Immunologisches Reaktionsvermögen als Indikator für Belastungen bei der Milchkuh

Mit ansteigenden Jahresmilchleistungen werden die Kühe einer hohen metabolischen Belastung ausgesetzt, die bei einer suboptimalen Gestaltung der Lebensbedingungen mit einer Erhöhung der Inzidenzrate von Faktorenkrankheiten einhergehen kann. Im Vordergrund der Untersuchungen stand die Frage, inwieweit metabolische Belastungszustände von Milchkühen in der Phase des Puerperiums und in Abhängigkeit von der Milchleistung sowie Belastungen durch eine klinische Erkrankung zu Beginn der Laktation mit Hilfe von Parametern der immunologischen Abwehr und der Reaktion des Immunsystems auf eine Challenge dargestellt werden können. In die Untersuchung wurden insgesamt 68 klinisch gesunde sowie 20 klinisch erkrankte Milchkühe der Rasse Holstein Friesian einbezogen. Die Untersuchungen erfolgten in den Zeiträumen 10-21 Tage sowie 14-15 Wochen nach der Kalbung. Dazu wurden an jeweils drei Untersuchungstagen (Tag 0, 2, 7) Blutproben aus der Vena jugularis entnommen. Zur Stimulierung des unspezifischen Immunsystems wurde in beiden Versuchszeiträumen an den Untersuchungstagen 0 und 2 der Paramunitätsinducer Zylexis® appliziert. Ferner wurde den Kühen zu Beginn der Laktation der Tollwutimpfstoff Rabisin® verabreicht. Für die Auswertung wurden die untersuchten Milchkühe in Gruppen unterteilt. Die klinisch gesunden Kühe wurden anhand der nach Fett und Eiweiß korrigierten 305-Tage-Leistung in die Gruppe M = mittleres Leistungsniveau (Milchmengenleistung 6.500-8.990 kg) und die Gruppe H = hohes Leistungsniveau (Milchmengenleistung 9.000-12.500 kg) aufgeteilt. Die klinisch erkrankten Kühe wurden in der Gruppe K zusammengefasst. Zur Beurteilung der Immunabwehr wurden die Parameter Phagozytoseaktivität der isolierten Neutrophilen Granulozyten, die Vollblutbakterizidie, die Lymphozytenproliferation mit den Mitogenen ConA, PHA und PWM sowie die spezifische Antikörperbildung gegen Tollwut untersucht. Anhand der Parameter Phagozytoseaktivität, Vollblutbakterizidie und Lymphozytenproliferation wurde zusätzlich die Reaktion auf die Challenge mit dem Paramunitätsinducer Zylexis® überprüft. Zur Erfassung der metabolischen Belastungszustände wurden verschiedene Stoffwechselparameter und hämatologische Parameter erfasst. Zu Beginn der Laktation konnten bei den Kühen in der mittleren und hohen Leistungsgruppe signifikant höhere Konzentrationen an ß-Hydroxybuttersäure und Freien Fettsäuren im Vergleich zu der Laktationsmitte festgestellt werden. Die Kühe mit einem hohen Leistungsniveau zeigten darüber hinaus eine signifikant höhere Bilirubinkonzentration am Laktationsanfang gegenüber der Laktationsmitte. Die mittlere Konzentration der freien Fettsäuren lag bei den Kühen in beiden Leistungsgruppen oberhalb des Referenzbereiches und wies auf eine negative Energiebilanz zu Laktationsbeginn hin. Die mittleren Konzentrationen bzw. Enzymaktivitäten der Parameter Cholesterol, Harnstoff, AST, GLDH, γ-GT, Gesamtprotein, Kalzium und Phosphor wiesen in der Laktationsmitte signifikant höhere Werte als am Laktationsanfang auf. Dabei lagen die mittleren Enzymaktivitäten von AST und GLDH sowie die Konzentrationen von Harnstoff und Gesamtprotein in der Laktationsmitte oberhalb des Referenzbereiches. Die untersuchten Stoffwechselparameter wurden durch die Challenge mit einem Paramunitätsinducer nicht signifikant beeinflusst. Hinsichtlich der Immunparameter zeigten die Milchkühe mit einem mittleren Leistungsniveau in Abhängigkeit vom Laktationszeitpunkt zu Beginn der Laktation eine signifikant höhere Phagozytoseaktivität gegenüber der Laktationsmitte (p < 0,05). Die Gruppe mit einem hohen Leistungsniveau wies dagegen keine signifikanten Unterschiede in der Phagozytoseaktivität zwischen den beiden Untersuchungszeiträumen auf. Bei den Immunparametern Vollblutbakterizidie und Lymphozytenproliferation konnten bei den Kühen beider Gruppen keine signifikanten Unterschiede in Abhängigkeit vom Laktationszeitpunkt festgestellt werden. Im Hinblick auf die Milchleistung wiesen die Kühe in den beiden Leistungsgruppen am Untersuchungstag 0 weder zu Beginn noch in der Mitte der Laktation signifikante Unterschiede bezüglich der untersuchten Immunparameter auf. Nach der Challenge durch den Paramunitätsinducer reagierten einzig die Kühe mit einer mittleren Leistung zu Beginn der Laktation auf die Challenge mit einer signifikanten Reduzierung der mittleren Phagozytoseaktivität von Tag 0 zu Tag 2 (p < 0,05). Bei den weiteren untersuchten Immunparametern konnten weder bei den Kühen mit einer mittleren noch mit einer hohen Leistung eine signifikante Reaktion auf die Challenge nachgewiesen werden. Die klinisch erkrankten Kühe zeigten im Vergleich zu den klinisch gesunden Kühen keine unterschiedlichen Konzentrationen bzw. Aktivitäten der untersuchten Stoffwechselparameter. Auch konnten anhand der immunologischen Parameter und der Reaktion auf die Challenge keine Unterschiede zwischen den klinisch gesunden Kühen festgestellt werden. Die in der vorliegenden Untersuchung geprüften metabolischen Belastungen konnten weder anhand der Immunparameter noch durch die Reaktion der Immunparameter auf eine Challenge dargestellt werden. Es wird geschlussfolgert, dass das immunologische Reaktionsvermögen nicht geeignet ist, um als Indikator für Belastungszustände bei der Milchkuh herangezogen zu werden.

Improving food and nutritional security of small and marginal coconut growers through diversification of crops and enterprises

This paper presents the impact of integrating interventions like nutrition gardening, livestock rearing, product diversification and allied income generation activities in small and marginal coconut homesteads along with nutrition education in improving the food and nutritional security as well as the income of the family members. The activities were carried out through registered Community Based Organizations (CBOs) in three locations in Kerala, India during 2005-2008. Data was collected before and after the project periods through interviews using a pre-tested questionnaire containing statements indicating the adequacy, quality and diversity of food materials. Fifty respondents each were randomly selected from the three communities, thereby resulting in a total sample size of 150. The data was analysed using SPSS by adopting statistical tools like frequency, average, percentage analysis, t – test and regression. Participatory planning and implementation of diverse interventions notably intercropping and off-farm activities along with nutrition education brought out significant improvements in the food and nutritional security, in terms of frequency and quantity of consumption as well as diet diversity. At the end of the project, 96%of the members became completely food secure and 72% nutritionally secure. The overall consumption of fruits, vegetables and milk by both children and adults and egg by children recorded increase over the project period. Consumption of fish was more than the Recommended Dietary Intake (RDI) level during pre and post project periods. Project interventions like nutrition gardening could bring in surplus consumption of vegetables (35%) and fruits (10%) than RDI. In spite of the increased consumption of green leafy vegetables and milk and milk products over the project period, the levels of consumption were still below the RDI levels. CBO-wise analysis of the consumption patterns revealed the need for location-specific interventions matching to the needs and preferences of the communities.

Double burden malnutrition of preschool children and its association with brain development and milk consumption

Protecting the quality of children growth and development becomes a supreme qualification for the betterment of a nation. Double burden child malnutrition is emerging worldwide which might have a strong influence to the quality of child brain development and could not be paid-off on later life. Milk places a notable portion during the infancy and childhood. Thus, the deep insight on milk consumption pattern might explain the phenomenon of double burden child malnutrition correlated to the cognitive impairments. Objective: Current study is intended (1) to examine the current face of Indonesian double burden child malnutrition: a case study in Bogor, West Java, Indonesia, (2) to investigate the association of this phenomenon with child brain development, and (3) to examine the contribution of socioeconomic status and milk consumption on this phenomenon so that able to formulate some possible solutions to encounter this problem. Design: A cross-sectional study using a structured coded questionnaire was conducted among 387 children age 5-6 years old and their parents from 8 areas in Bogor, West-Java, Indonesia on November 2012 to December 2013, to record some socioeconomic status, anthropometric measurements, and history of breast feeding. Diet and probability of milk intake was assessed by two 24 h dietary recalls and food frequency questionnaire (FFQ). Usual daily milk intake was calculated using Multiple Source Method (MSM). Some brain development indicators (IQ, EQ, learning, and memory ability) using Projective Multi-phase Orientation method was also executed to learn the correlation between double burden child malnutrition and some brain development indicator. Results and conclusions: A small picture of child double burden malnutrition is shown in Bogor, West Java, Indonesia, where prevalence of Severe Acute Malnutrition (SAM) is 27.1%, Moderate Acute Malnutrition (MAM) is 24.9%, and overnutrition is 7.7%. This phenomenon proves to impair the child brain development. The malnourished children, both under- and over- nourished children have significantly (P-value<0.05) lower memory ability compared to the normal children (memory score, N; SAM = 45.2, 60; MAM = 48.5, 61; overweight = 48.4, 43; obesity = 47.9, 60; normal = 52.4, 163). The plausible reasons behind these evidences are the lack of nutrient intake during the sprout growth period on undernourished children or increasing adiposity on overnourished children might influence the growth of hippocampus area which responsible to the memory ability. Either undernutrition or overnutrition, the preventive action on this problem is preferable to avoid ongoing cognitive performance loss of the next generation. Some possible solutions for this phenomenon are promoting breast feeding initiation and exclusive breast feeding practices for infants, supporting the consumption of a normal portion of milk (250 to 500 ml per day) for children, and breaking the chain of poverty by socioeconomic improvement. And, the national food security becomes the fundamental point for the betterment of the next. In the global context, the causes of under- and over- nutrition have to be opposed through integrated and systemic approaches for a better quality of the next generation of human beings.

A pilot investigation of the relationship between climate variability and milk compounds under the bootstrap technique

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data.

Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow’s Milk

This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new), and respiratory rate predictor RRP) with three main components of cow’s milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p-value < 0.001 and R2 (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.

A Survey of the Relationship between Climatic Heat Stress Indices and Fundamental Milk Components Considering Uncertainty

The main purpose of this study is to assess the relationship between four bioclimatic indices for cattle (environmental stress, heat load, modified heat load, and respiratory rate predictor indices) and three main milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when the cows use the natural pasture. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty information in the confidence intervals. The main results identify an interesting relationship between the milk compounds and climate indices under all climate conditions. During spring, there are reasonably high correlations between the fat and protein concentrations vs. the climate indices, whereas there are insignificant dependencies between the milk yield and climate indices. During summer, the correlation between the fat and protein concentrations with the climate indices decreased in comparison with the spring results, whereas the correlation for the milk yield increased. This methodology is suggested for studies investigating the impacts of climate variability/change on food and agriculture using short term data considering uncertainty.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.