This paper examines different hedging techniques for options written on non-exchange-traded agricultural commodities using the futures markets to hedge, and evaluates the performance using statistical measures. The paper applies the hedging methods to real agricultural commodity data from the USDA. In these markets there are a number of commercial risks, such as weather and supply-chain disruption, which need to be managed by both producers and consumers. Typically, there is no perfectly correlated hedging instrument available for the product being traded, and as such there is basis risk present when trying to find a hedging solution. This highlights the need for empirical studies which address the problem of how to hedge in this environment. We evaluate static and dynamic hedging strategies for European options written on livestock indices using live cattle futures to hedge. Hedging methods based on delta, minimum variance, value-at-risk (VaR), and conditional VaR (C-VaR) are tested. Hedging performance is examined by hedging effectiveness (i.e calculating risk reduction versus an unhedged portfolio) and distribution statistics. Overall, we found that the static minimum-variance technique provided the best hedging performance in terms of risk reduction versus the unhedged portfolio.