122 resultados para farm production

em Helda - Digital Repository of University of Helsinki


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Tämän tutkimuksen tavoitteena oli selvittää tilalla määritetyn hyvinvoinnin yhteyttä emakoiden tuotantotuloksiin. Hyvinvointia arvioitiin suomalaisen hyvinvointi-indeksin, A-indeksi, avulla. Tuotantotuloksina käytettiin kahta erilaista tuotosaineistoa, jotka molemmat pohjautuivat kansalliseen tuotosseuranta aineistoon. Hyvinvointimääritykset tehtiin 30 porsastuotantosikalassa maaliskuun 2007 aikana. A-indeksi koostuu kuudesta kategoriasta ’liikkumismahdollisuudet’, ’alustan ominaisuudet’, ’sosiaaliset kontaktit’, ’valo, ilma ja melu’, ’ruokinta ja veden saanti’ sekä ’eläinten terveys ja hoidon taso’. Jokaisessa kategoriassa on 3-10 pääosin ympäristöperäistä muuttujaa, jotka vaihtelevat osastoittain. Maksimipistemäärä osastolle on 100. Hyvinvointimittaukset tehtiin porsitus-, tiineytys- ja joutilasosastoilla. Erillisten tiineytysosastojen pienen lukumäärän takia (n=7) tilakohtaiset tiineytys- ja joutilasosastopisteet yhdistettiin ja keskiarvoja käytettiin analyyseissä. Yhteyksiä tuotokseen tutkittiin kahden eri aineiston avulla 1) Tilaraportti aineisto (n=29) muodostuu muokkaamattomista tila- ja tuotostuloksista tilavierailua edeltävän vuoden ajalta, 2) POTSIaineisto (n=30) muodostuu POTSI-ohjelmalla (MTT) muokatusta tuotantoaineistosta, joka sisältää managementtiryhmän (tila, vuosi, vuodenaika) vaikutuksen ensikoiden ja emakoiden pahnuekohtaiseen tuotokseen. Yhteyksiä analysointiin korrelaatio- ja regressioanalyysien avulla. Vaikka osallistuminen tutkimukseen oli vapaaehtoista, molempien tuotantoaineistojen perusteella tutkimustilat edustavat keskituottoista suomalaista sikatilaa. A-indeksin kokonaispisteet vaihtelivat välillä 37,5–64,0 porsitusosastolla ja 39,5–83,5 joutilasosastolla. Tilaraporttiaineistoa käytettäessä paremmat pisteet porsitusosaston ’eläinten terveys ja hoidon taso’ -kategoriasta lyhensivät eläinten lisääntymissykliä, lisäsivät syntyvien pahnueiden ja porsaiden määrää sekä alensivat kuolleena syntyneiden lukumäärää. Regressiomallin mukaan ’eläinten terveys ja hoidon taso’ -kategoria selitti syntyvien porsaiden lukumäärän, porsimisvälin pituuden sekä keskiporsimiskerran vaihtelua. Paremmat pisteet joutilasosaston ’liikkumismahdollisuudet’ kategoriasta alensivat syntyneiden pahnueiden sekä syntyneiden että vieroitettujen porsaiden lukumäärää. Regressiomallin mukaan ensikkopahnueiden osuus ja ”liikkumismahdollisuudet” kategorian pisteet selittivät vieroitettujen porsaiden lukumäärän vaihtelua. POTSI-aineiston yhteydessä kuolleena syntyneiden porsaiden lukumäärän aleneminen oli ensikoilla yhteydessä parempiin porsitusosaston ’sosiaalisiin kontakteihin’ ja emakoilla puolestaan joutilasosaston parempiin ’eläinten terveys ja hoidon taso’ pisteisiin. Kahden eri tuotantoaineiston avulla saadut tulokset erosivat toisistaan. Seuraavissa tutkimuksissa onkin suositeltavampaa käyttää Tilaraporttiaineistoja, joissa tuotokset ilmoitetaan vuosikohtaisina. Tämän tutkimuksen perusteella hyvinvoinnilla ja tuotoksella on yhteyksiä, joilla on myös merkittävää taloudellista vaikutusta. Erityisesti hyvä eläinten hoito ja eläinten terveys lisäävät tuotettujen porsaiden määrää ja lyhentävät lisääntymiskiertoa. Erityishuomiota tulee kiinnittää vapaana olevien joutilaiden emakoiden sosiaaliseen stressiin ja rehunsaannin varmistamiseen kaikille yksilöille.

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In the past decade, the Finnish agricultural sector has undergone rapid structural changes. The number of farms has decreased and the average farm size has increased when the number of farms transferred to new entrants has decreased. Part of the structural change in agriculture is manifested in early retirement programmes. In studying farmers exit behaviour in different countries, institutional differences, incentive programmes and constraints are found to matter. In Finland, farmers early retirement programmes were first introduced in 1974 and, during the last ten years, they have been carried out within the European Union framework for these programmes. The early retirement benefits are farmer specific and de-pend on the level of pension insurance the farmer has paid over his active farming years. In order to predict the future development of the agricultural sector, farmers have been frequently asked about their future plans and their plans for succession. However, the plans the farmers made for succession have been found to be time inconsistent. This study estimates the value of farmers stated succession plans in predicting revealed succession decisions. A stated succession plan exists when a farmer answers in a survey questionnaire that the farm is going to be transferred to a new entrant within a five-year period. The succession is revealed when the farm is transferred to a suc-cessor. Stated and revealed behaviour was estimated as a recursive Binomial Probit Model, which accounts for the censoring of the decision variables and controls for a potential correlation between the two equations. The results suggest that the succession plans, as stated by elderly farmers in the questionnaires, do not provide information that is significant and valuable in predicting true, com-pleted successions. Therefore, farmer exit should be analysed based on observed behaviour rather than on stated plans and intentions. As farm retirement plays a crucial role in determining the characteristics of structural change in agriculture, it is important to establish the factors which determine an exit from farming among eld-erly farmers and how off-farm income and income losses affect their exit choices. In this study, the observed choice of pension scheme by elderly farmers was analysed by a bivariate probit model. Despite some variations in significance and the effects of each factor, the ages of the farmer and spouse, the age and number of potential successors, farm size, income loss when retiring and the location of the farm together with the production line were found to be the most important determi-nants of early retirement and the transfer or closure of farms. Recently, the labour status of the spouse has been found to contribute significantly to individual retirement decisions. In this study, the effect of spousal retirement and economic incentives related to the timing of a farming couple s early retirement decision were analysed with a duration model. The results suggest that an expected pension in particular advances farm transfers. It was found that on farms operated by a couple, both early retirement and farm succession took place more often than on farms operated by a single person. However, the existence of a spouse delayed the timing of early retirement. Farming couples were found to co-ordinate their early retirement decisions when they both exit through agricultural retirement programmes, but such a co-ordination did not exist when one of the spouses retired under other pension schemes. Besides changes in the agricultural structure, the share and amount of off-farm income of a farm family s total income has also increased. In the study, the effect of off-farm income on farmers retirement decisions, in addition to other financial factors, was analysed. The unknown parameters were first estimated by a switching-type multivariate probit model and then by the simulated maxi-mum likelihood (SML) method, controlling for farmer specific fixed effects and serial correlation of the errors. The results suggest that elderly farmers off-farm income is a significant determinant in a farmer s choice to exit and close down the farm. However, off-farm income only has a short term effect on structural changes in agriculture since it does not significantly contribute to the timing of farm successions.

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Campylobacter, mainly Campylobacter jejuni and C. coli, are worldwide recognized as a major cause of bacterial food-borne gastroenteritis. Epidemiological studies have shown handling or eating of poultry to be significant risk factors for human infections. Campylobacter contamination can occur at all stages of a poultry meat production cycle. The aim of this thesis was to study the occurrence and diversity of Campylobacter in broiler and turkey production in Finland. In summer 1999, 2.9 % of slaughtered broiler flocks were Campylobacter-positive. From the isolated strains 94 % were C. jejuni and 6% were C. coli. During years 2005-2006 one turkey parent flock, the hatchery, six different commercial turkey farms and different stages of the slaughterhouse were monitored during one and the half year. No Campylobacter were detected in either of the samples from the turkey parent flock or from the hatchery using the culture method. Instead PCR detected DNA of Campylobacter from the turkey parent flock and samples from the hatchery. Six out of 12 commercial turkey flocks were found negative at the farm level but only two of those were negative at slaughter. Campylobacter-positive samples within the flock at slaughter were detected between 0% and 94% with evisceration and chilling water being the most critical stages for contamination. All of Campylobacter isolates were shown to be C. jejuni. Campylobacter-positive turkey flocks were colonized by a limited number of Campylobacter genotypes both at the farm and slaughter level. In conclusion, in our first study in 1999 a low prevalence of Campylobacter in Finnish broiler flocks was detected and it has remained at a low level during the study period until the present. In the turkey meat production, we found that flocks which were negative at the farm became contaminated with Campylobacter at the slaughter process. These results suggest that proper and efficient cleaning and disinfection of slaughter and processing premises are needed to avoid cross-contamination. Prevention of colonization at the farm by a high level of biosecurity control and hygiene may be one of the most efficient ways to reduce the amount of Campylobacter-positive poultry meat in Finland. With a persistent low level of Campylobacter-positive flocks, it could be speculated that the use of logistic slaughtering, according to Campylobacter status at farm, might have be advantageous in reducing Campylobacter contamination of retail poultry products. However, the significance of the domestic poultry meat for human campylobacteriosis in Finland should be evaluated.

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Campylobacter, mainly Campylobacter jejuni and C. coli, are worldwide recognized as a major cause of bacterial food-borne gastroenteritis (World Health Organization 2010). Epidemiological studies have shown handling or eating of poultry to be significant risk factors for human infections. Campylobacter contamination can occur at all stages of a poultry meat production cycle. In summer 1999, every broiler flock from all three major Finnish poultry slaughterhouses was studied during a five month period. Caecal samples were taken in the slaughterhouses from five birds per flock. A total of 1 132 broiler flocks were tested and 33 (2.9%) of those were Campylobacter-positive. Thirty-one isolates were identified as C. jejuni and two isolates were C. coli. The isolates were serotyped for heat-stable antigens (HS) and genotyped by pulsed-field gel electrophoresis (PFGE). The most common serotypes found were HS 6,7, 12 and 4-complex. Using a combination of SmaI and KpnI patterns, 18 different PFGE types were identified. Thirty-five Finnish C. jejuni strains with five SmaI/SacII PFGE types selected among human and chicken isolates from 1997 and 1998 were used for comparison of their PFGE patterns, amplified fragment length polymorphism (AFLP) patterns, HaeIII ribotypes, and HS serotypes. The discriminatory power of PFGE, AFLP and ribotyping with HaeIII were shown to be at the same level for this selected set of strains, and these methods assigned the strains into the same groups. The PFGE and AFLP patterns within a genotype were highly similar, indicating genetic relatedness. An HS serotype was distributed among different genotypes, and different serotypes were identified within one genotype. From one turkey parent flock, the hatchery, six different commercial turkey farms (together 12 flocks) and from 11 stages at the slaughterhouse a total of 456 samples were collected during one and the half year. For the detection of Campylobacter both conventional culture and a PCR method were used. No Campylobacter were detected in either of the samples from the turkey parent flock or from the hatchery samples using the culture method. Instead PCR detected DNA of Campylobacter in five faecal samples from the turkey parent flock and in one fluff and an eggshell sample. Six out of 12 commercial turkey flocks were found negative at the farm level but only two of those were negative at slaughter. Campylobacter-positive samples within the flock at slaughter were detected between 0% and 94%, with evisceration and chilling water being the most critical stages for contamination. All of a total of 121 Campylobacter isolates were shown to be C. jejuni using a multiplex PCR assay. PFGE analysis of all isolates with KpnI restriction enzyme resulted in 11 PFGE types (I-XI) and flaA-SVR typing yielded nine flaA-SVR alleles. Three Campylobacter-positive turkey flocks were colonized by a limited number of Campylobacter genotypes both at the farm and slaughter level.In conclusion, in our first study in 1999 a low prevalence of Campylobacter in Finnish broiler flocks was detected and it has remained at a low level during the study period until the present. In the turkey meat production, we found that flocks which were negative at the farm became contaminated with Campylobacter at the slaughter process. These results suggest that proper and efficient cleaning and disinfection of slaughter and processing premises are needed to avoid cross-contamination. Prevention of colonization at the farm by a high level of biosecurity control and hygiene may be one of the most efficient ways to reduce the amount of Campylobacter-positive poultry meat in Finland. In Finland, with a persistent low level of Campylobacter-positive flocks, it could be speculated that the use of logistic slaughtering, according to Campylobacter status at farm, might have be advantageous in reducing Campylobacter contamination of retail poultry products. However, the significance of the domestic poultry meat for human campylobacteriosis in Finland should be evaluated.

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Listeria monocytogenes is the causative agent of the severe foodborne infection listeriosis. The number of listeriosis cases in recent years has increased in many European countries, including Finland. Contamination of the pathogen needs to be minimized and growth to high numbers in foods prevented in order to reduce the incidence of human cases. The aim of this study was to evaluate contamination routes of L. monocytogenes in the food chain and to investigate methods for control of the pathogen in food processing. L. monocytogenes was commonly found in wild birds, the pig production chain and in pork production plants. It was found most frequently in birds feeding at landfill site, organic farms, tonsil samples, and sites associated with brining. L. monococytogenes in birds, farms, food processing plant or foods did not form distinct genetic groups, but populations overlapped. The majority of genotypes recovered from birds were also detected in foods, food processing environments and other animal species and birds may disseminate L. monocytogenes into food chain. Similar genotypes were found in different pigs on the same farm, as well as in pigs on farms and later in the slaughterhouse. L. monocytogenes contamination spreads at farm level and may be a contamination source into slaughterhouses and further into meat. Incoming raw pork in the processing plant was frequently contaminated with L. monocytogenes and genotypes in raw meat were also found in processing environment and in RTE products. Thus, raw material seems to be a considerable source of contamination into processing facilities. In the pork processing plant, the prevalence of L. monocytogenes increased in the brining area, showing that the brining was an important contamination site. Recovery of the inoculated L. monocytogenes strains showed that there were strain-specific differences in the ability to survive in lettuce and dry sausage. The ability of some L. monocytogenes strains to survive well in food production raises a challenge for industry, because these strains can be especially difficult to remove from the products and raises a need to use an appropriate hurdle concept to control most resistant strains. Control of L. monocytogenes can be implemented throughout the food chain. Farm-specific factors affected the prevalence of L. monocytogenes and good farm-level practices can therefore be utilized to reduce the prevalence of this pathogen on the farm and possibly further in the food chain. Well separated areas in a pork production plant had low prevalences of L. monocytogenes, thus showing that compartmentalization controls the pathogen in the processing line. The food processing plant, especially the brining area, should be subjected to disassembling, extensive cleaning and disinfection to eliminate persistent contamination by L. monocytogenes, and replacing brining with dry-salting should be considered. All of the evaluated washing solutions decreased the populations of L. monocytogenes on precut lettuce, but did not eliminate the pathogen. Thus, the safety of fresh-cut produce cannot rely on washing with disinfectants, and high-quality raw material and good manufacturing practices remain important. L. monocytogenes was detected in higher levels in sausages without the protective culture than in sausages with this protective strain, although numbers of L. monocytogenes by the end of the ripening decreased to the level of < 100 MPN/g in all sausages. Protective starter cultures provide an appealing hurdle in dry sausage processing and assist in the control of L. monocytogenes.

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This study is about the challenges of learning in the creation and implementation of new sustainable technologies. The system of biogas production in the Programme of Sustainable Swine Production (3S Programme) conducted by the Sadia food processing company in Santa Catarina State, Brazil, is used as a case example for exploring the challenges, possibilities and obstacles of learning in the use of biogas production as a way to increase the environmental sustainability of swine production. The aim is to contribute to the discussion about the possibilities of developing systems of biogas production for sustainability (BPfS). In the study I develop hypotheses concerning the central challenges and possibilities for developing systems of BPfS in three phases. First, I construct a model of the network of activities involved in the BP for sustainability in the case study. Next, I construct a) an idealised model of the historically evolved concepts of BPfS through an analysis of the development of forms of BP and b) a hypothesis of the current central contradictions within and between the activity systems involved in BP for sustainability in the case study. This hypothesis is further developed through two actual empirical analyses: an analysis of the actors senses in taking part in the system, and an analysis of the disturbance processes in the implementation and operation of the BP system in the 3S Programme. The historical analysis shows that BP for sustainability in the 3S Programme emerged as a feasible solution for the contradiction between environmental protection and concentration, intensification and specialisation in swine production. This contradiction created a threat to the supply of swine to the food processing company. In the food production activity, the contradiction was expressed as a contradiction between the desire of the company to become a sustainable company and the situation in the outsourced farms. For the swine producers the contradiction was expressed between the contradictory rules in which the market exerted pressure which pushed for continual increases in scale, specialisation and concentration to keep the production economically viable, while the environmental rules imposed a limit to this expansion. Although the observed disturbances in the biogas system seemed to be merely technical and localised within the farms, the analysis proposed that these disturbances were formed in and between the activity systems involved in the network of BPfS during the implementation. The disturbances observed could be explained by four contradictions: a) contradictions between the new, more expanded activity of sustainable swine production and the old activity, b) a contradiction between the concept of BP for carbon credits and BP for local use in the BPfS that was implemented, c) contradictions between the new UNFCCC1 methodology for applying for carbon credits and the small size of the farms, and d) between the technologies of biogas use and burning available in the market and the small size of the farms. The main finding of this study relates to the zone of proximal development (ZPD) of the BPfS in Sadia food production chain. The model is first developed as a general model of concepts of BPfS and further developed here to the specific case of the BPfS in the 3S Programme. The model is composed of two developmental dimensions: societal and functional integration. The dimension of societal integration refers to the level of integration with other activities outside the farm. At one extreme, biogas production is self-sufficient and highly independent and the products of BP are consumed within the farm, while at the other extreme BP is highly integrated in markets and networks of collaboration, and BP products are exchanged within the markets. The dimension of functional integration refers to the level of integration between products and production processes so that economies of scope can be achieved by combining several functions using the same utility. At one extreme, BP is specialised in only one product, which allows achieving economies of scale, while at the other extreme there is an integrated production in which several biogas products are produced in order to maximise the outcomes from the BP system. The analysis suggests that BP is moving towards a societal integration, towards the market and towards a functional integration in which several biogas products are combined. The model is a hypothesis to be further tested through interventions by collectively constructing the new proposed concept of BPfS. Another important contribution of this study refers to the concept of the learning challenge. Three central learning challenges for developing a sustainable system of BP in the 3S Programme were identified: 1) the development of cheaper and more practical technologies of burning and measuring the gas, as well as the reduction of costs of the process of certification, 2) the development of new ways of using biogas within farms, and 3) the creation of new local markets and networks for selling BP products. One general learning challenge is to find more varied and synergic ways of using BP products than solely for the production of carbon credits. Both the model of the ZPD of BPfS and the identified learning challenges could be used as learning tools to facilitate the development of biogas production systems. The proposed model of the ZPD could be used to analyse different types of agricultural activities that face a similar contradiction. The findings could be used in interventions to help actors to find their own expansive actions and developmental projects for change. Rather than proposing a standardised best concept of BPfS, the idea of these learning tools is to facilitate the analysis of local situations and to help actors to make their activities more sustainable.

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The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

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Alzheimer's disease (AD) is characterized by an impairment of the semantic memory responsible for processing meaning-related knowledge. This study was aimed at examining how Finnish-speaking healthy elderly subjects (n = 30) and mildly (n=20) and moderately (n = 20) demented AD patients utilize semantic knowledge to performa semantic fluency task, a method of studying semantic memory. In this task subjects are typically given 60 seconds to generate words belonging to the semantic category of animals. Successful task performance requires fast retrieval of subcategory exemplars in clusters (e.g., farm animals: 'cow', 'horse', 'sheep') and switching between subcategories (e.g., pets, water animals, birds, rodents). In this study, thescope of the task was extended to cover various noun and verb categories. The results indicated that, compared with normal controls, both mildly and moderately demented AD patients showed reduced word production, limited clustering and switching, narrowed semantic space, and an increase in errors, particularly perseverations. However, the size of the clusters, the proportion of clustered words, and the frequency and prototypicality of words remained relatively similar across the subject groups. Although the moderately demented patients showed a poor eroverall performance than the mildly demented patients in the individual categories, the error analysis appeared unaffected by the severity of AD. The results indicate a semantically rather coherent performance but less specific, effective, and flexible functioning of the semantic memory in mild and moderate AD patients. The findings are discussed in relation to recent theories of word production and semantic representation. Keywords: semantic fluency, clustering, switching, semantic category, nouns, verbs, Alzheimer's disease

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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.

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