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PubMed · 3397338

Optimal beef cattle diets formulated by nonlinear programming.

G Hertzler·D E Wilson·D D Loy·G H Rouse
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Abstract

A beef diet model based on National Research Council recommendations is significantly nonlinear for feed ingredients, daily gain and weight of cattle. Solving a diet model has been difficult, but advances in nonlinear programming now allow solutions that are quick and easy. This study developed a nonlinear programming method for optimally planning a feeding program by choosing feeds, daily gains and selling weight. Two types of diets are important for this purpose:optimal-return diets and least-cost-gain diets. For a given weight of cattle, an optimal-return diet chooses feeds and daily gain to maximize returns above feed costs. A least-cost-gain diet chooses feeds and daily gain to minimize feed plus yardage costs per kilogram of gain. In an optimal feeding program, a sequence of optimal-return diets is fed to increasing weights of cattle. Feed costs plus yardage per kilogram of gain rise to equal the actual selling price at the optimal selling weight, and the cattle are sold. Cattle feeders and researchers with access to a microcomputer can maximize net returns from a feeding program.

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G Hertzler, D E Wilson, D D Loy, G H Rouse. 1988. Optimal beef cattle diets formulated by nonlinear programming.. https://doi.org/10.2527/jas1988.6651115x

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PubMed1995

Use of performance ratios to calculate the economic impact of thin cows in a beef cattle herd.

OBJECTIVE: To determine gross income lost that was attributable to thin cows in a beef cattle herd, to estimate the cost of added nutrition necessary to prevent thin cows in the herd, and to determine the financial outcome of the improved nutritional practices. DESIGN: Prospective, observational study. ANIMALS: Four hundred and twenty-two Santa Gertrudis cows and their calves. PROCEDURE: At pregnancy examination in the fall of 1992, cows were assigned a body condition score (BCS), using a scale of 1 (emaciated) to 9 (obese), and the ratio of the productivity of BCS-3 and BCS-4 cow groups (thin cows), compared with the mean productivity of BCS-5 and BCS-6 cows (cows in good condition), was determined. Measures of productivity evaluated included pregnancy rates, weaning weights, and prices per hundredweight of calves. The performance ratios of BCS-3 and BCS-4 cows were multiplied by the mean gross income of BCS-5 and BCS-6 cows to calculate their gross income. This was then subtracted from the mean income of BCS-5 and BCS-6 cows to estimate the amount of lost gross income per thin cow. The cost of a nutritional program that would prevent thin cows in the herd was subtracted from the lost gross income of the thin cows to yield the amount of increased net income that could be generated from a nutritional program that would maintain cows in the herd at a BCS of 5 or 6. RESULTS: Cows with a BCS of 3 were 0.48 as productive, and cows with a BCS of 4 were 0.74 as productive as the average of the BCS-5 and BCS-6 cows combined. Each BCS-3 cow generated $215.06 less, and each BCS-4 cow generated $107.53 less gross income than the average gross income of BCS-5 and BCS-6 cows. The added cost of nutrition that would have reconditioned BCS-3 and BCS-4 cows to a BCS of 5.5 was $91.48/BCS-3 cow and $43.67/BCS-4 cow. Implementation of the reconditioning nutrition program the previous fall would have resulted in an extra net income of $123.58/BCS-3 cow and $63.86/BCS-4 cow, received over a 2-year period. The 262 thin cows in the herd accounted for a total net income loss of $19,897. CLINICAL IMPLICATIONS: The time of pregnancy examination is a strategic intervention point to estimate the past negative economic impact of thin cows and to implement a plan to prevent these losses in the future. Pregnancy examinations should be performed at least 100 days before the beginning of the calving season, and thin pregnant cows should be sorted into a special group and fed a reconditioning diet that will improve their body condition to an average BCS of 5.5 by the onset of the calving season.

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