Kishore Joseph

The research evaluated how location, crop year, relative maturity, and nutrient composition affect modeled soybean meal (SBM) values and the relative livestock feed value (LFV) scores of soybean varieties grown in southern Illinois. The study also assessed the impact of non-ruminant-specific LFV scores and modeled SBM composition in ruminant diets on requirements for other feed ingredients, such as feed corn. Among 47 soybean varieties collected from two southern Illinois locations over two growing seasons, modeled SBM values ranged from US$340.0 to US$370.0 per ton, while relative LFV scores varied from 1.3 to 9.9. SBM inclusion in the modeled backgrounding beef cattle diets ranged from 331.8 kg to 367.1 kg/ton, and feed corn inclusion ranged from 82.4 kg to 117.6 kg/ton. The feed formulation model showed a positive association for soybean seed protein with methane (CH₄) emissions (r = 0.94 for CH₄ as % GE, r = 0.98 for CH₄ in mol/d, and r = 0.89 for CH₄ in Mcal/d), though the relative range in predicted CH₄ emissions from the feed formulations was only 1.8%, suggesting minimal impact of soybean varieties and limited practical significance. The feed formulation model showed a positive association between corn demand and dietary CP concentrations (R² = 0.85). Meal from superior soybean seeds is predicted to be required at lower inclusions in model ruminant diets to achieve a net positive metabolizable protein balance.

CONTEXT: Environmental assessments of food systems often assume stable crop nutritional quality, yet variation in feed composition can substantially affect livestock nutrient utilization, emissions, and farm economics. Because soybean seed composition is influenced by both germplasm and environmental conditions, it is important to evaluate how resulting differences in soybean meal feed value affect livestock feed formulations and associated emissions.OBJECTIVE: To evaluate how variation in feed value of modeled SBM affects livestock feed formulation, SBM and feed corn demand, and associated livestock emissions.METHODS: Soybean seed samples (n = 47) collected from two locations in southern Illinois over two crop years were analyzed for seed crude protein (CP) and amino acid concentrations. Modeled SBM feed value and the inclusion rates of SBM and feed corn were estimated using least-cost feed formulation for swine and poultry diets. The effects of modeled SBM composition on livestock greenhouse gas (GHG, kg CO2e/ton of diet) and nitrogen (N, kg N/ton of diet) emissions were also evaluated.RESULTS AND CONCLUSION: High CP, high feed value SBM required lower inclusion in swine and poultry diets, increasing corn demand and reducing GHG and N emissions. Diets containing 50% CP SBM reduced GHG emissions by 4.6% in swine lactation and 4.5% in broiler grower diets compared with 44% CP SBM. In backgrounding cattle, higher SBM feed value was associated with increased CH₄ production metrics (R² = 0.32–0.48). Overall, high feed value SBM benefits swine and poultry diets, whereas low feed value SBM can be effectively utilized in beef and dairy cattle diets.SIGNIFICANCE: Strategic marketing and utilization of SBM with varying feed value can maximize feed efficiency and minimize livestock emissions, supporting sustainable livestock production.

We examined the limitations of observed course DFWI rates (% of D and F grades, withdrawals, and incompletes) as evaluation metrics, which obscure student characteristics, course design, instruction, structure, and latent factors, posing challenges in identifying courses that need improvement. An artificial neural network (ANN) was trained using student data to model risk, accounting for variations in student characteristics. The model’s predictions on test data were averaged at the course level, producing expected DFWI rates based on student composition. Courses with high observed DFWI rates and large deviations between observed and predicted DFWI rates (the GAP) were ranked and prioritized for review, as they may reflect aspects of course design, structure, or instructional practices warranting further qualitative evaluation. Our predictions are non-causal, and modeling calibration varies across subgroups; therefore, the original GAP rankings, robust to a post-hoc calibration check, are presented as risk-adjusted indicators for prioritizing courses for further review rather than as definitive causal measures of course quality. Rankings based on observed DFWI rates differ substantially from risk-adjusted GAP rankings, indicating that relying on observed DFWI rates alone may misidentify high-risk courses. Our methodology can assist educators and administrators in making fair resource allocation decisions and improving student outcomes.

Hedonic analysis of Wisconsin Beef Improvement Association Bull Sale and Development Program data revealed buyer preferences for calving ease, growth, production weight, and carcass merit traits. Attributes like calving ease direct Expected Progeny Differences (EPD), average daily gain, birth to yearling gain EPD, and rib-eye area consistently ranked higher and significantly influenced the bull’s sale price. Further analysis using a 2-Class Finite Mixture Model indicated distinct groups of buyers in the region who prioritized measured bull attributes and others who did not, confirming heterogeneity in buyer preferences.

This article investigates market reactions to major United States Department of Agriculture announcements during non-trading and trading hours in the soybean futures market using microstructure data. Following report release, volume increases and remains elevated for up to 15 to 20 minutes. The volume spikes for the non-trading releases relative to the trading releases, but are identical after the first reaction. Report releases during non-trading hours cause a large spike in volatility at the onset of trading which subsides quickly. In contrast, releases during trading hours result in a smaller volatility spike, which extends for 5–6 min at a higher magnitude. Adjusting volatility by normal trading volatility indicates that volatility in trading hour release is higher in both immediate response and persistence. Return correlations provide little evidence to support systematic under- or overreaction in prices regardless of when the report is released reflecting the efficiency of the market.

We investigate storage in the presence of backwardation and the existence of the Working curve for Chicago Board of Trade corn, soybeans, and wheat markets and the Kansas City Board of Trade wheat market using 1990–2010 data. Two spread measures—the futures‐spot and futures‐futures—are matched with deliverable stocks on the first Friday of delivery. To account for grade and location aggregation issues, the futures‐spot spreads are measured using the lowest spot bid and highest futures price. Storage in the presence of backwardation is pervasive both in terms of the percentage of observations and the magnitude of the stockholdings. The Working curve emerges most clearly in KCBT wheat and soybeans. Convenience yield is also supported by the negligible holdings of delivery shipping certificates in backwardations. Overall, the results show that the Working curve does indeed still work today. When evaluating policy proposals to deal with heightened price volatility in agricultural markets it is important that models incorporate this well‐established relationship.