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STUDIES SHOW IRRIGATING USING SOIL SENSORS INCREASE PROFITS BY 21%

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Agronomist and Freelance Author

13 Feb 2017

USDA–NIFA Specialty Crops Research Initiative funded a study with to objectively measure the financial impact soil-measurement sensors. University of Maryland used a 10,000m2 greenhouse growing operation and compared profit and yield with and without sensor technology. They and crunched the numbers and learned that investing in a soil sensor system is one of the best investments a farmer can make, generating an return on investment of 21% including repaying equipment. In addition, the gardenia’s grew to full maturity in 11 months instead of 22 which doubles profits on an annualized basis. The increase in profits was demonstrated through a combination of input savings, yield increases, reduced production time and efficient use of fertilizer and several practices.

The USDA-funded-study was run by University of Maryland researchers Erik Lichtenberg, John Majsztrik, and Monica Saavoss; and used research data from greenhouse operations in Dearing, GA. The study used a large commercial nursery in a 20,000 ft2 unheated greenhouse growing MAGDA 1 gardenias. The sensor-based irrigation was setup to irrigate when water content dropped below 0.20 m3 .m-3. The other 5,000m2 of the greenhouse were told to irrigate according to their regular practice. The sensors used for this study is very similar to the connected Crops Advanced Irrigation Station, however the Connected Crops unit has the added benefit of having the data accessible on a mobile app.

Table 2. Annualized revenue, expenditures, and profit: wireless sensor system versus standard practice, based on greenhouse production of gardenias for an operation in Dearing, GA.

Standard practice ($) Sensor-based irrigation ($)
Annualized revenue 66,297.36 145,505.64
Annualized production expenditures 30,539.11 50,039.93
Annualized sensor system cost 3,755.24
Annualized profit 35,758.24 91,710.47
Annualized revenue per foot2 $3.31 / ft2 $7.28 /ft2
Annualized production expenditures $1.53 / ft2 $2.50 / ft2
Annualized sensor system cost per foot2 $0.19 / ft2
Annualized profit per foot2 $1.79 / ft2 $4.59 / ft2

Increase in annualized profit: 116%

$1.00/ft2 = $10.7639/m2.

“Sensor-based irrigation can reduce irrigation water use without risking adverse consequences from under- or overwatering.”

John Majsztrik., 2013

The study found that the standard practice had expenditures of $53,019 and a profit of $62,080; while the sensor based irrigation had expenditures of $54,941 and profit of $74,837; this represented a 20.6% increase of profit. However, the standard practice needed 22 months for a complete harvest cycle, while a sensor based irrigation needed half the time and completed in 11 months. On an annualized basis, the sensor based irrigation produced a 116% increase in profit over standard methods.

Monthly tracking of expenses, revenue and profit is provided below:

Monthly accounting of present-value expenditures, sales, revenues, and profits for the production of gardenias
at a greenhouse operation in Dearing, GA

Standard Practice Sensor-based irrigation
Month Expenditure Revenue Profit Expenditure Revenue Profit
June 0 29,17 39,483
July 1,432 -1,432 1,439 –1,439
August 1,432 –1,432 1,432 –1,432
September 1,425 –1,425 1,425 –1,425
October 1,417 –1,417 1,417 –1,417
November 1,296 –1,296 1,296 –1,296
December 2,287 –2,287 2,277 –2,277
January 1,256 –1,256 1,245 –1,245
February 1,236 –1,236 1,219 11,449 10,230
March 1,216 –1,216 1,194 50,135 48,941
April 1,302 –1,302 1,271 37,898 36,626
May 1,281 15,374 14,093 1,244 30,297 29,052
June 3,369 7,162 3,793 0 0 0
July 1,027 6,347 5,320 0 0 0
August 947 24,497 23,550 0 0 0
September 696 17,000 16,303 0 0 0
October 518 12,763 12,245 0 0 0
November 349 2,221 1,872 0 0 0
December 565 0 –565 0 0 0
January 301 0 –301 0 0 0
February 287 10,698 10,412 0 0 0
March 179 16,807 16,628 0 0 0
April 21 2,230 2,209 0 0 0
Total 53,019 15,099 62,080 54,941 129,779 74,837

The research team attributed the dramatic increase in profits due reduced expenditures in irrigation water, labor, energy, and fertilizer expenditures. They also found other less obvious potential benefits are: lower disease pressure, often caused by precautionary overwatering (Majsztrik et al., et al., 2012). Historically, 18.2% of gardenia plants died or could not be sold; however the sensor-based irrigation reduced that by approximately half. Lower disease pressure means reduced crop losses in addition to less fungicide use. Better matching of water availability to plant uptake has also been shown to accelerate growth in some instances (Chappell et al., 2013). Shorter production times mean higher profits, just as lower costs do.

“Better matching of moisture availability with plant demands can also reduce leaching of nutrients, resulting in fertilizer savings as well as water savings.”

The results from this study have been reproduced by university research with many different types of crops. Although rates of return do vary based on the type of crop, all studies show a dramatic increase in profits based advanced use of soil water content and other related data.

A separate Colorado University study on Maize, evaluated state irrigation recommendationslevels based on estimated values for water use efficiency, evapo-transportation. The study found that the state irrigations recommendations were overstated by 43% compared on actual soil measurements; demonstrating a big savings not only on the cost of water, but also increasing the effectiveness of fertilizer and other methods. “During the period July 15th to October 4th, CoAgMet recommended that 360 mm of water needed to be replenished to the soil (423 mm ET – 63 mm precipitation). Assuming furrow irrigation efficiency of 60%, this results in a required application depth of 599 mm. Improved Agricultural Irrigation Scheduling Using a Soil Water Content Sensor 99 However, the measured depth of irrigated water applied to this plot was 342 mm, which is a savings of 43%” (http://hydrologydays.colostate.edu/Papers_2011/Varble_paper.pdf, p4)

Precision technology requires both financial investment and incorporating new information into farming practices. The fixed and variable costs associated with irrigation continue trending upward with shifts in energy, water, labor, and equipment costs; the modern farmer uses new technology and new methods to fight back. ConnectedCrops is the next advanced tool that a farmer must use when making decisions to a) maximize yield, b) maximize crop water use efficiency or maximize profit.

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