A. Stone

发表

Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows.

W. J. Silvia, W. Silvia, L. M. Mayo, 2019, Journal of dairy science.

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

B. A. Wadsworth, J M Bewley, A. Stone, 2017, Journal of dairy science.

Predicting dairy cattle heat stress using machine learning techniques.

M. Marufuzzaman, A. Stone, C. Becker, 2020, Journal of dairy science.

Precision dairy monitoring technologies use in disease detection: Differences in behavioral and physiological variables measured with precision dairy monitoring technologies between cows with or without metritis, hyperketonemia, and hypocalcemia

S. Janse, L. M. Mayo, B. Jones, 2020 .

Precision Dairy Farming Technology Solutions for Detecting Dairy Cow Disease to Improve Dairy Cow Well-Being

A. Stone, 2017 .

Case Study: Characterization of milk yield, lying and rumination behavior, gait, cleanliness, and lesions between 2 different freestall bases

D. Ray, B. Jones, A. Stone, 2017 .

Influence of breed, milk yield, and temperature-humidity index on dairy cow lying time, neck activity, reticulorumen temperature, and rumination behavior.

B. Jones, A. Stone, J. Bewley, 2017, Journal of dairy science.

Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies.

B. A. Wadsworth, W. J. Silvia, J M Bewley, 2015, Journal of dairy science.

Comparing dairy farm milk yield and components, somatic cell score, and reproductive performance among United States regions using summer to winter ratios.

A. Stone, P. Krawczel, G. Pighetti, 2019, Journal of dairy science.

Short communication: Measuring feed volume and weight by machine vision.

J M Bewley, D. Lau, A. Stone, 2016, Journal of dairy science.

Graduate Student Literature Review: Heat abatement strategies used to reduce negative effects of heat stress in dairy cows.

A. Stone, C. Becker, 2020, Journal of dairy science.

Symposium review: The most important factors affecting adoption of precision dairy monitoring technologies.

A. Stone, 2020, Journal of dairy science.

Aiming for the optimum: examining complex relationships among sampling regime, sampling density and landscape complexity to accurately model resource availability

Garrett M. Street, B. B. Karisch, Stephen L. Webb, 2021, Landscape Ecology.

Effect of alley-floor scraping frequency on Escherichia coli, Klebsiella species, environmental Streptococcus species, and coliform counts

A. Stone, J. D. Clark, J. Bewley, 2015 .

Stall cleanliness and stall temperature of two different freestall bases.

B. A. Wadsworth, D. Ray, A. Stone, 2015, Journal of dairy science.

Evaluation of production parameters and health of dairy cows treated with pegbovigrastim in the transition period.

A. Stone, J. Larson, M. X. S. Oliveira, 2020, Preventive veterinary medicine.

Invited review: Physiological and behavioral effects of heat stress in dairy cows.

A. Stone, R. Collier, C. Becker, 2020, Journal of dairy science.

Rotational Cropping Systems to Reduce Cheat (Bromus secalinus) Densities1

A. Stone, J. C. Stone, T. Peeper, 2006, Weed Technology.

Italian Ryegrass (Lolium Multiflorum) Management Options in Winter Wheat in Oklahoma

A. Stone, T. Peeper, Chad S. Trusler, 2007, Weed Technology.

Italian Ryegrass (Lolium perenne), Feral Cereal Rye (Secale cereale), and Volunteer Wheat (Triticum aestivum) Control in Winter Canola

A. Stone, J. Bushong, M. Boyles, 2011, Weed Technology.

Characterizing jointed goatgrass (Aegilops cylindrica) × winter wheat hybrids in Oklahoma

A. Stone, T. Peeper, 2004, Weed Science.

Automated walk-over-weigh system to track daily body mass and growth in grazing steers

Garrett M. Street, Stephen L. Webb, A. Stone, 2023, Computers and Electronics in Agriculture.

Variation in Characteristics and Imazamox Tolerance of Feral Rye

A. Stone, T. Peeper, Johnnie R. Roberts, 2008 .

0064 Identification of lameness using lying time, rumination time, neck activity, reticulorumen temperature, and milk yield.

B. A. Wadsworth, A. Stone, J. D. Clark, 2016 .