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Abstract: Fish production in marine netcages is expanding rapidly in many parts of the world. Nevertheless, production planning and layout design tools still rely on rule of thumb, spreadsheets, local experience and practices handed down through the generations. An integrated model (queuing, optimization and simulation were linked together) was developed. The solution finds the values of decision variables to maximize yearly production. The concept was that a single netcage can be seen as a “server” in which neither a “queue” (over-holding of fish), nor an idle netcage is allowed. A marine fish farm can then be seen as a queuing network, and a queuing network-based management model was developed. Growth data of 40 batches of fish, each batch comprising on average 180,000 fish (std 50,000), were recorded over an experimental period of 4 years. The model inputs were (1) the empirical fish growth rates (2) the given space for netcages, (3) preferred netcage holes, netcage depth and netcage diameter, (4) fingerling supply limitations, (5) market timing, and (6) Preferred market-size fish at the farm gate. The model outputs were: (7) optimal fingerling arrival frequency, (8) optimal number of fingerlings in a batch, (9) number of days in each culture netcage, (10) grading and sorting criteria along the production line, and (11) optimal facility allocation (number of netcages for each growing phase). Model validity was statistically tested and was not rejected within the 95% confidence level. The model application results with 4 netcages in the 1st growing phase, 8 netcages in the 2nd growing phase and 16 netcages in the 3rd growing phase (so called “4,8,16 layout”) gave the following optimal operating parameters: arrival of a batch every 30 days; 122 days in each successive growth phase. The optimal values satisfied the biomass density criterion of less than 25kgm−3 and the netcage utilization criterion of never below 99%. Expected production was 2403tonyear−1 (vs. the current 686tonyear−1). The enterprise owners decided to adopt the model results and the system is now being built according to the 4,8,16 design. [Copyright &y& Elsevier]

Abstract: The design and management of a recirculating aquaculture system (RAS) is crucial for the farm''s economic survival. In a previous paper (Part I of this study), a model was developed. The current paper extends the principles developed in Part I by (1) addressing a larger-scale RAS, (2) addressing the layout positioning problem, (3) integrating a robust 6σ design into the optimization problem. A queuing model and a solvable nonlinear constrained optimization problem including the 6σ robust design were developed and validated. The design criteria were: (1) turnover ≥1000ton/year, (2) 7 days quarantine, i.e., at least 7 days between arrivals of two successive fish batches, (3) fish biomass density ≤55kg/m3, (4) three growth phases, (5) neither fish-sorting nor batch-splitting events allowed, and (6) a robust design to accommodate two species—seabream and seabass grouper, with different growth rates. Decision variables were: (1) number of culture tanks, (2) fingerling arrival frequency, (3) number of fingerlings per batch, (4) number of days in a growth phase, (5) timing of grading and sorting criteria on the production lines, (5) standing biomass in the entire system, which is the actual biomass load on the biofilters, (6) feed amount per day. The optimal layout was: 13 culture tanks in each of the three growth phases (39 tanks total). Optimal parameters included: arrival frequency—a single fish batch into the system every 7 days, 91 days in each phase; growth up to 77, 233, and 468g in successive growth phases. Optimal values satisfied the criteria of biomass density below 50kg/m3 and culture tank utilization above 99%. Expected production was 1000ton/year. The proposed layout can accommodate different fish species—here, seabream and grouper—under the same culture volume, density, and schedule, but with different growth rates. Increasing the desired biomass density from 50 to 60kg/m3 advances expected production to 1335ton/year. The numerical values reflect local aquatic conditions, but the proposed methodology can be applied anywhere. [Copyright &y& Elsevier]

Abstract: This study describes the design and management of an effective recirculating aquaculture system (RAS). The RAS design involves many aspects, both physical and biological: (1) a desired turnover, (2) fingerling arrival frequency, (3) number of fingerlings per batch, (4) number of days in a growth phase, (4) timing of grading and sorting, based on (5) fish growth rate, and (6) number of culture tanks. The design criteria were: (1) turnover of 250ton/year, (2) fingerling arrival frequency of 12batches/year, (3) biomass density ≤60kg/m3, (4) two fish batch-sorting and batch-splitting events, and (5) a robust design to accommodate two species—slower- and faster-growing species. The culture tank was regarded as a queuing system in which neither a “queue” (overholding of fish) nor an idle culture tank is allowed, enabling modeling of the fish farm as a queuing network. A queuing model, stochastic simulation, optimization, and six sigma robust design were developed, validated, and implemented. The optimal layout was found to comprise three growth phases, with 1, 8, and 24 culture tanks, respectively. Optimal parameters included: arrival frequency—a single fish batch into the system every 30 days; then 30, 120 and 180 days in the 1st, 2nd and 3rd phases, to 42, 200, and 440g, respectively. The optimal values satisfied the criteria of biomass density below 60kg/m3 and culture tank utilization above 93%. Expected production was 250–276ton/year. The proposed layout can accommodate different fish species with different growth rates under the same proposed layout, culture volume, density, and schedule. The numerical values reflect local aquatic conditions, but the proposed methodology can be applied elsewhere. [Copyright &y& Elsevier]

Abstract: When the environmental and/or market conditions of an intensive aquacultural operation vary with time, maximization of profit may require a time dependent fish stocking rate. A simplified stocking problem is formulated where temperature, market price and/or market demand change sinusoidally over the annual cycle. The fish biomass sustaining-capacity is limited by the water treatment equipment, and is expressed in terms of maximum feeding rate per unit volume of culture tanks. It is demonstrated that under such conditions, sinusoidal stocking rates produce good sub-optimal solutions. A critical element of the solution is the time delay (phase-shift) between the constraining (restricting) conditions (temperature and market), and the stocking cycle. Furthermore, if the solutions for two individual conditions have very different time delays, a combination of the two conflicting restrictions is likely to produce poor returns. [Copyright &y& Elsevier]

Abstract: The aim of this study was to develop a simulation model for finding the optimal layout and management regime for a re-circulating aquaculture system (RAS). The work plan involved: (1) quantifying the effects of fish growth and management practices on production; (2) developing a mathematical simulation model for the RAS, taking into account all factors that directly influence system profitability; and (3) estimating the production costs and, hence, the profitability of an RAS. The resulting model is process-oriented, following the flow of fish through the RAS facility, and generates an animated graphic representation of the processes through which the fish passes as it progress through the system. The simulation assesses the performance in terms of yearly turnover, stocking density, tank utilization and biomass in process, and uses statistics to track the state of the RAS and record changes that affect efficiency. The economic impact of system design and operation was modeled to enable a user to anticipate how changes in design or operating practices, costs of inputs, or price of products affect system profitability. The proposed approach overcomes difficulties in characterizing RAS design and operation. The simulation approach allows all of the RAS''s components such as equipment, biological processes (e.g., fish growth), and management practices to be evaluated jointly, so that an initial design can be fine-tuned to produce an optimized system and management regime suited to a specific fish farm within a reasonable time. The methodology was executed step-by-step to design an optimal RAS that meets both economic and stocking-density limits. Optimal design specifications were presented for several case studies based on data from Kibbutz Sde Eliahu''s RAS, in which Nile tilapia (Oreochromis niloticus) are raised in 20 concrete raceways. Further research should include more extensive testing and validation of the integrated model, which then should be disseminated to the aquaculture community. [Copyright &y& Elsevier]

Due to water turbidity, fish stress might be difficult to observe. Evaluation of fish stress by blood sampling requires removing a fish from the water, which is in itself a stressful event. Therefore, we designed and built a sensor to detect fish behaviour that reflects stress. The electronic sensor detected early signs of fish stress by scoring the fish's inactivity. LEDs and detectors are embedded on a steel wand that is held underwater by an operator. In this preliminary (feasibility) study, the new sensor was validated for Tilapia ( Cichlidae ) and Hybrid Striped Bass (Morone) . We induced stressful situations in the fish tanks by manipulating oxygen and temperature levels. Results Lowering the temperature and oxygen levels both significantly increased the average number of signals identified by the sensor, which indicate stress. The effect of reducing water temperature from 24 °C to 15 °C was three times stronger than was the effect of lowering the oxygen saturation level from 85% to 50%. The difference in the number of signals between the good and stressful conditions was statistically significant, amounting to approximately eight sensor signals, 10.57 compared to 2.49 respectively. Lowering the temperature increased the mean number of signals by 5.85 and 6.06 at 85% and 50% oxygen saturation respectively, whereas lowering oxygen levels increased the mean number of signals by 2.02 and 2.23 at 24 °C and 15 °C, respectively. The results indicate that the stress status of cultured fish can be evaluated using the proposed behavioural sensor. The new sensor may provide an earlier indication of a problem in a fish tank or pond than was heretofore possible. This early warning can enable the fish farmer to take action before many fish are harmed. [ABSTRACT FROM AUTHOR]

Body condition scoring (BCS) is a farm-management tool for estimating dairy cows' energy reserves. Today, BCS is performed manually by experts. This paper presents a 3-dimensional algorithm that provides a topographical understanding of the cow's body to estimate BCS. An automatic BCS system consisting of a Kinect camera (Microsoft Corp., Redmond, WA) triggered by a passive infrared motion detector was designed and implemented. Image processing and regression algorithms were developed and included the following steps: (1) image restoration, the removal of noise; (2) object recognition and separation, identification and separation of the cows; (3) movie and image selection, selection of movies and frames that include the relevant data; (4) image rotation, alignment of the cow parallel to the x-axis; and (5) image cropping and normalization, removal of irrelevant data, setting the image size to 150 × 200 pixels, and normalizing image values. All steps were performed automatically, including image selection and classification. Fourteen individual features per cow, derived from the cows' topography, were automatically extracted from the movies and from the farm's herd-management records. These features appear to be measurable in a commercial farm. Manual BCS was performed by a trained expert and compared with the output of the training set. A regression model was developed, correlating the features with the manual BCS references. Data were acquired for 4 d, resulting in a database of 422 movies of 101 cows. Movies containing cows' back ends were automatically selected (389 movies). The data were divided into a training set of 81 cows and a test set of 20 cows; both sets included the identical full range of BCS classes. Accuracy tests gave a mean absolute error of 0.26, median absolute error of 0.19, and coefficient of determination of 0.75, with 100% correct classification within 1 step and 91% correct classification within a half step for BCS classes. Results indicated good repeatability, with all standard deviations under 0.33. The algorithm is independent of the background and requires 10 cows for training with approximately 30 movies of 4 s each. [ABSTRACT FROM AUTHOR]

Lameness is still an important problem in modern dairy farming. Human observation of locomotion, by looking at different traits in one go, is used in practice to assess locomotion. The objectives of this article were to determine which individual locomotion traits are most related to locomotion scores in dairy cows, and whether experienced raters are capable of scoring these individual traits consistently. Locomotion and 5 individual locomotion traits (arched back, asymmetric gait, head bobbing, reluctance to bear weight, and tracking up) were scored independently on a 5-level scale for 58 videos of different cows. Videos were shown to 10 experienced raters in 2 different scoring sessions. Relations between locomotion score and traits were estimated by 3 logistic regression models aiming to calculate the size of the fixed effects on the probability of scoring a cow in 1 of the 5 levels of the scale (model 1) and the probability of classifying a cow as lame (locomotion score ≥3; model 2) or as severely lame (locomotion score ≥4; model 3). Fixed effects were rater, session, traits, and interactions among fixed effects. Odds ratios were calculated to estimate the relative probability to classify a cow as lame when an altered (trait score ≥3) or severely altered trait (trait score ≥4) was present. Overall intrarater and interrater reliability and agreement were calculated as weighted kappa coefficient (κw) and percentage of agreement, respectively. Specific intrarater and interrater agreement for individual levels within a 5-level scale were calculated. All traits were significantly related to the locomotion score when scored with a 5-level scale and when classified as (severely) lame or nonlame. Odds ratios for altered and severely altered traits were 10.8 and 14.5 for reluctance to bear weight, 6.5 and 7.2 for asymmetric gait, and 4.8 and 3.2 for arched back, respectively. Raters showed substantial variation in reliability and agreement values when scoring traits. The acceptance threshold for overall intrarater reliability (κw ≥0.60) was exceeded by locomotion scoring and all traits. Overall interrater reliability values ranged from κw = 0.53 for tracking up to κw = 0.61 for reluctance to bear weight. Intrarater and interrater agreement were below the acceptance threshold (percentage of agreement <75%). Most traits tended to have lower specific intrarater and interrater agreement in level 3 and 5 of the scale. In conclusion, raters had difficulties in scoring locomotion traits consistently, especially slight alterations were difficult to detect by experienced raters. Yet, the locomotion traits reluctance to bear weight, asymmetric gait, and arched back had the strongest relation with the locomotion score. These traits should have priority in locomotion-scoring-system guidelines and are the best to be used for the development of automated locomotion scoring systems. [ABSTRACT FROM AUTHOR]

Locomotion scores are used for lameness detection in dairy cows. In research, locomotion scores with 5 levels are used most often. Analysis of scores, however, is done after transformation of the original 5-level scale into a 4-, 3-, or 2-level scale to improve reliability and agreement. The objective of this study was to evaluate different ways of merging levels to optimize resolution, reliability, and agreement of locomotion scores for dairy cows. Locomotion scoring was done by using a 5-level scale and 10 experienced raters in 2 different scoring sessions from videos from 58 cows. Intra- and interrater reliability and agreement were calculated as weighted kappa coefficient (KW) and percentage of agreement (PA), respectively. Overall intra- and interrater reliability and agreement and specific intra- and interrater agreement were determined for the 5-level scale and after transformation into 4-, 3-, and 2-level scales by merging different combinations of adjacent levels. Intrarater reliability (KW) ranged from 0.63 to 0.86, whereas intrarater agreement (PA) ranged from 60.3 to 82.8% for the 5-level scale. Interrater KW = 0.28 to 0.84 and interrater PA = 22.6 to 81.8% for the 5-level scale. The specific intrarater agreement was 76.4% for locomotion level 1, 68.5% for level 2, 65% for level 3, 77.2% for level 4, and 80% for level 5. Specific interrater agreement was 64.7% for locomotion level 1, 57.5% for level 2, 50.8% for level 3, 60% for level 4, and 45.2% for level 5. Specific intra- and interrater agreement suggested that levels 2 and 3 were more difficult to score consistently compared with other levels in the 5-level scale. The acceptance threshold for overall intra- and interrater reliability (KW and K ≥0.6) and agreement (PA ≥75%) and specific intra- and interrater agreement (≥75% for all levels within locomotion score) was exceeded only for the 2-level scale when the 5 levels were merged as (12)(345) or (123)(45). In conclusion, when locomotion scoring is performed by experienced raters without further training together, the lowest specific intra- and interrater agreement was obtained in levels 2 and 3 of the 5-level scale. Acceptance thresholds for overall intra- and interrater reliability and agreement and specific intra- and interrater agreement were exceeded only in the 2-level scale. [ABSTRACT FROM AUTHOR]

Abstract: An animal expresses its physiological and well-being status by its behaviour. Changes in behaviour can be associated with health, production or well-being problems and therefore with the profitability of the farm. The objectives of the present study were to analyse lying patterns of healthy cows, collected with a commercial behaviour sensor, in early lactation in relation to environmental conditions, age of the cow and production performance. In future, these results may be used as a ‘baseline’ for detection of alterations in behaviour that indicate health problems. The study involved 210 healthy multiparous Israeli Holstein cows in three commercial dairy farms. Only healthy cows during the first 28 days after calving were included in this study. Data were analysed in relation to calving season, age of cows and correlation between milk production and lying time. The results show that lying time increased significantly with age and is significantly (P <0.05) higher in winter than in summer (summer lactation 2: 491±17min/day (mean±SD), summer lactation 3 and more: 520±25min/day, winter lactation 2: 531±25min/day, winter lactation 3 and more: 579±38min/day). The proportion of positively and negatively milk production and lying time correlated cows is affected by calving season. This study indicates that behaviour variables in early lactation are affected by calving season, lactation number and type of correlation between milk production and lying time. [Copyright &y& Elsevier]

Abstract: This study examined the biomass yield and nutritive value for lactating cows of two sorghum silages, a new brown mid-rib BMR-101 variety (BMR) and the commercial hybrid FS-5 widely used in Israel, in comparison with the corn Oropesa silage. Forages were grown in a Mediterranean climate in five replicate plots, harvested by a combine harvester at the soft dough stage and ensiled in bunker silos. The BMR plants had high degree of lodging, and the yield of forage dry matter (DM) was highest for corn, intermediate for FS-5 and lowest for BMR. Ensiling resulted in moderate DM losses for corn and FS-5 and higher losses for BMR, but all silages were stable after exposure to air. The in vitro DM digestibility (IVDMD) of BMR and corn silages were similar and higher than that of the FS-5 silage. Forty-two milking cows were assigned into three groups of 14 cows each, that were similar in their initial performance and DM intake, and fed three total mixed rations (TMR) containing either BMR, FS-5 or corn silages as the basal forage, in a 3×3 Latin square design. Each period consisted of 2 adaptation weeks to the TMR plus 5 data collection weeks. There were no differences in DM intake among cows fed the three silage-based TMR, but the number of voluntary daily meals per cow was higher for the FS-5-fed group versus the BMR and corn groups. In contrast, DM intake per meal and average meal duration were higher for the cows fed the corn and BMR-based TMR. Rate of feed consumption and daily eating duration were similar in the three treatments. Milk yield of the cows fed the corn-based TMR was higher than that of the FS-5 group, while that of BMR group was intermediate (42.1 vs. 40.7 and 41.4kg /d, respectively). The two groups fed the sorghum TMR had higher milk fat production, while the group fed corn silage TMR had higher milk and milk protein production and moderate milk fat yield and content, as well as the lowest loss of body weight (BW). However, silage yield per hectare, digestibility of the silage, and availability of water for irrigation are the dominant parameters when deciding which forage varieties to grow. [Copyright &y& Elsevier]