Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Milking Diatoms for Sustainable Energy: Biochemical Engineering versus Gasoline-Secreting Diatom Solar Panels

In the face of increasing CO2 emissions from conventional energy (gasoline), and the anticipated scarcity of Crude oil, a worldwide effort is underway for cost-effective renewable alternative energy sources. Here, we review a simple line of reasoning: (a) geologists claim that Much crude oil comes from diatoms; (b) diatoms do indeed make oil; (c) agriculturists Claim that diatoms could make 10-200 times as much oil per hectare as oil seeds; and (d) therefore, sustainable energy could be made from diatoms. In this communication, we propose ways of harvesting oil from diatoms, using biochemical engineering and also a new solar panel approach that utilizes genomically modifiable aspects of diatom biology, offering the prospect of ``milking'' diatoms for Sustainable energy by altering them to actively secrete oil products. Secretion by and milking of diatoms may provide a way around the puzzle of how to make algae that both grow quickly and have a very high oil content.

Inspection of teats by colour image analysis for automatic milking systems

C.R. Bull, N.J.B. McFarlane, R. Zwiggelaar, C.J. Allen and T.T. Mottram, 'Inspection of teats by colour image analysis for automatic milking systems', Computers and Electronics in Agriculture 15 (1), 15-26 (1996)

Behavioural and physiological responses of heifer calves to acute stressors: long-term consistency and relationship with adult reactivity to milking

The present study investigated the long-term consistency of individual differences in dairy cattles’ responses in tests of behavioural and hypothalamo–pituitary–adrenocortical (HPA) axis reactivity, as well as the relationship between responsiveness in behavioural tests and the reaction to first milking. Two cohorts of heifer calves, Cohorts 1 (N = 25) and 2 (N = 16), respectively, were examined longitudinally from the rearing period until adulthood. Cohort 1 heifers were subjected to open field (OF), novel object (NO), restraint, and response to a human tests at 7 months of age, and were again observed in an OF test during first pregnancy between 22 and 24 months of age. Subsequently, inhibition of milk ejection and stepping and kicking behaviours were recorded in Cohort 1 heifers during their first machine milking. Cohort 2 heifers were individually subjected to OF and NO tests as well as two HPA axis reactivity tests (determining ACTH and/or cortisol response profiles after administration of exogenous CRH and ACTH, respectively) at 6 months of age and during first lactation at approximately 29 months of age. Principal component analysis (PCA) was used to condense correlated response measures (to behavioural tests and to milking) within ages into independent dimensions underlying heifers’ reactivity. Heifers demonstrated consistent individual differences in locomotion and vocalisation during an OF test from rearing to first pregnancy (Cohort 1) or first lactation (Cohort 2). Individual differences in struggling in a restraint test at 7 months of age reliably predicted those in OF locomotion during first pregnancy in Cohort 1 heifers. Cohort 2 animals with high cortisol responses to OF and NO tests and high avoidance of the novel object at 6 months of age also exhibited enhanced cortisol responses to OF and NO tests at 29 months of age. Measures of HPA axis reactivity, locomotion, vocalisation and adrenocortical and behavioural responses to novelty were largely uncorrelated, supporting the idea that stress responsiveness in dairy cows is mediated by multiple independent underlying traits. Inhibition of milk ejection and stepping and kicking behaviours during first machine milking were not related to earlier struggling during restraint, locomotor responses to OF and NO tests, or the behavioural interaction with a novel object. Heifers with high rates of OF and NO vocalisation and short latencies to first contact with the human at 7 months of age exhibited better milk ejection during first machine milking. This suggests that low underlying sociality might be implicated in the inhibition of milk ejection at the beginning of lactation in heifers.

Effect of feeding intensity and milking system on nutritionally relevant milk components in dairy farming systems in the North East of England

There is increasing concern that the intensification of dairy production reduces the concentrations of nutritionally desirable compounds in milk. This study therefore compared important quality parameters (protein and fatty acid profiles; α-tocopherol and carotenoid concentrations) in milk from four dairy systems with contrasting production intensities (in terms of feeding regimens and milking systems). The concentrations of several nutritionally desirable compounds (β-lactoglobulin, omega-3 fatty acids, omega-3/omega-6 ratio, conjugated linoleic acid c9t11, and/or carotenoids) decreased with increasing feeding intensity (organic outdoor ≥ conventional outdoor ≥ conventional indoors). Milking system intensification (use of robotic milking parlors) had a more limited effect on milk composition, but increased mastitis incidence. Multivariate analyses indicated that differences in milk quality were mainly linked to contrasting feeding regimens and that milking system and breed choice also contributed to differences in milk composition between production systems.

Alternative body sites for heat stress measurement in milking cows under tropical conditions and their relationship to the thermal discomfort of the animals

This study was conducted to determine the relationship among temperatures measured at different anatomical sites of the animal body and their daily pattern as indicative of the thermal stress in lactating dairy cows under tropical conditions. Environmental dry bulb (DBT) and black globe (BGT) temperatures and relative humidity (RH) were recorded. Rectal temperature (RT), respiratory frequency (RF), body surface (BST), internal base of tail (TT), vulva (VT) and auricular temperatures (AT) were collected, from 37 Black and White Holstein cows at 0700, 1300 and 1800 hours. RT showed a moderately and positive correlations with all body temperatures, ranging from 0.59 with TT to 0.64 with BST. Correlations among AT, VT and TT with RF were very similar (from 0.63 to 0.64) and were greater than those observed for RF with RT (0.55) or with BST (0.54). RF and RT were positively correlated to TT (0.63 and 0.59, respectively), AT (r = 0.63 for both) and VT (r = 0.64 and 0.63, respectively). Positive and very high correlations were observed among AT, VT and TT (from 0.94 to 0.97) indicating good association of temperatures measured in these anatomical sites. Correlations of BST with AT and VT were positive and very similar (0.71 and 0.72, respectively) and lower with TT (0.66). The AT, TT, VT and BST presented similar patterns and follow the variations of DBT through the day. Temperatures measured at different anatomical sites of the animal body have the potential to be used as indicative of the thermal stress in lactating dairy cows.

Hormone release and behavior during suckling and milking in Gir, Gir x Holstein, and Holstein cows

There are several different milking management systems in Latin America, because Gir cattle are reputed to be easily stressed and not well adapted to machine-milking. This paper, therefore, provides an overview of hormone release and behavior during suckling and milking in Gir cows and their crossbred offspring. Several experiments were performed to study oxytocin release during exclusive suckling or exclusive hand- and machine-milking, oxytocin, and prolactin release during a mixed suckling-milking system and oxytocin release after weaning. Cortisol concentrations and behavior were also examined. Concentration of oxytocin, released during suckling, and both types of milking were high, but the maximum concentration measured during suckling was significantly greater than that observed during exclusive milking. In the mixed suckling-milking system, the greatest oxytocin and prolactin releases were measured during suckling. Cortisol concentrations measured before, during, and after milking demonstrated that Gir x Holstein and Holstein cows were not stressed. On the other hand, although Gir had greater concentrations of cortisol, the percentage of residual milk for Gir cows was less than for dairy cows exposed to different stressful situations. In general, Gir cows and their crossbred offspring adapted to machine-milking, although these breeds can react negatively to milkers. Gir, Gir x Holstein, and Holstein cows all had similar cortisol levels during and after milking.

Milking their health for all its worth? Improving the health of farming families through facilitated learning

The Victorian Dairy Industry has an annual turnover of $5,125 million and produces over two thirds of the nation’s fresh milk and cheese, but what do we know about the health of the dairy men and women who drive this industry, and how can health professionals and industry assist them to focus on the health of the people involved in the farm business? The Sustainable Dairy Farm Families (SDFF) program undertook research exploring the health, wellbeing and safety of Victorian Dairy farming families across eleven locations. The program involved physical assessments, reviewed health conditions and health behaviours and provided education relating to common health conditions. Risk factors were identified for chronic and lifestyle diseases such as cardiovascular disease, diabetes and cancer. Participants were referred to health professionals as required and reassessed over three years concluding in 2007. The program has influenced participants’ decisions about their health and improved some clinical indicators. A cross-sectoral intervention appears to be an effective method for improving health, wellbeing and safety in farm men and women and their families.

Fluorescent amplified fragment length polymorphism genotyping of human and animal Staphylococcus aureus isolates from dairy farms with manual milking

Fluorescence amplified fragment length polymorphism (fAFLP) was used to assess the genetic relatedness of 40 Staphylococcus aureus strains isolated from human and animal skin samples in seven dairy farms with manual milking. S. aureus was isolated from 11 out of 30 (36%) human skin samples and from 29 out of 100 (29%) teat skin samples from apparently healthy cows. Genomic DNA from each isolate was double-digested with EcoRI and MseI and complementary oligonucleotide adaptors were ligated to the restriction fragments. Pre-selective and selective, amplification reactions were performed, the amplified fragments were separated by electrophoresis in an ABI377 sequencer and analysed using GeneScan 3.1 and Genotyper 2.5. Three single isolates (a-c), a predominant cluster with 35 isolates (d) and another cluster with two isolates (e) were identified. Both clusters d and e included human and animal isolates genetically related, because the profiles had 90-100% homology. Since no cluster was comprised uniquely of human or animal isolates and given the close genetic relatedness among human and animal samples in the farms, the present findings support the. hypothesis that dairy workers can spread S. aureus through manual milking. (C) 2005 Elsevier B.V. All rights reserved.

Influence of the season of year, stage of lactation and milking time on the chloride content in bovine milk

From January to October 1995, chloride content determinations were accomplished in 2,218 samples of milk collected from 67 quarters of 17 lactating cows, in initial, middle and final stages of lactation, in the morning and afternoon milking. The highest means of chloride contents were observed among the milk samples collected in the final stage of lactation (0,203 gC1/100ml), in the summer (0,212 gC1/100ml) and in the morning milking (0,189 g C1/100ml). The differences observed between the chloride contents in the samples obtained in the different stages of lactation and the seasons of the year were statistically significant (P<0.0001). The gratest occornce of chloride at rates superior to 0.22 gC1100ml was observed in the final stge of lactation (31.4%), summer (44.2%) and after the morning milking (27.8%). These results evidentiate the influence of physiological and external factors (stage of lactation and season of the year) on the concentration of chloride of milk.

Analysis of the electrical conductivity in milking fractions as a mean for detecting and characterizing mastitis in goats

The aim of the work was to study the effect of milking fraction on electrical conductivity of milk (EC) to improve its use in dairy goat mastitis detection using automatic EC measurements during milking. The experiment was carried out on a group of 84 Murciano-Granadina goats (28 primiparous and 56 multiparous). Goats were in the fourth month of lactation. A linear mixed model was used to analyse the relationship between EC or somatic cell count (SCC) of gland milk and parity, mammary gland health status, analysed fraction (first 100 mL=F-1; machine milk=F-2; and stripping milk=F-3) and their first order interactions. Additionally, the mastitis detection characteristics (sensitivity, specificity, positive predictive value and negative predictive value) of SCC and EC were studied at different thresholds.All factors considered were significant for EC and SCC. EC decreased significantly as milking progressed (from F-1 to F-3) in both healthy and infected glands. EC was not significantly different between healthy and infected glands in F-1 and F-2 fractions, but EC of healthy glands (5.01 mS/cm) was significantly lower than in infected glands (5.03 mS/cm) at F-3.Mastitis detection characteristics of EC did not differ amongst studied fractions. The small significant difference of EC between healthy and infected glands obtained in F-3 fraction did not yield better sensitivity results compared to F-1 and F-2. The best EC mastitis detection characteristics were obtained at 5.20 mS/cm threshold (sensitivity of 70% and specificity of 50%). The best SCC mastitis detection characteristics were obtained at 300,000 cells/mL threshold and F-3 fraction (sensitivity of 85% and specificity of 65%).It was concluded that mastitis detection characteristics of EC were similar in the three milking fractions analysed, being slightly better for SCC in F-3 fraction. As shown in previous studies, there are no factors other than the mammary gland health status that affect milk EC and should be considered in the algorithms for mastitis detection to improve the results. (C) 2012 Elsevier B.V. All rights reserved.