Simple, Low-Cost Data Collection Methods for Agricultural Field Studies

Publishing in refereed journals has long been a requirement for Extension specialists with university faculty status. Because several states also have granted Extension agents faculty status, the requirement for refereed publications as evidence of scholarly activity is now becoming more common for field agents as well. O'Neill (1990) described 10 tips for Extension agents on getting published in a refereed journal. The first tip was to write about what you know. Agriculture Extension agents know agriculture and frequently conduct field trials that, with the appropriate data collection techniques, experiment controls, and replication, can lead to a refereed journal publication.

Loveridge (1998) noted that Extension field personnel can be at a disadvantage when conducting research because of the distance from a university campus and lack of infrastructure (equipment) and monetary support. A major limitation for field personnel conducting agricultural research is obtaining adequate quantitative data for statistical analysis.

A recent literature search reveals an abundance of simple and relatively inexpensive methods for gathering quantitative data from agriculture experiments. This article briefly summarizes and cites various methods to make agents aware of these field data collection opportunities. This list is not meant to be exhaustive, but rather to provide field agents with ideas for data collection methods that may be used in field studies.

Validity of Data Collection Methods

Prior to adopting any new methodology, one has to ask whether the method will be valid in the context in which it will be used. We recommend that researchers return to the original references cited in this paper and critically evaluate whether a method is appropriate for their intended use. Some critical evaluation has already occurred if the method was published in a refereed journal. However, additional research may be necessary before determining whether the method is appropriate for the situation in which it will be used.

Data Collection Methods

On-Farm Trials

On-farm trials, whether with demonstration plots or replicated treatments, have long been the primary vehicle for applied research in Extension (Kittrell, 1974). The advantages of on-farm trials include:

• Equipment used for field work is frequently owned by the farmer, eliminating the need for the agent to purchase equipment or borrow from campus sources;
• On-farm trial plots sizes are commonly large because equipment is farm scale; and
• Research is done on a producer's farm, which can lend additional credibility to the data and facilitate the adoption of new technology by other producers (Rzewnicki, 1991).

In many situations, on-farm trials minimize the need for Extension agent equipment resources and are an established and efficient way to conduct publishable research.

Various guides have been produced to aid in designing valid on-farm field trials (Miller, Adams, Peterson, & Karow, 1992). Recent variations of on-farm trials include using demonstration plots and single farms as replications for, among other practices, evaluating hybrid performance and fertilizer responses across a county, state, or region (Posner & Crawford, 1992; Devlin, Christian, & Fjell, 1994). These variations provide an alternative to conducting a replicated trial at each location, and data may still be analyzed using traditional statistical procedures (Nafziger, 1984).

Yield Measurements

Yield is the most frequent parameter measured in agricultural field trials. Direct harvest is the most accurate method of measuring yield. However, unless plots are large enough to use farmer equipment, an agent must have the equipment for harvesting and weighing, or use indirect methods to estimate yield.

Yield from small plots or subsampled yield from larger plots can be determined by directly harvesting plant material from a known area. A known area can be harvested within an inexpensive frame made of PVC or wood, or along a measured linear distance for row crops. A sickle mower or rechargeable or manual clippers can be used to harvest plant material from small plots. The tissue can then be weighed and yield calculated from the weight and harvest area. Grain plots also can be harvested by hand and a representative sample of heads or ears shelled by hand. The total cost of equipment to measure yield from small plots can be under $1,000.

Various indirect methods for measuring forage yield have been developed and successfully tested against direct harvest measurements. Some success with simple visual techniques has been reported (Laca, Demment, Winckel, & Kie, 1989); however, visual estimates of yield have not gained widespread acceptance in published research.

The rising plate meter is a simple tool utilizing a graduated shaft with a sliding plate to measure forage production and utilization (Scrivner, Center, & Jones, 1986). One end of the shaft is placed on the ground, and the plate is allowed to fall from a fixed height. The height and density of the forage prevents the plate from falling to the ground, and a measurement of plate height taken from the graduated shaft is related to yield via a calibration curve. The rising plate meter can be calibrated for specific situations (Gourley & McGowan, 1991), or one may use pre-established calibration curves if appropriate (Earle & McGowan, 1979).

Canopy height and leaf area index measurements have also been correlated to direct harvest yield measurements for various forages (Harmoney, Moore, George, Brummer, & Russell, 1997). Whenever indirect measurements are used, the method and actual measurements collected should be reported, as well as the yield derived from the measurement.

One additional challenge in determining yield for direct harvested agricultural experiments is variations in tissue water content. For example, forages vary in water content among species and at different times of the season (Laca et al., 1989). Therefore, the assumption of average and constant moisture content may result in errors in dry matter yield estimates. Rapid (10 minute) sample drying using a microwave oven is comparable to drying in a forced air oven at 55 degrees C for 24 hours (Schuman & Rauzi, 1981). This method apparently does not affect the nitrogen and phosphorus content of forage samples; however, feed quality parameters may be affected by microwave drying (Carlier & van Hee, 1971).

Forage Quality Evaluation

Techniques for field evaluation of alfalfa quality parameters (primarily acid and neutral detergent fibers) based on the tallest stem and maturity of the most mature stem have been developed in several states (Owens, Albrecht, & Hintz, 1995; Sulc et al., 1997). These techniques have been used mainly for pre-harvest quality evaluations and in decisions regarding harvest timing. Widespread use of these techniques for alfalfa quality assessment in research settings has not been reported.

Weed Control Effectiveness

The effectiveness of various weed control methods has been evaluated by visual rating scales (e.g., percent control) and weed counts per unit area (Willard, 1958; Frans & Talbert, 1977; McDaniel, Hart, & Carrol, 1997). Both of these methods are routinely reported in weed control literature. In addition, both methods have been expanded to include ratings of crop herbicide injury (Steckel, Defelice, & Sims, 1990).

Plant Nutrient Status

Chlorophyll meters have been used to rapidly assess the green color of leaves of various plant species (Peryea & Kammereck, 1997; Varvel et al., 1997; Bullock & Anderson, 1998). Relationships between meter reading and nutritive status or yield have been developed for certain plants; however, universal calibration curves relating meter readings to tissue nutrient (e.g., nitrogen or iron) content have not been developed. Chlorophyll meter data may be useful for comparing treatments such as nitrogen or iron rates. Readings may also be related to yield to develop localized data for routine use of the meter during field monitoring.

A simple visual rating scale (1=yellow through 9=green) has been used extensively to monitor turfgrass color and response to nitrogen or iron treatments (Wehner & Haley, 1990). A similar four-point scale also has been adapted to evaluate tree leaf color in response to iron treatments (Messenger, 1984). Color index scales may be improved by using standardized colors from sources such as the Munsell color chart for plant tissues (Wilde & Voigt 1952; Harrell, Pierce, Mooter, & Webster, 1984).

Rapid analysis of plant sap using portable meters or test strips (Prasad & Spiers, 1984) has been related to traditional colorimetric methods with some success. Use of quick test methods should be preceded by further research into the method to determine whether it has been successfully used for the specific situation.

Other Measures of Plant Performance

Many other simple and inexpensive measures of plant performance are routinely used in agricultural field research. Measured plant height may be a useful tool to evaluate different varieties or treatment effects on plant growth. Stand counts can be used to evaluate effects of treatments or other variables on seed germination and plant population. Yield component analysis, including tillers/area, ear or head number/plant, and seed counts, has also been used to evaluate performance among varieties or treatments. In addition, seed samples brought to local elevators can be tested for moisture and test weight using available equipment, often at no charge. Finally, rating scales or estimates of percent lodging and disease occurrence also are simple methods for gaining quantitative data from field experiments.

References

Bullock, D.G. & Anderson, D.S. (1998). Evaluation of the Minolta SPAD-502 chlorophyll meter for nitrogen management in corn. J. Plant Nutrit., 21, 741-755.

Carlier, L.A. & van Hee, L.P. (1971). Microwave drying of lucerne and grass samples. J. Sci. Fd Agric., 22, 306-307.

Devlin, D.L., Christian, M.L., & Fjell, D.L. (1994). Developing an on-farm testing and demonstration program for grain sorghum hybrids. J. Nat. Resour. Life Sci. Educ., 23, 59-60.

Earle, D.F. & McGowan A.A. (1979). Evaluation and calibration of an automated rising plate meter for estimating dry matter yield of pasture. Aust. J. of Exp. Agr. and Anim. Husb., 19, 337-343.

Frans, R.E. & Talbert, R.E. (1977). Design of field experiments and the measurement and analysis of plant responses. In B. Truelove (Ed) research methods in weed science (2nd ed.). Southern Weed Science Society.

Gourley, C.J.P., & McGowan, A.A. (1991). Assessing differences in pasture mass with an automated rising plate meter and a direct harvesting technique. Aust. J. of Exp. Agric., 31, 337-339.

Harmoney, K.R., Moore, K.J., George, J.R., Brummer, E.C. & Russell, J.R. (1997). Determination of pasture biomass using four indirect methods. Agron. J., 89, 665-672.

Harrell, M.O., Pierce, P.A., Mooter, D.P., & B.L. Webster. (1984). A comparison of treatments for chlorosis of pin oak and silver maple. J. Arboric., 10, 246-249.

Kittrell, B.U. (1974). Result demonstration technique--history, philosophy, and contemporary nature. J. Agron. Educ., 3, 90-94.

Laca, E.A., Demment, M.W., Winckel, J., & Kie, J.G. (1989). Comparison of weight estimate and rising plate meter methods to measure herbage mass of a mountain meadow. J. Range Manage., 42, 71-74.

Loveridge, S. (1998). Publishing research in extension. Journal of Extension [On-line], 36(3). Available: http://www.joe.org/joe/1998june/tt2.html.

Messenger, S. (1984). Treatment of chlorotic oaks and red maples by soil acidification. J. Arboric., 10, 122-128.

McDaniel, K.C., Hart, C.R., & Carrol, D.B. (1997). Broom snakeweed control with fire on New Mexico blue grama rangeland. J. Range Manage., 50, 652-659.

Miller, B., E. Adams, P. Peterson, & R. Karow. (1992). On-farm testing A grower's guide. Extension bulletin EB1706, Washington State University, Pullman.

Nafziger, E.D. (1984). Use of demonstration plots as extension tools. J. Agron. Educ., 13, 47-49.

O'Neill, B. (1990). How to get published in a professional journal. Journal of Extension [On-line], 28(3). Available: http://www.joe.org/joe/1990fall/tt2.html

Owens, V.N., Albrecht, K.A., & R. W. Hintz. (1995). A rapid method for predicting alfalfa quality in the field. J. Prod. Agric., 8, 491-495.

Peryea, F.J. & Kammereck, R. (1997). Use of Minolta SPAD-502 chlorophyll meter to quantify the effectiveness of mid-summer trunk injection of iron on chlorotic pear trees. J. Plant Nutrit., 20, 1457-1463.

Posner, J.L. & Crawford, E.W. (1992). Improving fertilizer recommendations for subsistance farmers in West Africa: The use of agro-economic analysis of on-farm trials. Fert. Res., 32, 333-342.

Prasad, M. & Spiers, T.M. (1984). Evaluation of a rapid method for plant sap nitrate analysis. Comm. Soil Sci. Plant Anal., 15, 673-679.

Rzewnicki, P. (1991). Farmers' perceptions of experiment station research, demonstrations, and on-farm research in agronomy. J. Agron. Educ., 20, 31-36.

Schuman, G.E. & Rauzi, F. (1981). Microwave drying of rangeland forage samples. J. Range Manage., 34, 426-428.

Scrivner, J.H., Center, D.M., & Jones, M.B. (1986). A rising plate meter for estimating production and utilization. J. Range Manage., 39, 475-477.

Steckel, L.E., Defelice, M.S., & Sims, B.D. (1990). Integrating reduced rates of post-emergence herbicides and cultivation for broadleaf weed control in soybeans (Glycine max). Weed Sci., 38, 541-545.

Sulc, R.M., Albrecht, K.A., Cherney, J.H., M.H. Hall, Mueller, S.C., & Orloff, S.B. (1997). Field testing a rapid method for estimating alfalfa quality. Agron. J., 89, 952-957.

Varvel, G.E., Schepers, J.S., & Francis, D.D. (1997). Ability for in-season correction of nitrogen deficiency in corn using chlorophyll meters. Soil Sci. Soc. Am. J. 61, 1233-1239.

Wehner, D.J., & J.E. Haley. (1990). Iron Fertilization of kentucky bluegrass. Comm. Soil Sci. Plant Anal., 21, 629-637.

Wilde, S.A. & Voigt, G.K. (1952). The determination of color of plant tissues by the use of standard charts. Agron. J. 44:499-500.

Willard, C.J. (1958). Rating scales for weed control experiments. Weeds, 6, 327-328.