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Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1
Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1
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Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1
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Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1
Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1
Journal Article

Can net energy values be determined from animal performance measurements? A review of factors affecting application of the California Net Energy System1

2019
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Overview
Abstract The California Net Energy System (CNES) can reliably project performance of feedlot cattle based on three factors: expected dry matter intake (DMI), some index of degree of maturity of cattle linked to body composition (fat and protein content), and an estimate of the net energy (NE) content of the diet. The CNES allowed feedlot managers to monitor growth and efficiency of individual pens of cattle. Through assigning distinct values for net energy for maintenance (NEm) vs. net energy for gain (NEg) of the metabolizable energy (ME) present in feeds, the CNES enables valid economic comparisons among feedstuffs, an appraisal not feasible based on total digestible nutrients or digestible energy (DE) values. Because NEm and NEg are linked mathematically to ME, the CNES also allows performance-adjusted ME (paME) value of diets to be calculated from observed DMI and growth or carcass measurements. Compared with other productivity measures (e.g., average daily gain and gain-to-feed ratio) that are confounded with and affected by DMI, the CNES logically separates production responses by cattle into two factors—DMI and ME of the diet. This enables research scientists or cattle producers to appraise responses within these two factors independently. In feeding studies, means of paME values were related closely to ME values of diets calculated from the ME of diet ingredients. But unlike ME values projected from diet analyses, paME estimates are affected by environmental conditions (e.g., season, weather, animal interactions, stress, nutritional history and deficiencies, associative effects of feeds, imprecise feed management, and animal healthfulness and disorders). These factors typically overestimate ME intake or increase energy requirements, both of which decrease energetic efficiency. By comparing paME with ME values calculated from diet composition, logical reasons behind performance responses to and quantitative benefits from feed additives, grain processing, hormone implants, and animal management can be appraised. Considering the evolution in cattle types, management and marketing conditions, and changes in diet ingredients and processing that have occurred during the past 50 yr, updating by a skilled committee to correct certain anomalies within the CNES as currently being applied seems appropriate. Developing simplified spreadsheets could help users evaluate their own dietary and management conditions and assure that the CNES continues to be widely applied by the feedlot industry within the United States and worldwide.
Publisher
Oxford University Press
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