Predicting physiological responses of dairy cows using comprehensive variables

[1]  Hang Shu,et al.  Evaluation of environmental and physiological indicators in lactating dairy cows exposed to heat stress , 2022, International Journal of Biometeorology.

[2]  Yongfeng Li,et al.  Evaluation of the Best Region for Measuring Eye Temperature in Dairy Cows Exposed to Heat Stress , 2022, Frontiers in Veterinary Science.

[3]  H. Moon,et al.  Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables , 2021, International journal of environmental research and public health.

[4]  Kaixin Liu,et al.  The effects of cow-related factors on rectal temperature, respiration rate, and temperature-humidity index thresholds for lactating cows exposed to heat stress. , 2021, Journal of thermal biology.

[5]  P. Tassinari,et al.  Random Forest Modelling of Milk Yield of Dairy Cows under Heat Stress Conditions , 2021, Animals : an open access journal from MDPI.

[6]  Hang Shu,et al.  Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review , 2021, Animals : an open access journal from MDPI.

[7]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[8]  S. Hörtenhuber,et al.  Efficacy of adaptation measures to alleviate heat stress in confined livestock buildings in temperate climate zones , 2020, Biosystems Engineering.

[9]  Kevin Howell,et al.  Thermal camera performance and image analysis repeatability in equine thermography , 2020 .

[10]  Sigfredo Fuentes,et al.  Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras , 2020, Sensors.

[11]  Gan Li,et al.  Short communication: The lag response of daily milk yield to heat stress in dairy cows. , 2020, Journal of dairy science.

[12]  M. Marufuzzaman,et al.  Predicting dairy cattle heat stress using machine learning techniques. , 2020, Journal of dairy science.

[13]  M. Coffey,et al.  A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra. , 2020, Journal of dairy science.

[14]  Verônica Madeira Pacheco,et al.  Thermal imaging combined with predictive machine learning based model for the development of thermal stress level classifiers , 2020 .

[15]  Marianne Cockburn,et al.  Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms , 2020, Animals : an open access journal from MDPI.

[16]  Baoming Li,et al.  A review of measuring, assessing and mitigating heat stress in dairy cattle , 2020 .

[17]  O. Szenci,et al.  Evaluation of a commercial intravaginal thermometer to predict calving in a Hungarian Holstein-Friesian dairy farm. , 2020, Reproduction in domestic animals = Zuchthygiene.

[18]  Hanwook Chung,et al.  Using implantable biosensors and wearable scanners to monitor dairy cattle's core body temperature in real-time , 2020, Comput. Electron. Agric..

[19]  V. Ouellet,et al.  Methods for assessing heat stress in preweaned dairy calves exposed to chronic heat stress or continuous cooling. , 2020, Journal of dairy science.

[20]  A. Stone,et al.  Invited review: Physiological and behavioral effects of heat stress in dairy cows. , 2020, Journal of dairy science.

[21]  B. Dado-Senn,et al.  Carry over effects of late-gestational heat stress on dairy cattle progeny. , 2020, Theriogenology.

[22]  Sigfredo Fuentes,et al.  Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters , 2020, Sensors.

[23]  Gan Li,et al.  Predicting rectal temperature and respiration rate responses in lactating dairy cows exposed to heat stress. , 2020, Journal of dairy science.

[24]  Jianchu Xu,et al.  Will heat stress take its toll on milk production in China? , 2020, Climatic Change.

[25]  Tadayuki Yanagi Junior,et al.  ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF PHYSIOLOGICAL AND PRODUCTIVE VARIABLES OF BROILERS , 2020, Engenharia Agrícola.

[26]  M. Pastell,et al.  A generalised addictive model to characterise dairy cows' responses to heat stress. , 2020, Animal : an international journal of animal bioscience.

[27]  S. Pinto,et al.  Critical THI thresholds based on the physiological parameters of lactating dairy cows. , 2020, Journal of thermal biology.

[28]  D. Piwczyński,et al.  Forecasting the milk yield of cows on farms equipped with automatic milking system with the use of decision trees. , 2020, Animal science journal = Nihon chikusan Gakkaiho.

[29]  Daisuke Kondo,et al.  Monitoring of the core body temperature of cows using implantable wireless thermometers , 2019, Comput. Electron. Agric..

[30]  N. Cook,et al.  Thermodynamics of standing and lying behavior in lactating dairy cows in freestall and parlor holding pens during conditions of heat stress. , 2019, Journal of dairy science.

[31]  W. Heuwieser,et al.  Influence of Barn Climate, Body Postures and Milk Yield on the Respiration Rate of Dairy Cows , 2019, Annals of Animal Science.

[32]  I. Flamenbaum,et al.  Technical note: Accelerometer-based recording of heavy breathing in lactating and dry cows as an automated measure of heat load. , 2019, Journal of dairy science.

[33]  Y. Beckers,et al.  Thermotolerance indicators related to production and physiological responses to heat stress of holstein cows. , 2019, Journal of thermal biology.

[34]  L. Baumgard,et al.  Heat stress: physiology of acclimation and adaptation , 2018, Animal frontiers : the review magazine of animal agriculture.

[35]  P. Herbut,et al.  Environmental parameters to assessing of heat stress in dairy cattle—a review , 2018, International Journal of Biometeorology.

[36]  Hugo Fernando Maia Milan,et al.  Machine learning algorithms to predict core, skin, and hair-coat temperatures of piglets , 2018, Comput. Electron. Agric..

[37]  Xiaoshuai Wang,et al.  A predictive model of equivalent temperature index for dairy cattle (ETIC). , 2018, Journal of thermal biology.

[38]  J. Koltes,et al.  Automated collection of heat stress data in livestock: new technologies and opportunities , 2018, Translational animal science.

[39]  A. Saxton,et al.  Short communication: Relationships among temperature-humidity index with rectal, udder surface, and vaginal temperatures in lactating dairy cows experiencing heat stress. , 2018, Journal of dairy science.

[40]  P. Hansen,et al.  Cows exposed to heat stress during fetal life exhibit improved thermal tolerance. , 2017, Journal of animal science.

[41]  R. Sartori,et al.  Thermoregulatory responses of Holstein cows exposed to experimentally induced heat stress. , 2017, Journal of thermal biology.

[42]  S. Ammer,et al.  Is reticular temperature a useful indicator of heat stress in dairy cattle? , 2016, Journal of dairy science.

[43]  Rafael Vieira de Sousa,et al.  Development and evaluation of a fuzzy logic classifier for assessing beef cattle thermal stress using weather and physiological variables , 2016, Comput. Electron. Agric..

[44]  Jennifer M. Chen,et al.  Cooling cows efficiently with sprinklers: Physiological responses to water spray. , 2015, Journal of dairy science.

[45]  A. De Vries,et al.  Effects of season and herd milk volume on somatic cell counts of Florida dairy farms. , 2015, Journal of dairy science.

[46]  Marcos Aurélio Lopes,et al.  Models for Prediction of Physiological Responses of Holstein Dairy Cows , 2014, Appl. Artif. Intell..

[47]  R. Dunn,et al.  Analysis of heat stress in UK dairy cattle and impact on milk yields , 2014 .

[48]  R. Silva,et al.  Latent heat loss of Holstein cows in a tropical environment: a prediction model , 2008 .

[49]  T. Mader,et al.  Environmental factors influencing heat stress in feedlot cattle. , 2006, Journal of animal science.

[50]  Wayne Woldt,et al.  Evaluating Modelling Techniques for Cattle Heat Stress Prediction , 2005 .

[51]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[52]  D. Spiers,et al.  Use of physiological parameters to predict milk yield and feed intake in heat-stressed dairy cows , 2004 .

[53]  E. Maltz,et al.  Heat stress in lactating dairy cows: a review , 2002 .

[54]  L. Breiman Random Forests , 2001, Encyclopedia of Machine Learning and Data Mining.

[55]  J. Friedman Greedy function approximation: A gradient boosting machine. , 2001 .

[56]  D. Armstrong Heat stress interaction with shade and cooling. , 1994, Journal of dairy science.

[57]  P. Gemperline,et al.  A program for calculating Mahalanobis distances using principal component analysis , 1989 .

[58]  P. E. Wagner,et al.  A Dairy Cow Body Condition Scoring System and Its Relationship to Selected Production Characteristics , 1982 .

[59]  Kifle G. Gebremedhin,et al.  Ranking of environmental heat stressors for dairy cows using machine learning algorithms , 2020, Comput. Electron. Agric..

[60]  K. Janni Modeling lactating cow respiration rates during heat stress based on dry-bulb and dew-point temperatures, daily milk production and air velocity , 2019, 2019 Boston, Massachusetts July 7- July 10, 2019.

[61]  Mario R. Mondaca,et al.  Continuous Respiration Rate Measurement of Heat-Stressed Dairy Cows and Relation to Environment, Body Temperature, and Lying Time , 2018 .

[62]  Rafael Vieira de Sousa,et al.  Predictive model based on artificial neural network for assessing beef cattle thermal stress using weather and physiological variables , 2018, Comput. Electron. Agric..

[63]  P. Hansen,et al.  Is the temperature-humidity index the best indicator of heat stress in lactating dairy cows in a subtropical environment? , 2009, Journal of dairy science.

[64]  R. Eigenberg,et al.  Respiration Rate – Is It a Good Measure of Heat Stress in Cattle? , 2007 .

[65]  G. Hahn Dynamic responses of cattle to thermal heat loads. , 1999, Journal of animal science.