Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems
High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-08-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.00923/full |
| _version_ | 1828471084469452800 |
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| author | Tiago Bresolin João R. R. Dórea |
| author_facet | Tiago Bresolin João R. R. Dórea |
| author_sort | Tiago Bresolin |
| collection | DOAJ |
| description | High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality. |
| first_indexed | 2024-12-11T05:05:03Z |
| format | Article |
| id | doaj.art-965f859466da43709c192856d4750f50 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-11T05:05:03Z |
| publishDate | 2020-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-965f859466da43709c192856d4750f502022-12-22T01:20:03ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-08-011110.3389/fgene.2020.00923549366Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock SystemsTiago BresolinJoão R. R. DóreaHigh-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality.https://www.frontiersin.org/article/10.3389/fgene.2020.00923/fullbeef cattledairy cattlenear-infrarednovel phenotypesmid-infraredspectral information |
| spellingShingle | Tiago Bresolin João R. R. Dórea Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems Frontiers in Genetics beef cattle dairy cattle near-infrared novel phenotypes mid-infrared spectral information |
| title | Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems |
| title_full | Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems |
| title_fullStr | Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems |
| title_full_unstemmed | Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems |
| title_short | Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems |
| title_sort | infrared spectrometry as a high throughput phenotyping technology to predict complex traits in livestock systems |
| topic | beef cattle dairy cattle near-infrared novel phenotypes mid-infrared spectral information |
| url | https://www.frontiersin.org/article/10.3389/fgene.2020.00923/full |
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