control treatments. The largest difference was between the control treatment and the timer treatment (R2 = 0.565, P = 0.021). Over the growing season, the control treatment yielded a mean of 41 peppers per plot, averaging 12.6 lbs. The feel of soil, soil moisture sensor, and timer treatments yielded 33 (9.5lbs), 34 (9.7lbs), and 25 (6.7lbs) peppers respectively. The timer treatment was the only treatment that yielded significantly fewer peppers than the control plots (R2 = 0.246, P = 0.019). These results may suggest that a pepper yield is affected by overwatering. Previous irrigation studies support the idea that peppers are sensitive to soil moisture status. In Vermont there was sufficient water through precipitation for pepper growth, adding additional water through soil moisture sensors or feel of soil treatment did not increase yield and adding water daily decreased the yield of peppers in 2021.

In 2021 trial in Vermont, the feel of soil and timer treatments yielded significantly fewer individual fruits and lower total weight than the control treatment. The feel of soil treatment yielded a mean of 26 (8.1 lbs) peppers per plot over the growing season, the timer trial yielded 24 (6.4 lbs), and the control treatment yield double at a mean of 52 (16.2 lbs) peppers over the growing season.

Tomatoes: Tomato yield differed between Maine and Vermont in 2021 (R2 =0.434, P= 0.017) so data was not pooled for analysis. Vermont yield data in 2019 and 2021 did not differ significantly (R2 = 0.316, P = 0.360) and was pooled together, though each year was also analyzed separately.
In Maine, there was no difference in the total number of fruits averaged per plot over the growing season between any of the irrigation treatments and the control (176, 58 lbs). In Vermont, when data was pooled across 2019 and 2021, the timer treatment yielded statistically fewer tomatoes by fruit count per plot than the control plots (R2 = 0.194, P= 0.045). In Vermont the control treatment yielded 200 tomatoes per plot over each growing season, but with a smaller tomato size on average. Though the control plots had 21 more tomatoes on average, the mean weight was only 35.7lbs. This is consistent with prior research showing that timer systems can lead to overwatering causing leaching of inorganic nitrogen, thereby decreasing yield relative to more water-efficient irrigation practices. Both the feel of soil and soil moisture sensor treatments had comparable fruit counts with no statistical difference between them (189 and 185 fruited on average, respectively) with average total fruit weights of 40.7lbs and 37.3lbs respectively. When Vermont 2019 and 2021 were analyzed independently of one another, there were no significant treatment effects on tomato yield.


Quality: Crop quality (measured by assessments of color uniformity, gloss, shape, firmness, and number of defects) varied across sites and years.

Cucumbers: Though treatments did not have an observable effect on cucumber yield, there were significant differences in cucumber quality in Maine. Fruit harvested from plots with no irrigation (i.e., control treatments) were more uniform in color and had fewer defects but were significantly less firm and less uniform in shape and size compared to the control treatment. In examining the quality of cucumbers in Vermont, the gloss was the only quality parameter affected by irrigation treatments. The soil moisture sensor treatment was significantly less glossy than the control treatment, which received no irrigation (R2 = 0.05, t = 2.524, P = 0.036), however the difference was small (𝛽 = 0.052). With the contradictory quality results, the effect of irrigation strategies on the quality of cucumber in Maine in 2021 is unclear. In the context of the literature, more water is not necessarily better for cucumber quality. Indeed, some studies show that quality parameters (i.e., sugars, vitamin C) decline as water applications increase. This is a finding that is supported in research in Mediterranean climates, which shows that reduced water applications lead to a higher concentration of sugars and higher acidity, which are thought to contribute to desirable flavor profiles. These findings suggest that aligning the quality parameters used in the present research (developed by the USDA AMS) with parameters used in other crop research studies (i.e., sugars, acid, and water content) could lead to more understandable (and useful) results. 

Peppers: The quality of peppers varied very little over both year and location, however in Vermont in 2021, the feel of soil treatment resulted in less gloss than the control treatment. These results show that in the Northeast our changing and unpredictable precipitation patterns can have a mixed effect on the quality of peppers from year to year, even if yield effects were not particularly noticeable over the two years in Vermont and two locations. This finding aligns with prior research that shows that irrigation water quantity has a significant effect on pepper yield, though other studies have documented that deficit irrigation reduces yield compared to more generous irrigation approaches. To better tease apart these contradictions, future research should be conducted in a protected environment (e.g., greenhouse or high tunnel) which would better control external factors and make it more likely that differences between irrigation practices would become more observable.

Tomatoes: When comparing tomato quality parameters, there was no treatment effect in Maine in 2021. Though irrigation treatments did not have a statistically significant effect on yield in Vermont (in pooled data), there were significant differences in quality observed in 2019. Tomatoes harvested from the control plots exhibited lower quality than all other treatments which was not observed in Vermont 2021. These results suggest that even if irrigation does not increase yield of tomatoes, it may play a role in quality. This contradicts prior research suggesting that generally there is little difference in quality between tomato plants grown under drought conditions and non-drought conditions.

Studies that show minimal quality differences between different irrigation treatments. This is the basis of and justification for deficit irrigation, an approach designed to improve water use efficiency by limiting water availability to crops while maintaining an acceptable crop quality. Deficit irrigation is an evolving area of investigation, mostly in water-limited agricultural regions. In tomatoes, this approach is better suited to specific cultivars not included in this study, suggesting that the results presented here are likely influenced by the variety of tomato used. Future research should examine the relative fitness of different tomato varieties under the irrigation treatments included in this study, as it would provide useful information to Northeast growers about which varieties can tolerate water stress and/or water excesses. Because managing irrigation is a high-labor activity, it is often neglected on Northeast farms. Planting tolerant crop varieties may moderate the negative effects of suboptimal irrigation management.


Focus groups - qualitative findings: Farmers who attended the focus groups had a range of prior experiences with soil moisture sensors, from a general familiarity to no prior experience. Common themes that farmers discussed were (a) surprise to find they had been overwatering some crops, which was more commonly true in high tunnels; (b) preferences for various data delivery systems (in the field vs. in the cloud); (c) frequency with which they wanted to view soil water tension data; and (d) using soil moisture sensors to better manage "irrigation zones".

Overwatering in high tunnels was cited as a concern by some farmers. For example, one farmer who used sensors in a high tunnel where she grew tomatoes indicated that she was surprised to find out how much water she was actually using. This farmer paired sensors with a Netafim flow meter on her high tunnel irrigation line so she could assess how much water she was using to achieve desired cB readings. Blossom end rot was a challenge for this grower, and she concluded that overwatering was contributing to the problem. In the future, this grower planned to further fine tune her irrigation strategy to better control for consistent soil water content. The hope is that improved consistency would reduce tomato defects and improve the amount of marketable fruit produced in the high tunnel.

The desire to fine tune water applications was also mentioned by other focus group participants, as was the desire to "stop guessing" about how wet different soil textures were. This was discussed in the context of the cost of pumping water from wells, and the cost of purchasing municipal water. As one farmer stated: "I mean, it's money. We get double the yield with water, but we just don't know exactly how it went." Farmers in the focus groups voiced a desire to reduce unnecessary costs associated with accessing water and were interested in soil moisture sensors as a way to help them become more water efficient. They also noted that avoiding over-irrigation would help them make the most of expensive nutrient applications: "When you put your fertilizer in, how long do you water so you don't drive it past the roots?" is an example of a question that one strawberry grower had when thinking about assessing soil moisture during irrigation periods. He added: "We need to know much better what we're doing."

Data delivery systems for soil moisture sensors include integrated tension gauges, handheld meters to take readings in the field at a single point in time, and dataloggers that record continuous data. Data loggers can be connected to cellular or wireless networks, allowing farmers to access data from a smart phone or computer. Through focus group discussions, it became clear that farmers have different preferences for how to access data, with some preferring to read cB conditions in the field using a gauge or handheld meter. As one grower stated: "I don't hate the idea of a reader on the (sensor), because I'd have to run back to the house to get on the computer and login, because I couldn't do it through a phone. So, (a reader in the field would be) a quicker decision-making tool." Others indicated a preference for getting the information online. There is significant ongoing expense associated with cloud-based data, which some farmers indicated would be a barrier to them.  One farmer noted: "I'm okay with the prices (for the sensors) as they are. It's just that, if it were easier to get the data ... it depends on if you're going to get the software or not, honestly. That's the expensive part." Another stated: "I think the big question is: When does this pay? What carrot yield bump would justify this expense? You're getting fine carrots irrigation by feel(ing the soil) but would you get a $1,000 more of your carrot crop by using this technology? That's the think I keep coming back to." Other farmers indicated interest in alerts delivered directly to their phone, for both when to start and when to stop watering. 

Farmers in the focus groups indicated that they only wanted to check soil moisture sensors when they were able to irrigate. For some this was once a week, while for others this was every two or three days. Others indicated that their willingness to check sensors would be driven by weather. For high tunnel production, the farmer who grew tomatoes (above) reported that checking soil moisture levels was a daily ritual, but that was not necessarily true for sensors that she had installed in outdoor crops. Others indicated that having data that was collected on a shorter time step would be very useful to them. For example, one farmer stated: "I'm always curious about... water layering... turn it on for a little bit of time in the morning, and then once that's sunk down, then turn it on again... in order to get the moisture lower. I've always been curious about what's happening if I just water for ten minutes or what's happening if I water for an hour."

Farmers talked about using soil moisture sensors to identify irrigation zones. These participants indicated that parts of a single field or a single high tunnel could have very different moisture retention dynamics. In other words, some soils stayed wet while others dried out even in areas that were close together. One farmer noted that part of his field was located close to a wetland, and the water table was higher than in other parts of the same field. He stated: "Does it even matter if it's a little more saturated down there and a little bit drier up here if we're in a range? How differently does your soil have to respond before you reconsider your irrigation zones?"


Focus groups - survey findings:

Participants in the farmer focus groups were asked about how they assessed their irrigation needs in a typical year. Most (n = 9, or 69.23% of the 13 participants who answered the survey) reported that they irrigated based on crop condition and the feel of the soil. This aligns with prior surveys by our research team, and past USDA-ERS Irrigation Surveys. Additionally, five participants reported using weather reports (like frost warnings or heat advisories), and two reported that they did not irrigate. One person reported using a timer system on a valve. Most respondents (9 out of 13) had never used soil moisture sensors. Three participants had used soil moisture sensors in the past but had discontinued use because the sensors were "too complicated", "were defunct", or there was too much of a cost with "reinvesting on a new farm".

 Farmer participants were asked to report their level of agreement with several statements associated with on-farm water management before the workshop/focus group, and again after the workshop was complete. The workshop did not have an effect on participants level of concern about several measures (see table 3), but participants reported that the workshop increased their familiarity with soil moisture hardware and software, increase the likelihood that they perceived soil moisture sensor information as relevant to their farm operations, and their willingness to invest in soil moisture technology. 

5 = strongly agree, 1 = strongly disagree Average level of agreement PRE workshop Average level of agreement POST workshop
My current irrigation system allows me to successfully meet the water needs of my crops. 2.6 2.1
I am concerned about the effects of precipitation (rainfall and snow) on my crops’ ability to access to nutrients. 3.6 3.7
Fertilizer efficacy plays a role in my decisions about when to irrigate. 2.7 3.5
My irrigation system is efficient. 1.8 1.9
I wish to enhance irrigation efficiency on my farm. 4.4 4.5
I am familiar with soil moisture sensor hardware (sensors). 2.0 3.6
I am familiar with soil moisture sensor software (for reading data output). 1.5 2.9
Soil-moisture sensors provide information that is relevant to irrigation-related decisions that I make on my farm. 2.0 3.3
Considering what I know about crop water needs, I am willing to invest in soil moisture sensing technology. 3.5 3.8
I have concerns about managing soil moisture hardware in the field. 3.3 3.2
I am confident in my ability to interpret data generated by soil moisture sensing software. 3.3 3.5

We asked participants how much they would be willing to invest in soil moisture monitoring, if they could achieve 10%, 20%, 30%, or 40% increased yield. Several farmers reported that they would be willing to invest less than $500 for only a 10% increase in yield (8 out of 13 respondents), but willingness to invest greater sums was contingent upon higher rates of yield improvement. For example, 5 respondents would consider investing more than $2,000 if the return was a 40% increase in yield, but only 2 farmers would consider investing that sum for a 30% increase in yield. Only one respondent indicated that they would spend over $2,000 for a yield improvement of 20%, and no one was willing to invest this much money for a 10% yield improvement.

As a result of participating in the workshops and focus groups, farmers reported that their knowledge about soil moisture sensors had increased (4.5 average level of agreement, with 5 = strong agreement and 1 = strong disagreement). Participants also indicated that they would use soil moisture sensors in the future (mean response = 4.5) and that their confidence in using soil moisture sensors had increased (mean response = 4.0).

In summary, focus group findings showed that farmers are interested in soil moisture sensors as a way to improve water-use and nutrient efficiency, reduce unnecessarily irrigation, set up irrigation zones, and schedule irrigation cycles. These is a diversity of preferences among farmers when it comes to when they would like to access soil moisture data, and their preferred method of viewing the information. Cost of cloud-based data collection and storage is a barrier for some farmers, as the economic benefits of investing in these platforms has not been proven. 

Research conclusions:

H1: Use of soil moisture monitoring systems (a) improves vegetable yield/product quality, (b) decreases nutrient leaching, and (c) reduces water applied per unit harvested.

  1. Yield and quality varied by crop and was likely driven by environmental factors (precipitation and evapotranspiration) rather than irrigation approach. This was somewhat unexpected, as we anticipated that soil moisture sensors would improve crop outcomes. However, the amount of water applied in the soil moisture sensor treatment and the feel of soil treatment did not differ significantly, therefore it stands to reason that the crop outcomes were also similar. It should be noted that treatments irrigated based on soil moisture sensors and treatments irrigated based on the feel of soil were both assessed on a daily basis. It is possible that, in the real world, using soil moisture sensors would change the frequency with which farmers evaluated whether or not to irrigate. If that were the case, applying soil moisture sensors may still improve yield outcomes.
  2. We found that soil texture had a greater influence on nitrate loss through leaching than irrigation approach. It has long been known that sandy soils are much more vulnerable to N leaching than clay soils, and this is confirmed by comparing our results in Maine and Vermont. However, we were surprised to learn that even in over-watered treatments (i.e., those watered by timers), N leachate was not statistically different than the control (no irrigation) treatment.
  3. Water use efficiency was worse in timer treatments but did not differ between soil moisture sensors and feel of soil treatments. Water use efficiency was calculated based on the number of gallons used to produce a unit of a crop (in this case, pounds). We found that in clay soils, irrigating by timer was not a good approach from a water use efficiency perspective. In other words, we used more water but did not see improved yield in timer treatments. Surprisingly, irrigating based on soil moisture sensors did not improve water use efficiency when compared to feeling the soil. In sandy soils, there was no statistical difference in water use efficiency between the soil moisture sensor treatment, feel of soil treatment, and the control.  


H2: Following exposure and education, farmers will demonstrate changes in knowledge, attitudes, and awareness related to soil moisture technology.

As a result of participating in the workshops and focus groups, farmers reported that their knowledge about soil moisture sensors had increased. Participants also indicated that they would use soil moisture sensors in the future and that their confidence in using soil moisture sensors had increased. Farmers who participated in focus groups indicated that they would be willing to spend under $500 on soil moisture sensors for a 10% improvement in yield, but willingness to spend more was contingent upon a higher rate of return.


RQ1: What are the current barriers that keep NE farmers from investing in soil moisture sensing technology?

Labor is a barrier for using soil moisture sensing. A farmer or farm employee must regularly check the data generated by sensors and use that data to guide irrigation decisions. If farms do not have the personnel to both check sensor readings and then manage the irrigation system accordingly, then using sensors are not a good option. 

Cost is an additional barrier farmers face when accessing cellular and/or cloud-based data retrieval systems. Farmers would like to see a return on investment in expensive software systems before they decide to implement these systems. Software costs are fixed, meaning that they are more cost-efficient the most sensors a farmer uses. This makes the most sense for large farms with many irrigation zones. Small farms may find that the cost does not make sense until they are intensively monitoring high-value production areas, such as high tunnels.


RQ2: What changes to current tools/data systems should be made to increase their usefulness for NE vegetable growers?

Farmers are generally satisfied with the soil moisture sensors on the market, with granular matrix sensors and tensiometers being the most popular. Having a range of data-retrieval options at various price points meets the needs of growers and accommodates their diverse preferences for when and how they want to access this data. However, more farmers may be interested in cellular cloud-based data retrieval systems if software costs came down in price. Additionally, some farmers indicated a desire for automated alerts that would notify them when to start and stop irrigating at their location.

Participation Summary
22 Farmers participating in research

Education & Outreach Activities and Participation Summary

Educational activities:

15 Consultations
2 Curricula, factsheets or educational tools
1 Journal articles
1 On-farm demonstrations
1 Online trainings
1 Published press articles, newsletters
1 Tours
1 Workshop field days

Participation Summary:

50 Farmers participated
20 Number of agricultural educator or service providers reached through education and outreach activities
Outreach description:
  1. Presentation at one farmer twilight meeting at in Intervale Community Farm in Burlington Vermont (July 2019). We presented on soil moisture sensors, and discussed our field trials. 23 growers were in attendance.
  2. Participated in the UVM Horticulture Research Education Farm research field day (August 2019), where we discussed our project with 14 researchers and students.
  3. Presented a special session for the Climate Adaptation Fellowship participants on use of soil moisture sensors in diversified vegetable settings (online, March 2021).
  4. Presented at the New England Certified Crop Advisor Professional Development Conference (Portsmouth NH, January, 2020).
  5. Presented to the Wild Blueberry Commission of Maine (online, January 2021).
  6. Presented at the Maine Vegetable and Fruit School, hosted by University of Maine Extension (online, March 2021).
  7. Presented at the Vermont Vegetable and Berry Growers Association Annual Meeting (January 2022, online).
  8. Published one scholarly manuscript (based on a project that grew out of this grant: Schattman, R. E., Smart, A., Birkel, S., Jean, H., Barai, K., & Zhang, Y.-J. (2022). Strawberry growth under current and future rainfall scenarios. Water 14(3): 313. https://doi.org/10.3390/w14030313.
  9. Presented at the MOFGA Farmer to Farmer Conference (in person, November 2022)

Learning Outcomes

Key areas in which farmers reported changes in knowledge, attitude, skills and/or awareness:


Project Outcomes

2 Grants applied for that built upon this project
2 Grants received that built upon this project
$54,000.00 Dollar amount of grants received that built upon this project
4 New working collaborations
Success stories:

Several presentations have been given to farmer audiences based on this ongoing research:

  1. Jean, H. , Schattman, R. E., Faulkner, J. W., Maden, R. (2022). Turn the tap: Irrigation strategies for yield and quality in mixed vegetables. Vermont Vegetable and Berry Growers Association Annual Meeting. January 25, 2022 (online).
  2. Schattman, R. E. (2021). Irrigation strategies for diversified farmers. Maine Vegetable and Fruit School, University of Maine Extension. March 31, 2021 (online).
  3. Schattman, R. E. (2021) Water management in specialty crops: An overview of research from the University of Maine Agroecology Lab. Presentation to the Maine Wild Blueberry Commission. January 26, 2021.
  4. Schattman, R. E. (2020). Soil and water efficiency in specialty crops. New England Certified Crop Advisor Professional Development Conference. January 29, 2020. Portsmouth, NH

Additionally, a scholarly manuscript based on the spin-off project funded by the Maine Food and Agriculture Center was published:

  • Schattman, R. E., Smart, A., Birkel, S., Jean, H., Barai, K., & Zhang, Y.-J. (2022). Strawberry growth under current and future rainfall scenarios. Water 14(3): 313. https://doi.org/10.3390/w14030313.

Information gained through our research has been shared in informal ways with farmers from across the Northeast, and Drs. Schattman and Faulkner have advised several growers on soil moisture monitoring options for their farms. Typical decisions these farms are faced with that the PIs can help with include (a) the number of sensors needed, (b) strategic placement of sensors, and (c) data retrieval and monitoring options. An example of a decision made recently by a grower we have worked with in Vermont is: "After reading the info you sent on the different soil moisture meters, I'd like to go with the Watermark sensors and reader. I think two sensors per zone would be ideal; one at 6" and one at 12". We have a total of five irrigation zones, and we are grateful for any help we can receive to help us with our water management."

Assessment of Project Approach and Areas of Further Study:

2022: We have successfully implemented two seasons of the field trial at the UVM site (2019 and 2021), and one season at the UMaine site (2021), with a final bonus season planned for UMaine in 2022. This bonus season was not part of our original proposal but is supported by Dr. Schattman's startup funds at the University of Maine. We are mostly complete with data analysis for the VT 2019/2021 site and the ME 2021 site, and it is likely that we will not finish data analysis on ME 2022 until after the end of this SARE project, so we present our results to date in this report. In reviewing our experimental design and procedures, we have several recommendations for future research and outreach:

  1. The depth of lysimeter pans should be carefully considered. In this research, we situated our plots on two different field sites, with free draining lysimeters buried at the same depth at each site. In retrospect, crop root depth was likely influenced by soil type and drainage capacity of the soil, and lysimeters should have been placed based on this variation. Assessing a crop planting the year prior to lysimeter installation (i.e. measuring the crop root length) would have given us a better idea of how deep to bury the lysimeters.
  2. Crops of different families and varieties are often planted close together in diversified farming systems. Irrigation zones can sometimes include multiple crop families, depending on farmers' irrigation designs. Our results show that crops respond differently to irrigation cued by soil moisture sensors, however. Specifically, we started irrigating in soil moisture sensor plots when conditions exceeded 20 cB. In cucumbers, this approach led to a small decline in crop quality when compared to the control treatment (which received only ambient precipitation and no supplemental irrigation). However, crop quality was enhanced in peppers. Some quality parameters in tomatoes improved with use of soil moisture sensors (i.e., color uniformity) but declined in others (i.e., shape, firmness, gloss, and number of defects). This demonstrates that designing irrigation systems with an optimal number of zones may be a challenge for highly diversified operations, and best practices should be further investigated.
  3. Our results suggest that ambient precipitation, rather than how much water is applied through drip irrigation, is a bigger driver of both leachate amount and N-concentration in leachate. This means that farmers may not need to be as concerned about the effect of drip irrigation on fertilizer efficacy and water body contamination, but that split fertilizer applications may still be a good way to protect against loosing nutrients to heavy rainfalls. Timing fertilizer applications to align with crop needs is important, but it's also important not to apply fertilizer prior to large precipitation events. How to manage fertility in the context of a changing climate, where heavy rainfall events are anticipated to become more common, is an important area of research that should be further supported. 

2020: Due to COVID-19, we were unable to implement field trials at either the UVM or UMaine sites. We applied for (and received) extensions both on our SARE project and the UMaine funding that supports the extension at the UMaine Rogers Farm site. However, we were able to install lysimeters at the UMaine site, which means we will be ready to go at both sites in the 2021 growing season. Additionally, a graduate student (Haley Jean) at UMaine was brought on to help with the project. Ms. Jean has been developing R code and analysis procedures using 2019 data from Vermont. Once complete, this "data pipeline" will allow for a relatively easy analysis of the full, multi-year, multi-site data set. Ms. Jean will work with our team in 2021 to collect data in Maine and will use data from both sites for her M.S. thesis.

Prior to the onset of COVID-19, we were able to collect data at two additional farmer focus groups. The first of these was held at the Pennsylvania Association of Sustainable Agriculture (PASA) in February (5 farmers attended), and at the Vermont Vegetable and Berry Growers Association annual meeting in January (4 farmers attended). Data from all four focus groups still needs to be summarized. I would not recommend holding focus groups at farmer conferences in the future: attendance was lower than we had hoped, and it was difficult to convince people to attend, even with a financial incentive and lunch provided.

2019: This was a very productive season in terms of data collection. We successfully installed the irrigation field trials at the UVM Horticulture Research Education Center (HREC), including a soil moisture monitoring network, and lysimeter pans and ports. We established a successful crop of tomatoes, cucumbers, and green peppers, as well as a harvesting and crop evaluation protocol. Our research team included a lab technician, a field-based research assistant, a nutrient management specialist, in addition to the two project leaders (Schattman and Faulkner). 

In addition, we held 2 focus groups: the first was held at the Farmer-to-Farmer Conference hosted by the Maine Organic Farming and Gardening Association (MOFGA) in November (9 farmers attended). The second was held at the New England Vegetable and Fruit Growers Conference in Manchester NH in December (3 farmers attended, and 5 service providers). Two more focus groups are planned for 2020: In January we will hold on at the Vermont Vegetable and Berry Growers Association annual meeting in VT, and in February we will host our final focus group at the Pennsylvania Sustainable Agriculture (PASA) conference in Lancaster PA (where 15 people are already registered). 

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.