Range cattle in semi-arid regions are commonly limited by lack of nitrogen and other nutrients from grazing low-quality forage, with managers needing to monitor diet quality to address nutrient limitations. Near-infrared spectroscopy of faecal samples (FNIRS) is an accurate method used to determine diet quality in grazing animals. When combined with a nutritional balance software such as the Nutritional Balance Analyser (NUTBAL), FNIRS can monitor nutritional status and estimate weight change. We aimed to test the ability of NUTBAL to predict animal performance as represented by body condition score (BCS) in cattle grazing on a semi-desert rangeland. BCS and faecal samples were collected from a Red Angus herd (n = 82) at the Santa Rita Ranch (June 2016–July 2017). Standing biomass and botanical composition were measured before each grazing period, and relative utilisation was measured following each grazing period. During the midpoint of grazing in each pasture, 30 BCS and a faecal composite of 15 samples were collected. Faecal derived diet quality varied between a maximum of 10.75% crude protein (CP) and 61.25% digestible organic matter (DOM) in early August 2016, to a minimum value of 4.22% CP and 57.68% DOM in January 2017. Three NUTBAL evaluations were conducted to determine the likelihood of accurately predicting animal performance: one with typical user defined inputs; one with improved environment and herd descriptive inputs; and one with these improvements plus the use of metabolisable protein in the model. This third evaluation confirmed the ability of FNIRS:NUTBAL to predict future BCS within 0.5 BCS more than 75% of the time. With this information, cattle managers in semi-arid regions can better address animal performance needs and nutrient deficiencies.

半干旱地区的牧场牛通常因放牧低质量草料而缺乏氮和其他营养物质而受到限制，管理人员需要监测饮食质量以解决营养限制问题。粪便样本的近红外光谱 (FNIRS) 是一种准确的方法，用于确定放牧动物的饮食质量。当与营养平衡分析仪 (NUTBAL) 等营养平衡软件结合使用时，FNIRS 可以监测营养状况并估计体重变化。我们旨在测试 NUTBAL 预测动物表现的能力，如在半沙漠牧场放牧的牛的身体状况评分 (BCS) 所代表。BCS 和粪便样本来自红安格斯牛群 ( n = 82）在圣丽塔牧场（2016 年 6 月至 2017 年 7 月）。在每个放牧期之前测量直立生物量和植物成分，并在每个放牧期之后测量相对利用率。在每个牧场放牧的中点，收集了 30 个 BCS 和 15 个样本的粪便复合物。2016 年 8 月上旬，粪便衍生的饮食质量在最高 10.75% 粗蛋白 (CP) 和 61.25% 可消化有机质 (DOM) 之间变化，到 2017 年 1 月最低值为 4.22% CP 和 57.68% DOM。三项 NUTBAL 评估是用于确定准确预测动物性能的可能性：一种具有典型用户定义输入的；一种具有改善的环境和畜群描述性输入；一种具有这些改进以及在模型中使用可代谢蛋白质。第三次评估证实了 FNIRS:NUTBAL 在 0.5 BCS 内预测未来 BCS 的能力超过 75%。有了这些信息，半干旱地区的牛管理人员可以更好地解决动物性能需求和营养缺乏问题。