Rising Plate Meter Calibrations for Forage Mass of Wheat and Rye

Abstract

Estimating forage availability is important in optimizing livestock stocking rates. The rising plate meter was developed to estimate forage availability. It needs a calibration equation to convert its measurement to a prediction of forage mass, and predictions can vary across crops, seasons, and locations. Our research objective was to derive new calibration equations for wheat (Triticum aestivum L.) and rye (Secale cereale L.). Most past literature used a linear model, but recent literature has suggested that using a quadratic model without an intercept could improve predictions. A non-nested test was used to test among these two non-nested models for wheat and rye calibration equations. The results favored the more encompassing model of a quadratic with an intercept; however, with wheat the quadratic with no intercept was not rejected. A pooling test indicated different equations were needed for species, seasonality (winter and non-winter), and tillage type (tilled or no-till).

Evaluating nondestructive forage sampling techniques in alfalfa–bermudagrass mixtures in the southeastern United States

“…Alfalfa's growth will slow and its con-tribution to the stand will decline in August, but an alfalfa stand will rebound and increase its contribution in the fall, as reported by Hendricks et al (2020). Furthermore, many of these calibration models are farm-or season-specific (Cho et al, 2019;Dillard et al, 2016;Sanderson et al, 2001).…”

“…According to the results of the current work, a relatively large sample size is required to determine the canopy cover. The majority of forage research trials have found a 1-ft 2 quadrat to be sufficient for estimating HM (Cho et al, 2019;Dillard et al, 2016;Mason, 2020), whereas Baxter et al ( 2017) used a 10.7-ft 2 quadrat. The region's climate, coupled with the morphological characteristics of the ABG, resulted in a dense forage canopy with little bare ground, which saturated the images used in the ImageJ analysis.…”

“…(2020). Furthermore, many of these calibration models are farm‐ or season‐specific (Cho et al., 2019; Dillard et al., 2016; Sanderson et al., 2001). Although they are reported to be more accurate than season‐long equations, these models cannot be translated to a wide range of forage and livestock producers who need a simple method for quickly and accurately determining HM.…”

“…Mason (2020) reported a similar response to the present study when plant height was used to predict HM: R 2 = .42, RMSE = 567 lb DM acre –1 , and CV = 51%. Most other available literature on the nondestructive determination of HM, specifically via plant height or the RPM, has been conducted on cool‐season forages (Baxter et al., 2017; Cho et al., 2019; Dillard et al., 2016; Sanderson et al., 2001). In contrast to other cool‐season legumes, alfalfa is productive through the summer months.…”

CALIBRATION OF THE RISING PLATE METER FOR MIXED PASTURES OF RYEGRASS (Lolium perenne L.) AND KIKUYO (Cenchrus clandestinus)

“…The simple linear regression is a model that fit to predict the AHM in CH function. In fact, this is the most commonly used model for RPM calibration tests in different forage species (Michell, 1982;Michell and Large, 1983;Van der Colf, et al, 2013;Nakagami, 2016;Harmse et al, 2019;Cho, et al, 2019;Rayburn, 2020). Dillard et al (2016) evaluated the performance of the RPM in multispecies pastures composed of grasses, legumes and weeds, and reported that even, when equating the intercept to 0, the best prediction equation is a linear regression.…”