Algorithm development for individualized precision feeding of supplemental top dresses to influence feed efficiency of dairy cattle.

Individualized, precision feeding of dairy cattle may contribute to profitable and sustainable dairy production. Feeding strategies targeted at optimizing efficiency of individual cows, rather than groups of animals with similar characteristics, is a logical goal of individualized precision feeding. However, algorithms designed to make feeding recommendations for specific animals are scarce. The objective of this study was to develop and test 2 algorithms designed to improve feed efficiency of individual cows by supplementing total mixed rations (TMR) with varying types and amounts of top-dressed feedstuffs. Twenty-four Holstein dairy cows were assigned to 1 of 3 treatment groups as follows: a control group fed a common TMR ad libitum, a group fed individually according to algorithm 1, and a group fed individually according to algorithm 2. Algorithm 1 used a mixed-model approach with feed efficiency as the response variable and automated measurements of production parameters and top-dress type as dependent variables. Cow was treated as a random effect, and cow by top-dress interactions were included if significant. Algorithm 2 grouped cows based on top-dress response efficiency structure using a principal components and k-means clustering. Both algorithms were trained over a 36-d experimental period immediately before testing, and were updated weekly during the 35-d testing period. Production performance responses for dry matter intake (DMI), milk yield, milk fat percentage and yield, milk protein percentage and yield, and feed efficiency were analyzed using a mixed-effects model with fixed effects for feeding algorithm, top dress, week, and the 2- and 3-way interactions among these variables. Milk protein percentage and feed efficiency were significantly affected by the 3-way interaction of top dress, algorithm, and week, and DMI tended to be affected by this 3-way interaction. Feeding algorithm did not affect milk yield, milk fat yield, or milk protein yield. However, feeding costs were reduced, and hence milk revenue increased on the algorithm-fed cows. The efficacy of feeding algorithms differed by top dress and time, and largely relied on DMI shifts to modulate feed efficiency. The net result, for the cumulative feeding groups, was that cows in the algorithm 1 and 2 groups earned over $0.45 and $0.70 more per head per day in comparison to cows on the TMR control, respectively. This study yielded 2 candidate approaches for efficiency-focused, individualized feeding recommendations. Refinement of algorithm selection, development, and training approaches are needed to maximize production parameters through individualized feeding.

Practical challenges and potential approaches to predicting low-incidence diseases on farm using individual cow data: A clinical mastitis example.

Clinical mastitis (CM) incidence is considerable in terms of cows affected per year, but cases are much less common in terms of detections per cow per milking. From a modeling perspective, where predictions are made every time any cow is milked, low CM incidence per cow day makes training, evaluating, and applying CM prediction models a challenge. The objective of this study was to build models for predicting CM incidence using time-series sensor data and choose models that maximize net return based on a cost matrix. Data collected from 2 university dairy farms, the University of Florida and Virginia Polytechnic Institute and State University, were used to gather representative data, including 110,156 milkings and 333 CM cases. Variables used in the models were milk yield, protein, lactose, fat, electrical conductivity, days in milk, lactation number, and activity as the number of steps, lying time, lying bouts, and lying bout duration. Models that predicted either likelihood of CM caused by gram-negative (GN) or gram-positive (GP) bacteria on each day were derived using extreme gradient boosting with weighting favoring true-positive cases, logistic responses, and log-loss errors. Model accuracies were determined using data randomly held out from the training set on each run. All variables considered were in terms of change (slope) over previous days, including the day CM was visually detected. The GN models had a median sensitivity (Se) of 52.6% and specificity (Sp) of 99.8%, whereas the GP models had a median Se of 37.5% and Sp of 99.9% when tested on the held-out data. In our models optimized to reduce cost from predictions, the Se was much less than Sp, suggesting that CM models might benefit from greater model weighting placed on Sp. Results also highlight the importance of positive predictive value (true positive cases per predicted positive case) along with Sp and Se, as models built on sparse data tend to predict too many false-positive cases. The calculated partial net return of our GN and GP models were -$0.15 and -$0.10 per cow per lactation, respectively, whereas International Organization for Standardization (ISO) standard models with Se of 80% and Sp of 99% would return -$1.32 per cow per lactation. Models chosen that minimized the cost to the farmer differed markedly from models that met ISO guidelines, showing asymmetry in targets between Sp and Se when the disease incidence rate is low. Because of the unique challenges that low-incidence diseases like CM present, we recommend that future CM predictive models consider the economic and practical implications in addition to the traditional model evaluation metrics.

Rumen volatile fatty acid molar proportions, rumen epithelial gene expression, and blood metabolite concentration responses to ruminally degradable starch and fiber supplies.

The objective of this work was to characterize rumen volatile fatty acid (VFA) concentrations, rumen epithelial gene expression, and blood metabolite responses to diets with different starch and fiber sources. Six ruminally cannulated yearling Holstein heifers (body weight = 330 ± 11.3 kg) were arranged in a partially replicated Latin square experiment with 4 treatments consisting of different starch [barley (BAR) or corn (CRN)] and fiber [timothy hay (TH) or beet pulp (BP)] sources. Treatments were arranged as a 2 × 2 factorial. Beet pulp and TH were used to create relative changes in apparent ruminal fiber disappearance, whereas CRN and BAR were used to create relative changes in apparent ruminal starch disappearance. Each period consisted of 3 d of diet adaptation and 15 d of dietary treatment. In situ disappearance of fiber and starch were estimated from bags incubated in the rumen from d 10 to 14. From d 15 to 17, rumen fluid was collected every hour from 0500 to 2300 h. Rumen fluid samples were pooled by animal/period and analyzed for pH and VFA concentrations. On d 18, 60 to 80 papillae were biopsied from the epithelium and preserved for gene expression analysis. On d 18, one blood sample per heifer was collected from the coccygeal vessel. In situ ruminal starch disappearance rate (7.30 to 8.72%/h for BAR vs. 7.61 to 10.5%/h for CRN) and the extent of fiber disappearance (22.2 to 33.4% of DM for TH vs. 34.4 to 38.7% of DM for BP) were affected by starch and fiber source, respectively. Analysis of VFA molar proportions showed a shift from propionate to acetate, and valerate to isovalerate on TH diets compared with BP. Corn diets favored propionate over butyrate in comparison to BAR diets. Corn diets also had higher molar proportions of valerate. Expression of 1 gene (SLC9A3) were increased in BP diets and 2 genes (BDH1 and SLC16A4) tended to be increased in TH diets. Plasma acetate demonstrated a tendency for a starch by fiber interaction with BAR-BP diets having the highest plasma acetate, but other metabolites measured were not significant. These results suggest that TH has the greatest effect on shifts in VFA molar proportions and epithelial transporters, but does not demonstrate shifts in blood metabolite concentrations.

Contributions of dairy products to environmental impacts and nutritional supplies from United States agriculture.

Questions regarding the balance between the contribution to human nutrition and the environmental impact of livestock food products rarely evaluate specific species or how to accomplish the recommended depopulation. The objective of this study was to assess current contributions of the US dairy industry to the supply of nutrients and environmental impact, characterize potential impacts of alternative land use for land previously used for crops for dairy cattle, and evaluate the impacts of these approaches on US dairy herd depopulation. We modeled 3 scenarios to reflect different sets of assumptions for how and why to remove dairy cattle from the US food production system coupled with 4 land-use strategies for the potential newly available land previously cropped for dairy feed. Scenarios also differed in assumptions of how to repurpose land previously used to grow grain for dairy cows. The current system provides sufficient fluid milk to meet the annual energy, protein, and calcium requirements of 71.2, 169, and 254 million people, respectively. Vitamins supplied by dairy products also make up a high proportion of total domestic supplies from foods, with dairy providing 39% of the vitamin A, 54% of the vitamin D, 47% of the riboflavin, 57% of the vitamin B12, and 29% of the choline available for human consumption in the United States. Retiring (maintaining animals without milk harvesting) dairy cattle under their current management resulted in no change in absolute greenhouse gas emissions (GHGE) relative to the current production system. Both depopulation and retirement to pasture resulted in modest reductions (6.8-12.0%) in GHGE relative to the current agricultural system. Most dairy cow removal scenarios reduced availability of essential micronutrients such as α-linolenic acid, Ca, and vitamins A, D, B12, and choline. Those removal scenarios that did not reduce micronutrient availability also did not improve GHGE relative to the current production system. These results suggest that removal of dairy cattle to reduce GHGE without reducing the supply of the most limiting nutrients to the population would be difficult.

Identifying gram-negative and gram-positive clinical mastitis using daily milk component and behavioral sensor data.

Opportunities exist for automated animal health monitoring and early detection of diseases such as mastitis with greater on-farm adoption of precision technologies. Our objective was to evaluate time series changes in individual milk component or behavioral variables for all clinical mastitis (CM) cases (ACM), for CM caused by gram-negative (GN) or gram-positive (GP) pathogens, or CM cases in which no pathogen was isolated (NPI). We developed algorithms using a combination of milk and activity parameters for predicting each of these infection types. Milk and activity data were collated for the 14 d preceding a CM event (n = 170) and for controls (n = 166) matched for breed, parity, and days in milk. Explanatory variables in the univariate and multiple regression models were the slope change in milk (milk yield, conductivity, somatic cell count, lactose percentage, protein percentage, and fat percentage) and activity parameters (steps, lying time, lying bout duration, and number of lying bouts) over 7 d. Slopes were estimated using linear regression between d -7 and -5, d -7 and -4, d -7 and -3, d -7 and -2, and d -7 and -1 relative to CM detection for all parameters. Univariate analyses determined significant slope ranges for explanatory variables against the 4 responses: ACM, GN, GP, and NPI. Next, all slope ranges were offered into the multivariate models for the same 4 responses using 3 baselines: d -10, -7, and -3 relative to CM detection. In the univariate analysis, no explanatory variables were significant indicators of ACM, whereas at least 1 parameter was significant for each of GN, GP, and NPI models. Superior sensitivity (Se) and specificity (Sp) estimates were observed for the best GP (Se = 82%, Sp = 87%) and NPI (Se = 80%, Sp = 94%) multiple regression models compared with the best ACM (Se = 73%, Sp = 75%) and GN (Se = 71%, Sp = 74%) models. Sensitivity for the GN model was greater at the baseline closest to the day of CM detection (d -3), whereas the opposite was observed for the GP and NPI model as Se was maximized at the d -10 baseline. Based on this screening of relationships, milk and activity sensor data could be used in CM detection systems.

Technical note: Methodological and feed factors affecting measurement of protein A, B, and C fractions, degradation rate, and intestinal digestibility of rumen-undegraded protein.

When formulating dairy cow rations, characterization of protein in feeds requires estimation of protein degradation in the rumen and digestion in the intestine. The objective of this work was to evaluate experimental and feed-related factors that affect characterization using in situ, in vitro, or mobile bag techniques, of 0-h washout (A), potentially degradable (B), and undegradable (C) protein fractions, protein degradation rate (Kd), and digestibility of rumen undegradable protein (dRUP). Data sets of 136 studies on A, B, C, and Kd and 113 studies on dRUP were amassed from the literature. Mixed-effect linear models were used to relate these variables to methodological and feed factors while accounting for random differences among studies. Predictions of A, B, and C protein fractions were significantly influenced by crude protein and neutral detergent fiber interactions with bag pore size, incubation time, bag area, and sample-to-bag area ratio. For example, a 20.0% decrease in crude protein of a theoretical legume silage sample would increase A fraction prediction by 20.1%, but 34.7% with bag incubation time -1 standard deviation below the mean. Similarly, reported Kd values were significantly influenced by crude protein interactions with bag area and sample-to-bag area ratio and by neutral detergent fiber interaction with pore size. Feed variables and measurement variables influencing protein digestibility measures suggest that these analytical factors are likely associated with variance among differing methodologies and within unique samples of the same feed. When predicting dRUP, the use of mobile bag method produced significantly different estimates compared with the in vitro 3-step method. The use of mobile bag resulted in an 8.9% (±3.8%) higher estimate of dRUP compared with the in situ technique. In 618 and 977 samples, sample variation to sample mean ratio for acid detergent fiber and pepsin-acid incubation time was 63.0 and 58.0%, respectively. Variation in feedstuff content and lack of standardization of methods used to measure protein disappearance led to a lack of robustness in the measurements commonly employed.

Production and decay of element 114: high cross sections and the new nucleus 277Hs.

The fusion-evaporation reaction 244Pu(48Ca,3-4n){288,289}114 was studied at the new gas-filled recoil separator TASCA. Thirteen correlated decay chains were observed and assigned to the production and decay of {288,289}114. At a compound nucleus excitation energy of E{*}=39.8-43.9 MeV, the 4n evaporation channel cross section was 9.8{-3.1}{+3.9} pb. At E^{*}=36.1-39.5 MeV, that of the 3n evaporation channel was 8.0{-4.5}{+7.4} pb. In one of the 3n evaporation channel decay chains, a previously unobserved α branch in 281Ds was observed (probability to be of random origin from background: 0.1%). This α decay populated the new nucleus 277Hs, which decayed by spontaneous fission after a lifetime of 4.5 ms.

Loss of basal cell keratin 14 reflects increased risk of recurrence in surgically resected sinonasal inverted papilloma.

AIMS: To evaluate selected markers in terms of their possible relation to the development of recurrence in microsurgically resected sinonasal inverted papilloma (SIP) in order to advance understanding of the mechanisms pathogenetically involved, and to identify novel biomarkers for individual risk assessment in SIP. METHODS: Retrospective computerised database analysis and thorough review of medical charts was performed in order to identify all patients with newly diagnosed SIP who underwent microinvasive endonasal surgery at the HELIOS Klinikum Bad Saarow and at the Klinikum Hoyerswerda (Germany) between 1985 and 2005, yielding a total of 73 patients with newly diagnosed SIP. Among these, 22 patients (30.1%) developed recurrence during follow-up. Recurrent SIP were also microsurgically resected. Therefore, archival paraffin-wax-embedded tissues comprising a total of 95 SIP were immunostained for a panel of selected antigens (Ki67/CK5/CK14/E-cadherin/CD56) functionally involved in cellular adhesion structures or in proliferative activity. Adjacent non-papillomatous sinonasal mucosa was available in all cases and served as normal controls. RESULTS: Increased proliferative activity (Ki67) and loss of basal cell keratin 14 (CK14) expression were related to the development of recurrence in microsurgically resected SIP. CONCLUSION: These findings might advance understanding of the pathogenesis behind the development of recurrence in microsurgically resected SIP by focusing on so far neglected alterations of cell-matrix connections at the epithelial-stromal interface in SIP, and might hint at CK14 representing a possible novel biomarker for individual risk assessment in microsurgically resected SIP.

Do different disorders in cell cycle regulation account for different biological behavior of urothelial and sinonasal inverted papillomas?

OBJECTIVE: It was the aim of this study to assess the expression of selected cell cycle regulation genes in urothelial and sinonasal inverted papillomas (IP). METHODS: Archived surgically resected specimens from 18 urothelial and 19 sinonasal IP were studied immunohistochemically for p16, p53, cyclin D1 and Ki67. Staining results were semiquantified and compared between IP and adjacent control mucosa (CM). RESULTS: p53 expression did not differ between sinonasal and urothelial IP. Although there was a trend of higher p53 expression in IP compared with the adjacent CM in sinonasal and urothelial specimens, this trend failed to be statistically significant. p16 expression was significantly higher in urothelial IP and CM in comparison with their sinonasal counterparts, but did not differ significantly between IP and its adjacent CM either in urothelial or sinonasal specimens. There were no significant differences in the mean scores for cyclin D1 or Ki67. CONCLUSION: The changes in p53 expression seen in both types of IP compared with adjacent CM suggest that sinonasal and urothelial IP may share some common ground in terms of their evolution. Although p16 appears not to be directly involved in the development of sinonasal or urothelial IP, the differing recurrence patterns of sinonasal versus urothelial IP may be attributable in part to different p16 expression.