Evaporative water loss from dairy cows in climate-controlled respiration chambers

The effects of ambient temperature (AT) on total evaporative water loss from dairy cows at different relative humidity (RH) and air velocity (AV) levels were studied. Twenty Holstein dairy cows with an average parity of 2.0 ± 0.7 and body weight of 687 ± 46 kg participated in the study. Two climate-controlled respiration chambers were used. The experimental indoor climate was programmed to follow a diurnal pattern with AT at night being 9°C lower than during the day. Night AT was gradually increased from 7 to 21°C and day AT was increased from 16°C to 30°C within an 8-d period, both with an incremental change of 2°C/d. The effect of 3 RH levels with a diurnal pattern were studied as well, with low values during the day and high values during the night: low (day, 30%; night, 50%), medium (day, 45%; night, 70%), and high (day, 60%; night, 90%). The effects of AV were studied during the daytime at 3 levels: no fan (0.1 m/s), fan at medium speed (1.0 m/s), and fan at high speed (1.5 m/s). The medium and high AV levels were only combined with medium RH. In total, there were 5 treatments with 4 replicates each. The animals had free access to feed and water. Based on the water balance principle inside the respiration chambers, the total evaporative water loss from dairy cows at a daily level was quantified by measuring the mass of water in the incoming and outgoing air, condensed water, added water from a humidifier, and evaporative water from a wet floor, drinking bowl, manure reservoir, and water bucket. Water evaporation from a sample skin area was measured with a ventilated skin box, and water evaporation, through respiration with a face mask. The results show that RH/AV levels had no significant effect on total evaporative water loss, whereas the interaction effect between RH/AV with AT was significant. Cows at a high RH had a tendency for a lower increasing rate of evaporative water loss compared with cows at a low RH (0.61 vs. 0.79 kg/d per 1°C increase of AT). Cows at medium and high AV levels had a greater increasing rate than cows at low AV (0.91 and 0.95 vs. 0.71 kg/d per 1°C increase of AT, respectively). The increase of evaporative heat loss from dairy cows was mainly a result of the increase in evaporation (of sweat) from the skin. The skin water evaporation determined with the water balance method (less evaporation from respiration) and the ventilated skin box method showed no significant difference. The implication of this study is that cows at a high AT depend mainly on evaporative cooling from the skin. The ventilated skin box method, measuring only a small part of the skin during a short period during the day, can be a convenient and accurate way to determine the total cutaneous evaporative water loss from cows.

Effects of increasing air temperature on skin and respiration heat loss from dairy cows at different relative humidity and air velocity levels

The focus of this study was to identify the effects of increasing ambient temperature (T) at different relative humidity (RH) and air velocity (AV) levels on heat loss from the skin surface and through respiration of dairy cows. Twenty Holstein dairy cows with an average parity of 2.0 ± 0.7 and body weight of 687 ± 46 kg participated in the study. Two climate-controlled respiration chambers were used. The experimental indoor climate was programmed to follow a diurnal pattern with ambient T at night being 9°C lower than during the day. Night ambient T was gradually increased from 7 to 21°C and day ambient T was increased from 16 to 30°C within an 8-d period, both with an incremental change of 2°C per day. A diurnal pattern for RH was created as well, with low values during the day and high values during the night (low: RH_l = 30-50%; medium: RH_m = 45-70%; and high: RH_h = 60-90%). The effects of AV were studied during daytime at 3 levels (no fan: AV_l = 0.1 m/s; fan at medium speed: AV_m = 1.0 m/s; and fan at high speed: AV_h = 1.5 m/s). The AV_m and AV_h were combined only with RH_m. In total, there were 5 treatments with 4 replicates (cows) for each. Effects of short and long exposure time to warm condition were evaluated by collecting data 2 times a day, in the morning (short: 1-h exposure time) and afternoon (long: 8-h exposure time). The cows were allowed to adapt to the experimental conditions during 3 d before the main 8-d experimental period. The cows had free access to feed and water. Sensible heat loss (SHL) and latent heat loss (LHL) from the skin surface were measured using a ventilated skin box placed on the belly of the cow. These heat losses from respiration were measured with a face mask covering the cow's nose and mouth. The results showed that skin SHL decreased with increasing ambient T and the decreasing rate was not affected by RH or AV. The average skin SHL, however, was higher under medium and high AV levels, whereas it was similar under different RH levels. The skin LHL increased with increasing ambient T. There was no effect of RH on the increasing rate of LHL with ambient T. A larger increasing rate of skin LHL with ambient T was observed at high AV level compared with the other levels. Both RH and AV had no significant effects on respiration SHL or LHL. The cows lost more skin sensible heat and total respiration heat under long exposure than short exposure. When ambient T was below 20°C the total LHL (skin + respiration) represented approx. 50% of total heat loss, whereas above 28°C the LHL accounted for more than 70% of the total heat loss. Respiration heat loss increased by 34 and 24% under short and long exposures when ambient T rose from 16 to 32°C.

Effects of increasing air temperature on physiological and productive responses of dairy cows at different relative humidity and air velocity levels

This study determined the effects of increasing ambient temperature (T) at different relative humidity (RH) and air velocity (AV) levels on the physiological and productive responses of dairy cows. Twenty Holstein dairy cows were housed inside climate-controlled respiration chambers, in which the climate was programmed to follow a daily pattern of lower night and higher day T with a 9°C difference, excluding effects from sun radiation. Within our 8-d data collection period, T was gradually increased from 7 to 21°C during the night (12 h) and 16 to 30°C during the day (12 h), with an incremental change of 2°C per day for both nighttime and daytime T. During each research period, RH and AV were kept constant at 1 of 5 treatment levels. A diurnal pattern for RH was created, with lower levels during the day and higher levels during the night: low (RH_l: 30-50%), medium (RH_m: 45-70%), and high (RH_h: 60-90%). The effects of AV were studied during the day at 3 levels: no fan (AV_l: 0.1 m/s), fan at medium speed (AV_m: 1.0 m/s), and fan at high speed (AV_h: 1.5 m/s). Effects of short and long exposure time to increasing T were evaluated by collecting data 2 times a day: in the morning [short: 1 h (or less) - exposure time] and afternoon (long: 8 h - exposure time). The animals had free access to feed and water and both were ad libitum. Respiration rate (RR), rectal temperature (RT), skin temperature (ST), dry matter intake, water intake, milk yield, and composition were measured. The inflection point temperatures (IPt) at which a certain variable started to change were determined for the different RH and AV levels and different exposure times. Results showed that IPt under long exposure time for RR (first indicator) varied between 18.9 and 25.5°C but was between 20.1 and 25.9°C for RT (a delayed indicator). The IPt for both RR and RT decreased with higher RH levels, whereas IPt increased with higher AV for RR but gave a minor change for RT. The ST was positively correlated with ambient T and ST was not affected by RH but significantly affected by AV. For RR, all IPt was lower under long exposure time than under short exposure time. The combination of higher RH levels and low AV level negatively affected dry matter intake. Water intake increased under all treatments except RH_l-AV_l. Treatment RH_h-AV_l negatively affected milk protein and fat yield, whereas treatments RH_m-AV_m and RH_m-AV_h reduced milk fat yield. We concluded that RH and AV significantly affected the responses of RR, RT, ST, and productive performance of high-producing Holstein cows. These responses already occurred at moderate ambient T of 19 to 26°C.

Hot topic: Automated assessment of reticulo-ruminal motility in dairy cows using 3-dimensional vision

Reticulo-ruminal motility is a well-established indicator of gastrointestinal health in dairy cows. The currently available methods for assessing motility are labor-intensive, costly, and impractical to use regularly for all cows on a farm. We hypothesized that the reticulo-ruminal motility of dairy cows could be assessed automatically and remotely using a low-cost 3-dimensional (3D) camera. In this study, a 3D vision system was constructed and mounted on the frame of an automatic milking robot to capture the left paralumbar fossa of 20 primiparous cows. For each cow, the system recorded 3D images at 30 frames per second during milking. Each image was automatically processed to locate the left paralumbar fossa region and quantify its average concavity. Then, the average concavity values from all images of 1 cow during 1 milking process were chronologically assembled to form an undulation signal. By applying fast Fourier transformation to the signal, we identified cyclic oscillations that occurred in the same frequency range as reticulo-ruminal contractions. To validate the oscillation identification, 2 trained assessors visually identified reticulo-ruminal contractions from the same 3D image recordings on screen. The matching sensitivity between the automatically identified oscillations and the manually identified reticulo-ruminal contractions was 0.97. This 3D vision system can automate the assessment of reticulo-ruminal motility in dairy cows. It is noninvasive and can be implemented on farms without distressing the cows. It is a promising tool for farmers, giving them regular information about the gastrointestinal health of individual cows and helping them in daily farm management.

Automated body condition scoring of dairy cows using 3-dimensional feature extraction from multiple body regions

Machine vision technology has been used in automated body condition score (BCS) classification of dairy cows. The current vision-based classifications use information acquired from a limited number of body regions of the cow. Our study aimed to improve automated BCS classification by including multiple body condition-related features extracted from 3 viewpoints in 8 body regions. The data set of this study included 44 lactating cows with their BCS evenly distributed over the scale of BCS from 1.5 to 4.5 units. The body images of these cows were recorded over 2 consecutive days using 3-dimensional cameras positioned to view the cow from the top, right side, and rear. Each image was automatically processed to identify anatomical landmarks on the body surface. Around these anatomical landmarks, the bony prominences and body surface depressions were quantified to describe 8 body condition-related features. A manual BCS of each cow was independently assigned by 2 trained assessors using the same predefined protocol. With the extracted features as inputs and manual BCS as the reference, we built a nearest-neighbor classification model to classify BCS and obtained an overall classification sensitivity of 0.72 using a 10-fold cross-validation. We conclude that the sensitivity of automated BCS classification has been improved by expanding the selection of body condition-related features extracted from multiple body regions.

Abatement of particulate matter emission from experimental aviary housings for laying hens by spraying rapeseed oil

In alternative systems for laying hens, concentrations and emission rates of particulate matter (PM) give reason for concern with regard to working conditions, bird health and productivity, and health of residents living near farms. Previously, we found that spraying a film of rapeseed oil onto the litter of broilers could substantially reduce PM concentrations and emissions. The objective of this study was to establish dose-response effects of oil spraying in aviaries on concentrations and emission rates of PM with aerodynamic diameters less than 10 μm (PM₁₀) and 2.5 μm (PM_2.5), on stockmen's exposure to PM₁₀, on egg production, exterior quality and behavior of the hens, and on the litter. An experiment was carried out with 4 treatments: 0 (control), 15, 30, and 45 mL/m² per d (oil treatments). Each treatment was applied in 2 rooms with different aviary systems (8 rooms in total). The experiment was repeated during a second period, both lasting 35 days. From d 11 to d 35, oil was applied daily using a spraying gun. Applying 15, 30, or 45 mL/m² per d significantly reduced emission rates of PM₁₀ by 27, 62, and 82%, and emission rates of PM_2.5 by 71, 83, and 94%, respectively. No significant effects of oil spraying were found on mortality, egg production, dust bathing behavior, scratching behavior, plumage soiling, DM content of the litter, or friability of the litter. A significant worsening of the plumage condition was found only for the body spot back/wings/tail (not for: throat/neck, chest/breast, or legs) in the 45 mL/m² per d treatment. Egg quality shifted significantly towards more second-class eggs in the oil treatments (1.9% versus 1.4%; P = 0.004). Remarkably, foot soiling decreased with increasing oil application. In conclusion, PM concentrations and emission rates in aviaries can be effectively reduced by spraying 15 to 30 mL/m² per d with minor side effects within a 25 d application period.

A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff.

Energy demand on dairy farms in Ireland

Reducing electricity consumption in Irish milk production is a topical issue for 2 reasons. First, the introduction of a dynamic electricity pricing system, with peak and off-peak prices, will be a reality for 80% of electricity consumers by 2020. The proposed pricing schedule intends to discourage energy consumption during peak periods (i.e., when electricity demand on the national grid is high) and to incentivize energy consumption during off-peak periods. If farmers, for example, carry out their evening milking during the peak period, energy costs may increase, which would affect farm profitability. Second, electricity consumption is identified in contributing to about 25% of energy use along the life cycle of pasture-based milk. The objectives of this study, therefore, were to document electricity use per kilogram of milk sold and to identify strategies that reduce its overall use while maximizing its use in off-peak periods (currently from 0000 to 0900 h). We assessed, therefore, average daily and seasonal trends in electricity consumption on 22 Irish dairy farms, through detailed auditing of electricity-consuming processes. To determine the potential of identified strategies to save energy, we also assessed total energy use of Irish milk, which is the sum of the direct (i.e., energy use on farm) and indirect energy use (i.e., energy needed to produce farm inputs). On average, a total of 31.73 MJ was required to produce 1 kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity accounted for 60% of the direct energy use, and mainly resulted from milk cooling (31%), water heating (23%), and milking (20%). Analysis of trends in electricity consumption revealed that 62% of daily electricity was used at peak periods. Electricity use on Irish dairy farms, therefore, is substantial and centered around milk harvesting. To improve the competitiveness of milk production in a dynamic electricity pricing environment, therefore, management changes and technologies are required that decouple energy use during milking processes from peak periods.