Standardized Performance Analysis (SPA) Summary for 1999-2000 Veterinary Medicine Students

Nine Iowa State University veterinary medical students completed SPA records on herds from Iowa, North Dakota and South Dakota. The Iowa herds were included in the SPA summary for Iowa, but the six North and South Dakota herds were summarized separately. These six herds had an average herd size of 371 cows and had a financial return to capital, labor and management of $175 per cow. Total financial cost per cow averaged $286 for these herds with a range of $211 to $388. Feed utilized averaged 4,442 pounds of dry matter per cow and the average pounds of calf produced per exposed female was 506 pounds.

Critical Control Points for Profitability in the Cow-Calf Enterprise

Financial, economic, and biological data collected from cow-calf producers who participated in the Illinois and Iowa Standardized Performance Analysis (SPA) programs were used in this study. Data used were collected for the 1996 through 1999 calendar years, with each herd within year representing one observation. This resulted in a final database of 225 observations (117 from Iowa and 108 from Illinois) from commercial herds with a range in size from 20 to 373 cows. Two analyses were conducted, one utilizing financial cost of production data, the other economic cost of production data. Each observation was analyzed as the difference from the mean for that given year. The independent variable utilized in both the financial and economic models as an indicator of profit was return to unpaid labor and management per cow (RLM). Used as dependent variables were the five factors that make up total annual cow cost: feed cost, operating cost, depreciation cost, capital charge, and hired labor, all on an annual cost per cow basis. In the economic analysis, family labor was also included. Production factors evaluated as dependent variables in both models were calf weight, calf price, cull weight, cull price, weaning percentage, and calving distribution. Herd size and investment were also analyzed. All financial factors analyzed were significantly correlated to RLM (P < .10) except cull weight, and cull price. All economic factors analyzed were significantly correlated to RLM (P < .10) except calf weight, cull weight and cull price. Results of the financial prediction equation indicate that there are eight measurements capable of explaining over 82 percent of the farm-to-farm variation in RLM. Feed cost is the overriding factor driving RLM in both the financial and economic stepwise regression analyses. In both analyses over 50 percent of the herd-to-herd variation in RLM could be explained by feed cost. Financial feed cost is correlated (P < .001) to operating cost, depreciation cost, and investment. Economic feed cost is correlated (P < .001) with investment and operating cost, as well as capital charge. Operating cost, depreciation, and capital charge were all negatively correlated (P < .10) to herd size, and positively correlated (P < .01) to feed cost in both analyses. Operating costs were positively correlated with capital charge and investment (P < .01) in both analyses. In the financial regression model, depreciation cost was the second critical factor explaining almost 9 percent of the herd-to-herd variation in RLM followed by operating cost (5 percent). Calf weight had a greater impact than calf price on RLM in both the financial and economic regression models. Calf weight was the fourth indicator of RLM in the financial model and was similar in magnitude to operating cost. Investment was not a significant variable in either regression model; however, it was highly correlated to a number of the significant cost variables including feed cost, depreciation cost, and operating cost (P < .001, financial; P < .10, economic). Cost factors were far more influential in driving RLM than production, reproduction, or producer controlled marketing factors. Of these cost factors, feed cost had by far the largest impact. As producers focus attention on factors that affect the profitability of the operation, feed cost is the most critical control point because it was responsible for over 50 percent of the herd-to-herd variation in profit.

Effects of Pasture Conditions in Spring on Seasonal Forage Productivity

Fifteen beef cow-calf producers in southern Iowa were selected based on locality, management level, historical date of grazing initiation and desire to participate in the project. In 1997 and 1998, all producers kept records of production and economic data using the Integrated Resource Management-Standardized Performance Analysis (IRM-SPA) records program. At the initiation of grazing on each farm in 1997 and 1998, Julian date, degree-days, cumulative precipitation, and soil moisture, phosphorus, and potassium concentrations were determined. Also determined were pH, temperature, and load-bearing capacity; and forage mass, sward height, morphology and dry matter concentration. Over the grazing season, forage production, measured both by cumulative mass and sward height, forage in vitro digestible dry matter concentration, and crude protein concentration were determined monthly. In the fall of 1996 the primary species in pastures on farms used in this project were cool-season grasses, which composed 76% of the live forage whereas legumes and weeds composed 8.3 and 15.3%, respectively. The average number of paddocks was 4.1, reflecting a low intensity rotational stocking system on most farms. The average dates of grazing initiation were May 5 and April 29 in 1997 and 1998, respectively, with standard deviations of 14.8 and 14.1 days. Because the average soil moisture of 23% was dry and did not differ between years, it seems that most producers delayed the initiation of grazing to avoid muddy conditions by initiating grazing at a nearly equal soil moisture. However, Julian date, degree-days, soil temperature and morphology index at grazing initiation were negatively related to seasonal forage production, measured as mass or sward height, in 1998. And forage mass and height at grazing initiation were negatively related to seasonal forage production, measured as sward height, in 1997. Moreover, the concentrations of digestible dry matter at the initiation of and during the grazing season and the concentrations of crude protein during the grazing season were lower than desired for optimal animal performance. Because the mean seasonal digestible dry matter concentration was negatively related to initial forage mass in 1997 and mean seasonal crude proteins concentrations were negatively related to the Julian date, degree-days, and morphology indeces in both years, it seems that delaying the initiation of grazing until pasture soils are not muddy, is limiting the quality as well as the quantity of pasture forage. In 1997, forage production and digestibility were positively related to the soil phosphorus concentration. Soil potassium concentration was positively related to forage digestibility in 1997 and forage production and crude protein concentration in 1998. Increasing the number of paddocks increased forage production, measured as sward height, in 1997, and forage digestible dry matter concentration in 1998. Increasing yields or the concentrations of digestible dry matter or crude protein of pasture forage reduced the costs of purchased feed per cow.