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This research study developed milk spectral data-driven approach, called Adaptive Spectral Model for Abnormality Detection - ASMAD, for detection of physiological abnormalities of individual dairy cows. The algorithm is based on the logic that milk spectra of each individual cow is highly animal-specific, which means it could be used as a respective individual marker for identification. When the algorithm fails to recognize the milk spectra as coming from a certain animal, instead of being treated as a mistake, this outcome is accepted as a deviation of the respective individual marker, and a potential indicator of abnormal physiological state. For the purpose of ASMAD development, near infrared spectra of milk of seven dairy cows have been collected daily during 1-year period. The abnormality detection model is built using supervised recognition method Soft Independent Modeling of Class Analogies - SIMCA, and optimized with respect to spectral pre-processing, choice of the wavelength region and size of the time-window when developing the adaptive model. The sensitivity and specificity of ASMAD were dependent on the animal, and in the ranges 40.00-64.29% and 87.23-98.86%, respectively. Considering significant level of day-to-day spectral variation and multitude of physiological and environmental factors influence on milk constituents and spectra, these results represent a significant potential for creating a health-status monitoring and detection of abnormal physiological states in dairy animals. The adaptive modeling based on the time series of spectral data collected from the individual organism utilized in this work for monitoring physiological status and abnormality detection in dairy cows, has a good potential to be used for similar purposes in other animals and humans.

The effect of dietary vitamin K

This study was aimed at two objectives: 1) explore the possibility of near infrared (NIR) spectroscopy to determine the content of common dietary fatty acids (FAs) and fat content in cow's liquid milk for better individual cow's feed management; 2) using aquaphotomics obtain better understanding of interaction between water molecular structure and FAs and gain more insight into their functionality. For these purposes, 252 milk samples were collected from 9 cows during 14 weeks and FAs content measured using gas chromatography as a reference method. Applying aquaphotomics NIR spectral analysis, quantification was attempted using 1300–1850 nm region where both water and FAs absorbance bands are located. The results showed possibility of quantification for 8 common dietary FAs which was more accurate when spectral region was narrowed to 1600–1800 nm. In the external validation, good predictions (R2> 0.75, RPD>1.5), were obtained for caproic and caprylic and acceptable for capric, lauric, myristic, myristoleic, palmitoleic and oleic acid (0.55 1.5). Interpretation of influential variables in regression models revealed contribution of water absorbance bands related to protonated and hydration water, which originate from the water-FAs interaction and are important for their self-organization into assemblies with different morphologies.

A double threshold method to define the appropriate somatic cell count (SCC) levels for mastitis diagnosis based on the near-infrared (NIR) spectra of quarter foremilk of cows and soft independent modelling of class analogy (SIMCA) was proposed and evaluated. The accuracy of the double threshold method, as a new approach, was compared with the current single threshold method for measuring SCC for mastitis diagnosis based on SCC level in milk of individual cows. The accuracy of the SIMCA calibration model is expressed by specificity and sensitivity of disease diagnostics. As a result, 72.15% of specificity and 69.44% of sensitivity were obtained using the single threshold method which yielded its best result at 200,000 cells ml−1 SCC level. Improved accuracy was obtained with double threshold method which had 80.56% of specificity and 77.78% of sensitivity when the healthy and mastitic levels were set at 20,000 cells ml−1 and 200,000 cells ml−1, respectively.

The present study examined the effects of feeding order of grain and protein supplements on ruminal nitrogen (N) loss through the diurnal variation of ruminal ammonia N and urea N in the blood and milk of dairy cows. Three ruminally fistulated cows were used in a 3 × 3 Latin square arrangement of treatments; that is, grain supplement fed at the first feed and then the protein supplement at the second (GS-1st), protein supplement fed first and then the grain supplement (PS-1st), and the grain and protein supplements mixed and divided into equal portions fed at each supplement feeding time (GP-mix). No differences in the lactation parameters were observed among the treatments. In GS-1st treatment, the increase in the concentration of ruminal ammonia N was inhibited after feeding, and the concentration was lower (P

第一胃フィステルを装着した泌乳牛2頭を供試し、噴門付近の固形物層(上部)と腹嚢の液状層(底部)における第一胃液性状を経時的に比較した。pHは両部位とも飼料給与前と給与後1時間にほぼ同一の値を示し、その後急激に低下した後、底部では数時間にわたりが低値で推移した。総揮発性脂肪酸(VFA)濃度は概ね底部が高値で推移した。pH、総VFA濃度ともに上部の大きな変動により、部位間に有意差の生じる時間帯があり、pHと総VFA濃度との間に有意な負の相関が認められた。VFA構成比率とアンモニア態窒素(NH3N)濃度は両部位とも採取時間を通じてほぼ同一の値で推移し、部位間に有意差はなかった。上部から第一胃液を採取する経口カテーテル法の採取時間は、pHが最低値付近で部位間に差がなく、NH3N濃度が最高値に達する飼料給与後1時間が、最も盛んな第一胃発酵状態を把握・評価する上で最適であると考えらた。

Contents The purpose of this research was to develop rapid and cost-effective method for oestrus detection in dairy cows by means of near infrared spectroscopy and aquaphotomics, using raw milk from individual cows. We found that aquaphotomics approach showed consistent specific water spectral pattern of milk at the oestrus periods of the investigated Holstein cows. Characteristic changes were detected especially in foremilk collected at morning milking. They were reflected in calculated aquagrams of milk spectra where distinctive spectral pattern of oestrus showed increased light absorbance of strongly hydrogen-bonded water. Results showed that monitoring of raw milk near infrared spectra provides an opportunity for analysing hormone levels indirectly, through the changes of water spectral pattern caused by complex physiological changes related to fertile periods.

Although not scientifically proven, hoof trimming has been empirically shown to increase milk yields in healthy dairy cows. In this study, we examined the effect of one-time hoof trimming on blood biochemical composition, milk yield, and milk composition in healthy dairy cows. Eleven cows in the mid to late lactation period that were clinically fit and without hoof disease were subjected to hoof trimming, and metabolic profile tests and dairy herd improving tests were performed before and three weeks after the hoof trimming. The metabolic profiles showed changes in albumin, blood urea nitrogen, ammonia, glucose, and beta-hydroxybutyric acid as a result of the hoof trimming. This was indicated by the fact that the cows began to intake more roughage after hoof trimming than prior to hoof trimming, and rumen fermentation became stable. There was no change in milk yield after trimming. However, the milk fat and milk protein compositions were significantly increased after trimming.