OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Integration of Wet-Lab Measures, Milk Infrared Spectra, and Genomics to Improve Difficult-to-Measure Traits in Dairy Cattle Populations
Alessio Cecchinato, Hugo Toledo-Alvarado, Sara Pegolo, et al.
Frontiers in Genetics (2020) Vol. 11
Open Access | Times Cited: 12
Alessio Cecchinato, Hugo Toledo-Alvarado, Sara Pegolo, et al.
Frontiers in Genetics (2020) Vol. 11
Open Access | Times Cited: 12
Showing 12 citing articles:
Invited review: A comprehensive review of visible and near-infrared spectroscopy for predicting the chemical composition of cheese
Giovanni Bittante, Nageshvar Patel, Alessio Cecchinato, et al.
Journal of Dairy Science (2022) Vol. 105, Iss. 3, pp. 1817-1836
Open Access | Times Cited: 35
Giovanni Bittante, Nageshvar Patel, Alessio Cecchinato, et al.
Journal of Dairy Science (2022) Vol. 105, Iss. 3, pp. 1817-1836
Open Access | Times Cited: 35
Evaluating the performance of machine learning methods and variable selection methods for predicting difficult-to-measure traits in Holstein dairy cattle using milk infrared spectral data
Lúcio Flávio Macêdo Mota, Sara Pegolo, Toshimi Baba, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 7, pp. 8107-8121
Open Access | Times Cited: 27
Lúcio Flávio Macêdo Mota, Sara Pegolo, Toshimi Baba, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 7, pp. 8107-8121
Open Access | Times Cited: 27
Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle
Lúcio Flávio Macêdo Mota, Vittoria Bisutti, A. Vanzin, et al.
Journal of Dairy Science (2023) Vol. 106, Iss. 3, pp. 1853-1873
Open Access | Times Cited: 10
Lúcio Flávio Macêdo Mota, Vittoria Bisutti, A. Vanzin, et al.
Journal of Dairy Science (2023) Vol. 106, Iss. 3, pp. 1853-1873
Open Access | Times Cited: 10
Milk phenomics: leveraging biological bonds with blood and infrared technologies for evaluating animal nutritional and health status
Diana Giannuzzi, Chiara Evangelista, Angela Costa, et al.
Italian Journal of Animal Science (2024) Vol. 23, Iss. 1, pp. 780-801
Open Access | Times Cited: 3
Diana Giannuzzi, Chiara Evangelista, Angela Costa, et al.
Italian Journal of Animal Science (2024) Vol. 23, Iss. 1, pp. 780-801
Open Access | Times Cited: 3
Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows
Sara Pegolo, Lúcio Flávio Macêdo Mota, Vittoria Bisutti, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 10, pp. 10934-10949
Open Access | Times Cited: 19
Sara Pegolo, Lúcio Flávio Macêdo Mota, Vittoria Bisutti, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 10, pp. 10934-10949
Open Access | Times Cited: 19
Effects of breed, farm intensiveness, and cow productivity on infrared predicted milk urea
Giovanni Bittante
Journal of Dairy Science (2022) Vol. 105, Iss. 6, pp. 5084-5096
Open Access | Times Cited: 13
Giovanni Bittante
Journal of Dairy Science (2022) Vol. 105, Iss. 6, pp. 5084-5096
Open Access | Times Cited: 13
Integrating genomic and infrared spectral data improves the prediction of milk protein composition in dairy cattle
Toshimi Baba, Sara Pegolo, Lúcio Flávio Macêdo Mota, et al.
Genetics Selection Evolution (2021) Vol. 53, Iss. 1
Open Access | Times Cited: 11
Toshimi Baba, Sara Pegolo, Lúcio Flávio Macêdo Mota, et al.
Genetics Selection Evolution (2021) Vol. 53, Iss. 1
Open Access | Times Cited: 11
Comparison of Single-Breed and Multi-Breed Training Populations for Infrared Predictions of Novel Phenotypes in Holstein Cows
Lúcio Flávio Macêdo Mota, Sara Pegolo, Toshimi Baba, et al.
Animals (2021) Vol. 11, Iss. 7, pp. 1993-1993
Open Access | Times Cited: 6
Lúcio Flávio Macêdo Mota, Sara Pegolo, Toshimi Baba, et al.
Animals (2021) Vol. 11, Iss. 7, pp. 1993-1993
Open Access | Times Cited: 6
Phenotypic and genetic variation of ultraviolet–visible-infrared spectral wavelengths of bovine meat
Giovanni Bittante, Simone Savoia, Alessio Cecchinato, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 4
Giovanni Bittante, Simone Savoia, Alessio Cecchinato, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 4
Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein
Francesco Tiezzi, A. Fleming, F. Malchiodi
Animals (2022) Vol. 12, Iss. 9, pp. 1189-1189
Open Access | Times Cited: 3
Francesco Tiezzi, A. Fleming, F. Malchiodi
Animals (2022) Vol. 12, Iss. 9, pp. 1189-1189
Open Access | Times Cited: 3
Multiple‐trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait
Francesco Tiezzi, Clint Schwab, Caleb M Shull, et al.
Journal of Animal Breeding and Genetics (2024)
Open Access
Francesco Tiezzi, Clint Schwab, Caleb M Shull, et al.
Journal of Animal Breeding and Genetics (2024)
Open Access
Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: insights for enhancing breeding programs and herd management
Alessio Cecchinato, Hugo Toledo-Alvarado, Lúcio Flávio Macêdo Mota, et al.
Journal of Dairy Science (2024)
Open Access
Alessio Cecchinato, Hugo Toledo-Alvarado, Lúcio Flávio Macêdo Mota, et al.
Journal of Dairy Science (2024)
Open Access
