Developing a new thermal comfort prediction model and web-based application for heat stress assessment in dairy cows

This study aims to characterize the influence of short-term heat stress (HS; 4 day) in early lactating Holstein dairy cows, in terms of triggering blood metabolomics and parameters, milk yield and composition, and milk microRNA expression. Eight cows (milk yield = 30 ± 1.5 kg/day, parity = 1.09 ± 0.05) were homogeneously housed in environmentally controlled chambers, assigned into two groups with respect to the temperature humidity index (THI) at two distinct levels: approximately ~71 (low-temperature, low-humidity; LTLH) and ~86 (high-temperature, high-humidity; HTHH). Average feed intake (FI) dropped about 10 kg in the HTHH group, compared with the LTLH group (p = 0.001), whereas water intake was only numerically higher (p = 0.183) in the HTHH group than in the LTLH group. Physiological parameters, including rectal temperature (p = 0.001) and heart rate (p = 0.038), were significantly higher in the HTHH group than in the LTLH group. Plasma cortisol and haptoglobin were higher (p < 0.05) in the HTHH group, compared to the LTLH group. Milk yield, milk fat yield, 3.5% fat-corrected milk (FCM), and energy-corrected milk (ECM) were lower (p < 0.05) in the HTHH group than in the LTLH group. Higher relative expression of milk miRNA-216 was observed in the HTHH group (p < 0.05). Valine, isoleucine, methionine, phenylalanine, tyrosine, tryptophan, lactic acid, 3-phenylpropionic acid, 1,5-anhydro-D-sorbitol, myo-inositol, and urea were decreased (p < 0.05). These results suggest that early lactating cows are more vulnerable to short-term (4 day) high THI levels—that is, HTHH conditions—compared with LTLH, considering the enormous negative effects observed in measured blood metabolomics and parameters, milk yield and compositions, and milk miRNA-216 expression.

Download Full-text

Effects of dry period length on milk yield and content and metabolic status of high-producing dairy cows under heat stress

Tropical Animal Health and Production ◽

10.1007/s11250-021-02634-1 ◽

2021 ◽

Vol 53 (2) ◽

Author(s):

A. Boustan ◽

V. Vahedi ◽

M. Abdi Farab ◽

H. Karami ◽

R. Seyedsharifi ◽

...

Keyword(s):

Heat Stress ◽

Dairy Cows ◽

Milk Yield ◽

Period Length ◽

Metabolic Status ◽

Dry Period

Download Full-text

Simulating Heat Stress of Coal Gangue Spontaneous Combustion on Vegetation Using Alfalfa Leaf Water Content Spectral Features as Indicators

Remote Sensing ◽

10.3390/rs13132634 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2634

Author(s):

Qiyuan Wang ◽

Yanling Zhao ◽

Feifei Yang ◽

Tao Liu ◽

Wu Xiao ◽

...

Keyword(s):

Heat Stress ◽

Water Content ◽

Spontaneous Combustion ◽

Leaf Water ◽

Coal Gangue ◽

Leaf Water Content ◽

Spectral Features ◽

Lasso Regression ◽

Stress Assessment ◽

First Derivative

Vegetation heat-stress assessment in the reclamation areas of coal gangue dumps is of great significance in controlling spontaneous combustion; through a temperature gradient experiment, we collected leaf spectra and water content data on alfalfa. We then obtained the optimal spectral features of appropriate leaf water content indicators through time series analysis, correlation analysis, and Lasso regression analysis. A spectral feature-based long short-term memory (SF-LSTM) model is proposed to estimate alfalfa’s heat stress level; the live fuel moisture content (LFMC) varies significantly with time and has high regularity. Correlation analysis of the raw spectrum, first-derivative spectrum, spectral reflectance indices, and leaf water content data shows that LFMC and spectral data were the most strongly correlated. Combined with Lasso regression analysis, the optimal spectral features were the first-derivative spectral value at 1661 nm (abbreviated as FDS (1661)), RVI (1525,1771), DVI (1412,740), and NDVI (1447,1803). When the classification strategies were divided into three categories and the time sequence length of the spectral features was set to five consecutive monitoring dates, the SF-LSTM model had the highest accuracy in estimating the heat stress level in alfalfa; the results provide an important theoretical basis and technical support for vegetation heat-stress assessment in coal gangue dump reclamation areas.

Download Full-text

Computational modeling of a conductive cooling system to alleviate heat stress in dairy cows

10.13031/2013.41850 ◽

2012 ◽

Author(s):

Mario R Mondaca ◽

Fernando Rojano ◽

Christopher Y Choi

Keyword(s):

Heat Stress ◽

Computational Modeling ◽

Dairy Cows ◽

Cooling System

Download Full-text

Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review

Animals ◽

10.3390/ani11040980 ◽

2021 ◽

Vol 11 (4) ◽

pp. 980

Author(s):

Hang Shu ◽

Wensheng Wang ◽

Leifeng Guo ◽

Jérôme Bindelle

Keyword(s):

Heat Stress ◽

Early Detection ◽

Dairy Cows ◽

Real Time ◽

Dairy Farms ◽

Time Measurement ◽

Heat Strain ◽

Detection Methods ◽

Livestock Farming ◽

Real Time Measurement

In pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows.

Download Full-text

Heat stress assessment in artistic glass units

Industrial Health ◽

10.2486/indhealth.2017-0143 ◽

2018 ◽

Vol 56 (2) ◽

pp. 171-184 ◽

Cited By ~ 5

Author(s):

Francesca Romana d’AMBROSIO ALFANO ◽

Boris Igor PALELLA ◽

Giuseppe RICCIO ◽

Massimo BARTALINI ◽

Fabio STRAMBI ◽

...

Keyword(s):

Heat Stress ◽

Stress Assessment

Download Full-text

Effect of heat stress on milk production and its composition of Holstein Friesian crossbred dairy cows

Asian Journal of Medical and Biological Research ◽

10.3329/ajmbr.v2i2.29060 ◽

2016 ◽

Vol 2 (2) ◽

pp. 190-195 ◽

Cited By ~ 1

Author(s):

Mahmud Al Reyad ◽

Md Abid Hasan Sarker ◽

Md Elias Uddin ◽

Raihan Habib ◽

Md Harun Ur Rashid

Keyword(s):

Heat Stress ◽

Dairy Cows ◽

Milk Yield ◽

Management Practices ◽

Management Strategies ◽

Dairy Farm ◽

Milk Composition ◽

Mustard Oil ◽

Holstein Friesian ◽

Significant Difference

The aim of this research was to observe the effect of heat stress on milk yield and milk compositions of Holstein Friesian crossbred (HF) dairy cows. To fulfill the objectives, a total of 9 Holstein Friesian crossbred cows were selected for this study. Green grasses (German, Para) were supplied adlibitum and concentrate feeds (mixture of wheat bran, rice polish, mustard oil cake, di-calcium phosphate and salt) were supplied at the rate of 2.0 kg/day/cow. Management practices for all the cows were similar following the BAU Dairy farm practices. Data were collected on milk yield (l/h/d), relative humidity (%) and barn temperature (0C). The obtained temperature humidity index (THI) of July, August, September and October were 84.95, 81.99, 81.40 and 79.57, respectively. The highest THI was found in July which indicated higher heat stress during this month. A significant difference (p<0.05) in milk yield of cows was found among different months of July to October. The highest milk yield (6.10±0.50 l/h/d) was found in October among observed months. The compositions of milk such as total solids (TS), solids-not-fat (SNF), fat, protein, lactose, and ash also differed significantly (p<0.01). The highest values (%) of TS, SNF, fat, protein, lactose and ash content of milk were found in October as 12.63, 8.80, 3.83, 3.69, 4.39 and 0.72, respectively and lowest values (%) were in July as 12.20, 8.50, 3.71, 3.50, 4.30 and 0.69, respectively due to the high THI value. From these results, it is concluded that heat stress has strong effect on milk yield and milk composition of HF cows in Bangladesh. Management strategies are needed to minimize heat stress and attain optimal dairy animal performance.Asian J. Med. Biol. Res. June 2016, 2(2): 190-195

Download Full-text