Predicting beef tenderness using color and multispectral image texture features.

The objective of this study was to investigate the usefulness of raw meat surface characteristics (texture) in predicting cooked beef tenderness. Color and multispectral texture features, including 4 different wavelengths and 217 image texture features, were extracted from 2 laboratory-based multispectral camera imaging systems. Steaks were segregated into tough and tender classification groups based on Warner-Bratzler shear force. The texture features were submitted to STEPWISE multiple regression and support vector machine (SVM) analyses to establish prediction models for beef tenderness. A subsample (80%) of tender or tough classified steaks were used to train models which were then validated on the remaining (20%) test steaks. For color images, the SVM model correctly identified tender steaks with 100% accurately while the STEPWISE equation identified 94.9% of the tender steaks correctly. For multispectral images, the SVM model predicted 91% and STEPWISE predicted 87% average accuracy of beef tender.

Effects of increasing field pea (Pisum sativum) level in high-concentrate diets on growth performance and carcass traits in finishing steers and heifers.

Three experiments were conducted to determine the effect of increasing field pea level in high-concentrate finishing cattle diets on ADG, DMI, G:F, and carcass traits, and to estimate the NE of field pea. In Exp. 1, 118 yearling heifers (417.9 +/- 2.4 kg initial BW) were blocked by initial BW and assigned randomly to 1 of 4 treatments (0, 10, 20, or 30% dry-rolled field pea, DM basis; 4 pens/treatment). In Exp. 2, 143 beef steers (433 +/- 19 kg initial BW) were blocked by BW and assigned randomly to 1 of 4 treatments (0, 10, 20, or 30% dry-rolled field pea, DM basis; 6 pens/treatment). In Exp. 3, 80 beef steers (372.4 +/- 0.4 kg initial BW) were assigned randomly to 1 of 4 treatments (0, 18, 27, or 36% cracked field pea, DM basis; 4 pens/treatment). Field pea replaced a portion of the grain (dry-rolled and high moisture corn, dry-rolled corn, and barley and barley sprouts; Exp. 1, 2, and 3, respectively) and protein supplement. In Exp. 1, field pea inclusion decreased DMI linearly (P = 0.03), whereas ADG and G:F were not affected by treatment (P > or = 0.17); however, dietary NE(g) increased quadratically with increasing field pea level (P = 0.04). Fat thickness responded quadratically (P = 0.008) where heifers fed 20% field pea had greatest fat thickness and 30% field pea inclusion the least. Marbling tended (P < or = 0.09) to respond quadratically as field pea increased. No differences (P > or = 0.17) were observed for HCW, LM area, or KPH. In Exp. 2, DMI, ADG, G:F, dietary NE(g), HCW, marbling, LM area, 12th-rib fat, and USDA yield grade (YG) were unaffected by dietary field pea inclusion (P > or = 0.12). In Exp. 3, marbling score increased linearly (P = 0.05), fat thickness increased quadratically (P = 0.01), and YG tended to increase (P = 0.07) quadratically as field pea increased. Field pea inclusion did not affect (P > or = 0.38) DMI, ADG, G:F, dietary NE(g), HCW, or LM area. These results indicate that field pea can be included successfully into rations at levels up to 36% of DM without negatively affecting growth performance and most carcass characteristics of finishing beef cattle; however, effects on marbling score were variable. These data also indicate the energy content of field peas is similar to cereal grains, such as corn and barley, when included in high-concentrate finishing diets.