Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study
Abstract
:1. Introduction
2. Methodology
2.1. Research Questions
- RQ1.
- What countries/regions are responsible for the largest number of publications?
- RQ2.
- What journals and conference proceedings are research publications being published in?
- RQ3.
- What problem areas are being addressed using machine learning in the dairy farming domain?
- RQ4.
- What features are being employed to develop the machine learning models?
- RQ5.
- What machine learning algorithms are being utilised to develop the models?
- RQ6.
- Which evaluation metrics and methods are used?
2.2. Databases and Search Strategy
2.3. Selection Criteria
- The publication was not related to machine learning applied to dairy farming
- The publication did not report empirical findings
- The publication was not written in English
- The publication was a duplicate study
- There was no full text available
- The publication was a review or survey study
- The publication was published before 1999
- The publication features the development of machine learning models related to dairy farming
- The publication is a primary study
2.4. Data Collection
2.5. Data Analysis
3. Results
3.1. Geographical Distribution
3.2. Publications Timeline
3.3. Publications Breakdown
3.3.1. Problem Type, Journals/Conferences and Research Area
3.3.2. Research Area, Features and Algorithms Used
3.4. Evaluation Metrics Used
3.5. Validation Methods
4. Discussion Overview
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Category | Dependent Variables (Number of Studies) | n |
---|---|---|
Animal Husbandry | Estrus Detection (7), Pregnancy Status (6), Calving Prediction (3), Cow Survival (2), Abortion Incidence (1), Calving Difficulty (1), Conception Performance (1), Conception Probability (1), Conception Success (1), Conception Rate (1), First-Service Conception Rate (1), Genomic Evaluation (1), Service Rates (1), Submission Rate (1) | 14 |
Behavior Analysis | Cow Activity (17), Cow Detection (3), Cow Identification (2), Jaw Movements (1), Sleep Stages (1) | 6 |
Feeding | Dry Matter Intake (2), Concentrate Feed Intake (1), Diet Energy Digestion (1), Feeding Behavior (1), Insufficient Herbage Allowance (1), Residual Feed Intake (1), Volatile Fatty Acids (1) | 7 |
Management | Electricity Use (6), Energy Output (3), Methane Emissions (2), Water Use (2), Diesel Use (1), Faecal Nitrogen (1), Faeces Output (1), Herbage Production (1), Manure Temperature (1), Nutrient Concentration (1), Urinary Nitrogen (1), Urine Output (1) | 12 |
Milk | Milk Production (6), Milk Adulteration (4), Milk Quality Parameters (2), Fat EBV (1), Milk Bacterial Index (1), Milk EBV (1), Milk Metabolites (1), Milk Parameters (1), Outlier Lactations (1) | 9 |
Physiology and Health | Mastitis Detection (11), Lameness Detection (10), Body Condition Score (7), Heat Stress (4), Bodyweight (2), Metabolic Status (2), Animal Dimensions (1), Digital Dermatitis (1), Ketosis Detection (1), Milk Productivity (1), Noxious Events (1), Respiration Rate (1), Rumen and Blood Metabolites (1), Skin Temperature (1), Teat Cleanliness (1), Tuberculosis Status (1), Vaginal Temperature (1) | 17 |
Appendix B
Independent Variable Category | Features (Number of Studies) | n |
---|---|---|
Calving/Pregnancy Information | Parity (24), Calving Interval (5), Previous Calving (2), AI Season (1), AI Stage (1), Calf Sex (1), Calving Age (1), Calving Month (1), Conception Rate (1), Days Since Previous AI (1), Displaced Abomasum (1), Duration of The Voluntary Waiting Period (1), Fertility EBI (1), Length of Pregnancy (1), Month of Insemination (1), Negative Energy Balance (1), No. of Heifers Calved (1), No. of Lactating Cows (1), No. of Previous Inseminations (1), Number of Cows In The Maternity Pen (1), Pregnancy Status (1), Pregnancy Stage (1), Previous Abortion (1), Previous Year’s Conception Rate (1), Reproduction Performance (1), Strategy For Using A Clean-Up Bull (1), Temperature For Thawing Semen (1) | 27 |
Cow Characteristics and Clinical Information | Bodyweight (11), Age (5), Breed (5), Genetics (5), BCS (4), Heart Rate (4), Body Temperature (3), Mastitis Detected (3), Phenotype Data (3), Breeding Values (2), Core Rumen Microbiome (2), Ketosis (2), Survival (2), Veterinary Treatments (2), Accumulated Number of Mastitis Cases (1), Back Fat Thickness (1), Bacteriological analysis (1), Blood Oxygen Saturation (1), Body Mass (1), Bodyweight Leg Distribution (1), Breathing Rate (1), Clinical Case Ratio (1), Clinical Mastitis (1), Core Temperature (1), Cytometric Fingerprint (1), EBV (1), Estrus Detected (1), Health (1), Lameness (1), Longevity (1), Medical Conditions (1), Medication (1), Metritis (1), Microrna Gene Expression Data (1), Percentage of Cows With Low BCSs (1), Previous BCS (1), Proportion of Hf Genes In Cow Genotype (1), Retained Placenta (1), Reticulorumen Temperature (1), Ruminal pH (1), Sire and Dam Fat EBV (1), Sire And Dam Milk EBV (1), Teat Sanitation (1), The Frequency of Hoof Trimming Maintenance (1), Udder Depth (1) | 45 |
Diet/Feeding | Diet Composition (3), Feed Intake (2), Programmed Concentrate Feed (2), Concentrate Feed (1), DMI (1), Drinking Duration (1), Eating Duration (1), Feed Bin Visits (1), Forage Species (1), Mean Duration of Trough Visits (1), Nutrient Management (1), Pasture Composition (1), Roughage Feed (1), Rumination Time (1), TMR Composition (1), Total Feed Intake (1), Vitamins (1), Water Bin Visits (1), Water Intake (1) | 19 |
Farm Characteristics and Management | Herd Size (9), No. of Parlour Units (7), Frequency of Hot Wash (6), Hot Water Tank Volume (6), Milk Cooling System (4), Milk Tank Volume (4), No. of Air Compressors (4), No. of Scrapers (3), Electricity Energy (2), Field Troughs (2), Flow Rate (2), Fossil Fuel Energy (2), Housing (2), Milk Pre-Cooling (2), Parlour Washing (2), Rainwater Collection (2), Air Conditioning (1), Bunk Space Per Cow (1), Facilities (1), Fan (1), Farm Management (1), Feed Energy (1), Feed Supply Energy (1), Fuel Energy (1), Grazing Management (1), Hectares (1), Herd Management (1), Human Labour Energy (1), Indoor Temperature (1), Labour (1), Labour Energy (1), Lime Management (1), Logistics Pickup (1), Machinery Energy (1), Manure Depth (1), Mechanised Feeding (1), No. of Scrapers (1), Pasture Management (1), Room Temperature (1), Stocking Rate (1), Tank Cleaning (1), Tank Level (1), Type of Bedding In The Dry Cow Pen (1), Type of Cow Restraint System (1), Water Energy (1) | 45 |
Lactation Information | DIM (19), Complete Lactation (1), Dry Period (1), Dry Period Cure Rate (1), Dry Period Length (1), Early Lactation (1), Freshening Date (1), Lactation Stage (1), Week of Lactation (1) | 9 |
Meteorological Conditions | Ambient Temperature (15), Relative Humidity (11), Rainfall (6), Wind Speed (6), Wind Direction (4), Dewpoint Temperature (3), Solar Radiation (3), Wet Bulb Temperature (3), Dry Bulb Temperature (2), Air Pressure (1), Air Temperature (1), Black Globe Temperature (1), Degree Days Below 15 C (1) | 13 |
Milk Characteristics | Milk Yield (34), Milk Fat (20), Milk Protein (19), Milk Lactose (10), SCC (10), Milk Conductivity (5), Milk MIR Spectral Data (5), Milk Temperature (5), Milk Fatty Acids (3), Milk Flow (3), 305 Day MY Equivalent (2), Milk Density (2), Milk Ph (2), Milk SNF (2), 305 Day FPCM Equivalent (1), Blood In Milk (1), Fat Corrected Milk (1), Max Fat/Protein Ratio of Previous Lactation (1), Metabolite Data (1), Milk Acetone (1), Milk Casein (1), Milk Fever (1), Milk Freezing Point (1), Milk Genetics (1), Milk Infrared Spectroscopy Data (1), Milk Mineral Content (1), Milk Persistency (1), Milk Urea (1), Non-Esterified Fatty Acids (1), Saturated Fatty Acids (1), Single Nucleotide Polymorphism Markers (1), Specific Gravity (1), Unsaturated Fatty Acids (1), Urea (1) | 34 |
Milking Parameters | Milking Frequency (4), No. of Vacuum Pumps (3), Milking Duration (2), Milking Time (2), Peak Milk Flow (2), Cups Kicked off During Milking (Yes/No) (1), Expected Milk Yield (1), No. of Clusters (1), Start/End of Milking (1) | 9 |
Other | Month Number (3), Time (2), Cow ID (1), Date (1), Day Length (1), Herd ID (1), Test Day (1), Weekday (1), Year (1) | 9 |
Sensors | Accelerometer (27), Image Data (7), Pedometer (6), Depth Image Data (4), GPS Data (4), Magnetometer Data (3), Gyroscope Data (2), Mass Spectrometry Data (2), RGB Image Data (2), Sound Data (2), 2D Image Data (1), 3D Depth Image Data (1), Audio Data (1), Differential Scanning Calorimetry (DSC) Data (1), Ear Surface Temperature (1), ECG (1), Electromyography (1), Fourier Transformed Infrared Spectroscopy (FTIR) Data (1), Locomotion Score (1), Near Infrared Reflectance (NIR) Spectrophotometer Data (1), NIR Image Data (1), Pressure Sensor (1), Radar (1), RFID Data (1), Spectroscopic Data (1), Thermal Imaging Data (1), Thermo-Hygrometric Sensor Data (1) | 27 |
Soil Characteristics | Soil Boron (1), Soil Calcium (1), Soil Characteristics (1), Soil Copper (1), Soil Iron (1), Soil Magnesium (1), Soil Manganese (1), Soil Organic Matter (1), Soil Ph (1), Soil Phosphorus (1), Soil Potassium (1), Soil Sodium (1), Soil Sulphur (1), Soil Zinc (1) | 14 |
Appendix C
Algorithm Category | Algorithms (Number of Studies) | n |
---|---|---|
Bayes | Naïve Bayes (21), Bayes net (5), Gaussian Naïve Bayes (2), Bayes-A (1), Bayesian-LASSO (1), Naïve Bayes updatable (1) | 6 |
Clustering | DBSCAN (1), k-means clustering (1) | 2 |
Meta | Bagging (5), Adaboost (4), Random Subspace (2), rotation forest (2), Boosting (1), Bootstrap Aggregation (1), Super Learner (1), Stacking (1), Voting (1) | 9 |
Neural Network | ANN (46), CNN (10), LSTM (5), Adaptive Neuro-Fuzzy Inference System (2), Faster R-CNN (2), YOLOv2 CNN (2), ANFIS (1), Bi-LSTM (1), CNN Ensemble (1), Extreme Learning Machine (1), Kernel Extreme Learning Machine (1), MLANFIS (1), Mask R-CNN (1), Neuro-Fuzzy Systems (1), Radial Basis Function Network (1), YOLOv3 CNN (1) | 16 |
Other | SVM (31), KNN (20), ANOVA (2), SMO (2), 3-dimensional surface fitting (1), Genetic Algorithm (1), Gaussian Processes (1), Kstar (1), LWL (1), multi-class SVM (1), Multivariate Adaptive Regression Spline (1), one-class SVM (1), Quick Classifier (1) | 13 |
Rule | OneR (3), Jrip (2), PART (2), Classification Based on Associations (1), Majority Voting Rule (1), ZeroR (1) | 6 |
Statistical Regression | Logistic Regression (18), Multiple Linear Regression (13), Linear Discriminant Analysis (6), PLS (6), Linear Regression (4), GAM (3), Multivariate Logistic Regression (3), Ridge Regression (2), Genomic BLUP (1), General Linear Model (1), Logistics (1), MLR with Regularization (1), Multinomial Regression (1), Penalised Linear Regression (1), PLS Discriminant Analysis (1), PLS Regression (1), Simple Logistic (1), Stochastic Gradient Descent (1) | 18 |
Tree | RF (50), DT (26), Gradient Boosting Machine (4), C4.5 (3), CART (3), XGBoost (3), Alternating DT (2), Binary Tree (2), ExtraTrees (2), Gradient Boosted DT (2), J48 (2), M5P Tree (2), Decision Stumps (1), Hoeffding (1), Logistic Model Trees (1), Parallel DT (1), Predictive Clustering Trees (1), Random Tree (1), REPTree (1), Stump DT (1) | 20 |
Appendix D
Category | Source (Number of Studies) | n |
---|---|---|
Journals | Applied Animal Behavior Science (3), Biosystems Engineering (3), International Journal of Agricultural and Biological Engineering (2), Irish Veterinary Journal (2), Science Advances (2), African Journal of Science, Technology, Innovation and Development (1), Agricultural Systems (1), Agronomy (1), Animal (1), Applied Energy (1), Applied Sciences (1), Archives Animal Breeding (1), BMC Veterinary Research (1), BioData Mining (1), Ciencia Rural (1), Computational and Mathematical Methods in Medicine (1), Food Control (1), Genetics Selection Evolution (1), Genetics and Molecular Research (1), IEEE Geoscience and Remote Sensing Letters (1), Information Processing in Agriculture (1), Journal of Energy Technology and Policy (1), Journal of Food Composition and Analysis (1), Journal of Systems Architecture (1), Livestock Science (1), Multimodal Technologies and Interaction (1), Research in Veterinary Science (1), Theriogenology (1) | 28 |
Conferences | IEEE Sensors (2), International Conference on Unmanned Systems and Artificial Intelligence (ICUSAI) (2), ABASE Annual International Meeting (1), Africa Week Conference (IST) (1), Consumer Communications and Networking Conference (CCNC) (1), European Conference on Electrical Engineering and Computer Science (EECS) (1), International Conference on Big Data Computing Service and Applications (1), International Conference on Biometrics Theory, Applications and Systems (BTAS) (1), International Conference on Computers and Their Applications (CATA) (1), International Conference on Computing for Sustainable Global Development (INDIACom) (1), International Conference on Data Mining Workshops (1), International Conference on Data and Software Engineering (ICoDSE) (1), International Conference on Intelligent Robots and Systems (IROS) (1), International Electronics Symposium (IES) (1), International Seminar on Application for Technology of Information and Communication (iSemantic) (1), International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (1), International conference on Bio Signals, Images, and Instrumentation (ICBSII) (1), Journal of Physics: Conference Series (1) | 18 |
Appendix E
Animal Husbandry | |||||
---|---|---|---|---|---|
Study | Features | Dependent | Algorithms a | Evaluation Metrics b | Evaluation Methods c |
[14] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Milk Characteristics, Sensor Data | Calving Difficulty | multinomial regression, DT, RF, ANN | Recall, Specificity, F1 Score, Accuracy | Hold-Out |
[15] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Submission Rate | DT, KNN, RF, ANN, LR | Accuracy, Balanced Accuracy, Recall, Specificity, PPV, NPV, F1 Score, Cohen’s Kappa, Prevalence, AUC, MAE | Repeated k-fold CV, Hold-Out |
[5] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Farm Characteristics and Management | First-Service Conception Rate | Alternating DT, LR | Accuracy, FP, FN | k-fold CV |
[5] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Farm Characteristics and Management, Milk Characteristics | Pregnancy Status | Alternating DT, LR | Accuracy, FP, FN | k-fold CV |
[16] | Diet/Feeding | Estrus Detection | GLM, ANN, RF | Accuracy, Recall, Specificity, PPV, NPV, Error Rate | Nested CV |
[17] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Milk Characteristics | Pregnancy Status | DT | Accuracy, Recall, Specificity, PPV, NPV | Hold-Out |
[18] | Cow Characteristics and Clinical Information | Cow Survival | Naïve Bayes, RF, LR | Accuracy, Recall, Specificity, AUC | k-fold CV, Hold-Out |
[19] | Cow Characteristics and Clinical Information, Milk Characteristics | Genomic Evaluation | Random-Boosting, Genomic BLUP, Bayesian-LASSO, Bayes-A | MSE, r | Hold-Out |
[20] | Cow Characteristics and Clinical Information, Milk Characteristics, Milking Parameters | Estrus Detection | DT, Naïve Bayes, SVM, RF, LR | Accuracy, PPV, Recall, F1 Score, Specificity | Train/Validation/Test |
[21] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information | Conception Performance | ANN, multivariate adaptive regression spline, LR | RMSE, AIC, AUC, Bayesian Information Criterion, Generalized Cross-Validation Error, Accuracy | k-fold CV, Hold-Out |
[22] | Sensor Data | Calving Prediction | LSTM, Bi-LSTM | Recall, Specificity, PPV, NPV | Hold-Out |
[23] | Calving/Pregnancy Information | Estrus Detection | Multivariate LR | Accuracy | Hold-Out |
[24] | Sensor Data | Estrus Detection | Pre-trained | Recall, Specificity, PPV, NPV, Accuracy, Error Rate | Hold-Out |
[25] | Sensor Data | Estrus Detection | K-means clustering | n/a | Hold-Out |
[26] | Cow Characteristics and Clinical Information | Cow Survival | majority voting rule, multivariate LR, RF, Naïve Bayes | PPV, Recall, Balanced Accuracy, AUC | Repeated k-fold CV, Hold-Out |
[27] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics, Other | Conception Success | C4.5 DT, Naïve Bayes, Bayesian network, LR, SVM, PLS, RF, rotation forest | AUC | Repeated k-fold CV |
[28] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics, Other | Abortion Incidence | Naïve Bayes, Bayesian network, DT, RF, OneR, PART, LR, ANN, stochastic gradient descent, bagging, boosting, rotation forest | F1 Score, AUC, PPV, MCC, Recall, Lift | Hold-Out |
[29] | Sensor Data | Estrus Detection | KNN, ANN, LDA, DT | Recall, Specificity, PPV, NPV, Accuracy, F1 Score | k-fold CV |
[30] | Sensor Data | Calving Prediction | RF, LDA, ANN | Accuracy, Recall, Specificity | LOOCV, Hold-Out |
[31] | Diet/Feeding, Farm Characteristics and Management | Conception rate | M5P Tree, ANOVA | r, RMSE | k-fold CV |
[31] | Diet/Feeding, Farm Characteristics and Management | Service Rates | M5P Tree, ANOVA | r, RMSE | k-fold CV |
[32] | Sensor Data | Estrus Detection | LSTM, CNN, KNN | Recall, Specificity, PPV | Hold-Out |
[33] | Milk Characteristics | Pregnancy Status | PLS discriminant analysis, CNN | PPV, Recall, F1 Score | k-fold CV |
[34] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Milk Characteristics | Pregnancy Status | Naïve Bayes, Bayesian networks, DT, DT ensemble, RF | AUC, FP, TP | k-fold CV |
[35] | Sensor Data | Pregnancy Status | not specified | Recall, Specificity | Hold-Out |
[36] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Pregnancy Status | GAM, LR, bagging | PPV, Recall, F1 Score, AUC | Hold-Out |
[37] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Milk Characteristics, Other | Conception Probability | GAM, LR | Recall, Specificity, Accuracy, PPV, NPV, AUC, MCC | Hold-Out |
[38] | Sensor Data | Calving Prediction | RF | MCC, AUC, Recall, Specificity | Hold-Out |
Behavior Analysis | |||||
Study | Features | Dependent | Algorithms | Evaluation Metrics | Evaluation Methods |
[39] | Sensor Data | Cow Activity | RF, Naïve Bayes, Jrip, J48 | Accuracy, FP, F1 Score, AUC | Repeated k-fold CV |
[40] | Sensor Data | Cow Activity | RF | Accuracy | k-fold CV |
[41] | Diet/Feeding, Sensor Data | Jaw Movements | DT, RF, ANN, radial basis function network, SVM, extreme learning machine | Accuracy, Recall, PPV | LOOCV |
[42] | Sensor Data | Cow Detection | YOLOv2 CNN | Accuracy | Hold-Out |
[43] | Sensor Data | Cow Activity | KNN, SVM, ANN | Accuracy, PPV, Recall, Specificity, F1 Score, Cohen’s Kappa | LOOA |
[44] | Sensor Data | Cow Activity | SVM, Naïve Bayes, KNN, RF, LR | F1 Score, Recall, PPV | Nested CV |
[45] | Cow Characteristics and Clinical Information, Sensor Data | Cow Activity | RF, LDA, ANN | Recall, Specificity, Accuracy | k-fold CV, Hold-Out |
[46] | Sensor Data | Cow Activity | Bagging, Random Subspace, AdaBoost, Binary Tree, LDA classifier, Naïve Bayes, KNN, Adaptive Neuro-Fuzzy Inference System | Accuracy, Recall, Specificity, F1 Score, FDR | Hold-Out |
[47] | Sensor Data | Cow Activity | DT, SVM | PPV, Recall, Specificity | Nested CV |
[48] | Cow Characteristics and Clinical Information, Sensor Data | Cow Activity | SVM, DT | Accuracy | Hold-Out |
[49] | Sensor Data | Cow Detection | ANN, KNN | PPV, Recall, F1 Score, Accuracy, Hamming loss | Hold-Out |
[50] | Sensor Data | Cow Activity | DT, ANN | Accuracy, Recall, Specificity | k-fold CV, Train/Validation/Test |
[51] | Sensor Data | Cow Activity | Extreme Boosting Algorithm, SVM, Adaboost, RF | Accuracy, Cohen’s Kappa, Recall, Specificity | Repeated k-fold CV |
[52] | Sensor Data | Cow Activity | Bagging, Random Subspace, AdaBoost, Binary Tree, LDA, Naïve Bayes, KNN, Adaptive Neuro-Fuzzy Inference System | Accuracy, Recall, Specificity, F1 Score, FDR | Hold-Out |
[53] | Sensor Data | Cow Detection | Faster Region CNN, k-means clustering, DBSCAN | n/a | n/a |
[54] | Sensor Data | Cow Identification | Mask R-CNN | TP, FP, FN, IoU, PPV, Recall, Averaged PPV, mAP, AR | Hold-Out |
[55] | Sensor Data | Cow Activity | KNN | PPV, Recall | Repeated Hold-Out |
[56] | Sensor Data | Cow Activity | Adaboost | Accuracy, Specificity, Recall, PPV, F1 Score, Cohen’s Kappa | k-fold CV |
[57] | Cow Characteristics and Clinical Information, Sensor Data | Sleep Stages | ANN, RF | AUC, Accuracy, F1 Score, PPV, Recall | k-fold CV |
[58] | Cow Characteristics and Clinical Information, Sensor Data | Cow Udder Anomalies | KNN, ANN, LSTM, DT | Recall, FPR | Repeated Train/Validation/Test |
[59] | Sensor Data | Cow Activity | KNN, Naïve Bayes, SVM | PPV, Recall, Accuracy | LOOA |
[60] | Sensor Data | Cow Activity | CNN, LSTM | Accuracy | Train/Validation/Test |
[61] | Sensor Data | Cow Identification | KNN, SVM, RF, DT, LR | Accuracy | Hold-Out |
[62] | Sensor Data | Cow Activity | Naïve Bayes, Bayes net, SVM, ANN, Jrip, PART, OneR, Naïve Bayes, J48, logistic model trees, meta (super learner), LR, Simple Logistic | Accuracy, Recall, Specificity, PPV, F1 Score, Training Speed | k-fold CV |
Feeding | |||||
Title | Features | Dependent | Algorithms | Evaluation Metrics | Evaluation Methods |
[63] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Meteorological Conditions, Milking Parameters | Concentrate Feed Intake | ANN | MSE | Hold-Out |
[64] | Milk Characteristics | Volatile Fatty Acids | ANN, MLR | MSPE, RMSE, RMSE % | Train/Validation/Test |
[65] | Sensor Data | Insufficient Herbage Allowance | SVM, RF, XGBoost | AUC, Recall, Specificity, Accuracy, PPV, F1 Score | LOOA |
[66] | Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Dry Matter Intake | ANN, PLS | CCC, RMSE, Mean Bias, R2 | k-fold CV, Hold-Out |
[67] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Dry Matter Intake | ANN, PLS | R2, RMSE, RPD | Repeated k-fold CV |
[68] | Diet/Feeding | Diet Energy Digestion | kernel extreme learning machine, Linear Regression, ANN, SVM, Extreme Learning Machine | MAE, MAPE, RMSE, R2, Training Speed | k-fold CV, Repeated Hold-Out |
[69] | Sensor Data | Feeding Behavior | CNN | Accuracy | Hold-Out |
[70] | Cow Characteristics and Clinical Information, Diet/Feeding, Milk Characteristics | Residual Feed Intake | SVM | MSE, r | Repeated Hold-Out |
Management | |||||
Title | Features | Dependent | Algorithms | Evaluation Metrics | Evaluation Methods |
[71] | Cow Characteristics and Clinical Information | Methane Emissions | Ridge Regression, RF | R2 | Repeated k-fold CV |
[72] | Farm Characteristics and Management, Milk Characteristics | Electricity use | SVM | RPE, CCC, MAPE, MAE, MPE, r, RMSE | Hold-Out |
[73] | Farm Characteristics and Management | Energy Output | ANN | R2, RMSE, MAPE | Train/Validation/Test |
[74] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics, Milking Parameters | Electricity use | MLR, SVM | RPE, CCC, MPE, RMSE | Hold-Out |
[75] | Calving/Pregnancy Information, Farm Characteristics and Management | Electricity use | MLR | RPE, R2 | LOOCV |
[75] | Calving/Pregnancy Information, Farm Characteristics and Management | Diesel use | MLR | RPE, R2 | LOOCV |
[76] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics, Milking Parameters | Electricity use | ANN, RF, DT, SVM, MLR | RMSE, RPE, CCC, MSPE, MPE, r | Nested CV |
[76] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics | Water use | ANN, RF, DT, SVM, MLR | RMSE, RPE, CCC, MSPE, MPE, r | Nested CV |
[77] | Farm Characteristics and Management | Energy Output | MLANFIS | R2, RMSE, MAPE | Train/Validation/Test |
[78] | Farm Characteristics and Management | Energy Output | ANFIS | R2, RMSE, MAPE | Train/Validation/Test |
[79] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics | Electricity use | MLR | R2 | Hold-Out |
[80] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics, Milking Parameters | Electricity use | MLR | RMSE, RPE, CCC, MSPE, MPE, r | k-fold CV |
[80] | Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics | Water use | MLR | RMSE, RPE, CCC, MSPE, MPE, r | k-fold CV |
[81] | Diet/Feeding | Faeces Output | SVM, ANN, LR | RMSE, norm-RMSE | Repeated k-fold |
[81] | Diet/Feeding | Urine Output | SVM, ANN, LR | RMSE, norm-RMSE | Repeated k-fold |
[81] | Diet/Feeding | Faecal Nitrogen | SVM, ANN, LR | RMSE, norm-RMSE | Repeated k-fold |
[81] | Diet/Feeding | Urinary Nitrogen | SVM, ANN, LR | RMSE, norm-RMSE | Repeated k-fold |
[82] | Meteorological Conditions, Other | Methane Emissions | SVM, RF, ensemble, gradient boosting, ridge regression, ANN, gaussian processes, MLR with regularization, MLR | RMSE, R2, MAE | Nested CV |
[83] | Farm Characteristics and Management, Meteorological Conditions, Other | Manure Temperature | gradient boosted trees, bagged tree ensembles, RF, ANN | MAE, RMSE, R2 | Train/Validation/Test |
[84] | Diet/Feeding, Farm Characteristics and Management, Meteorological Conditions, Soil Characteristics1 | Herbage Production | predictive clustering trees, RF | R2, RRMSE | k-fold CV |
[84] | Diet/Feeding, Farm Characteristics and Management, Meteorological Conditions, Soil Characteristics1 | Nutrient Concentration | predictive clustering trees, RF | R2, RRMSE | k-fold CV |
Milk | |||||
Study | Features | Dependent | Algorithms | Evaluation Metrics | Evaluation Methods |
[85] | Farm Characteristics and Management, Milk Characteristics, Milking Parameters, Other | Milk Bacterial Index | C4.5, REPTree, RF, Random Tree, Hoeffding, Decision Stumps, ANN, SVM, Logistics, SMO, LWL, Kstar, KNN, Naïve Bayes, Naïve Bayes updateable, OneR, ZeroR, Adaboost, Bagging, Stacking, Voting | MAPE | Hold-Out |
[86] | Cow Characteristics and Clinical Information, Meteorological Conditions | Milk Production | ANN | MSE | Train/Validation/Test |
[63] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Meteorological Conditions, Milking Parameters | Milk Parameters | ANN | MSE | Hold-Out |
[87] | Diet/Feeding, Farm Characteristics and Management, Soil Characteristics1 | Milk Production | CART | n/a | Tree Analysis |
[88] | Calving/Pregnancy Information, Diet/Feeding, Lactation Information, Milking Parameters | Milk Production | SVM, ANN, RF, MLR | RMSE, MAE, R2 | k-fold CV |
[89] | Calving/Pregnancy Information, Lactation Information, Milk Characteristics, Milking Parameters | Milk Quality Parameters | GAM, RF, ANN | MSE | k-fold CV |
[90] | Sensor Data | Milk Adulteration | DT, Naïve Bayes, LDA, SVM, ANN | Accuracy, Recall, Specificity, FP, FN, FPR, AUC | Train/Validation/Test |
[91] | Sensor Data | Milk Adulteration | RF, gradient boosting machine, ANN | Accuracy, Specificity, Recall | Hold-Out |
[92] | Milk Characteristics | Milk Production | DT, ANN | Accuracy | k-fold CV, Hold-Out |
[93] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Outlier Lactations | CART | Recall, Specificity, TP, FP, PPV | k-fold CV |
[94] | Milk Characteristics | Milk Metabolites | RF, PLS | r | k-fold CV |
[95] | Milk Characteristics | Milk Adulteration | ANN | r | Train/Validation/Test |
[96] | Sensor Data | Milk Quality Parameters | ANN, PLS | MSE | Train/Validation/Test |
[97] | Sensor Data | Milk Adulteration | CNN, RF, Gradient Boosting Machine, LR, Linear Regression, PLS | Accuracy, AUC | Hold-Out |
[98] | Cow Characteristics and Clinical Information, Lactation Information, Other | Milk Production | RF, ANN, MLR | CCC, r | k-fold CV, Hold-Out |
[99] | Cow Characteristics and Clinical Information, Lactation Information, Meteorological Conditions, Milk Characteristics, Other | Fat EBV | ANN, neuro-fuzzy systems | RMSE, r | Train/Validation/Test |
[99] | Cow Characteristics and Clinical Information, Lactation Information, Meteorological Conditions, Milk Characteristics, Other | Milk EBV | ANN, neuro-fuzzy systems | RMSE, r | Train/Validation/Test |
[100] | Calving/Pregnancy Information, Farm Characteristics and Management, Lactation Information, Meteorological Conditions, Milk Characteristics, Sensor Data | Milk Production | RF | RPE | k-fold CV, Hold-Out |
Physiology and Health | |||||
Study | Features | Dependent | Algorithms | Evaluation Metrics | Evaluation Methods |
[101] | Sensor Data | Animal Dimensions | MLR | R2, RMSE, MRAE | Hold-Out |
[71] | Cow Characteristics and Clinical Information | Milk Productivity | Ridge Regression, RF | R2 | Repeated k-fold CV |
[71] | Cow Characteristics and Clinical Information | Rumen and Blood Metabolites | Ridge Regression, RF | R2 | Repeated k-fold CV |
[102] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Farm Characteristics and Management, Lactation Information, Milk Characteristics | Lameness Detection | CART, gradient boosted machine, extreme gradient boosting, RF, Multivariate LR | AUC, Recall, Specificity | Repeated k-fold CV |
[103] | Sensor Data | Lameness Detection | one-class SVM | Accuracy, Specificity, Recall | LOOCV |
[104] | Sensor Data | Body Condition Score | CNN, YOLO-v3 CNN | IoU, Mean IoU, Accuracy, PPV, fps, Model Size | Hold-Out |
[105] | Sensor Data | Lameness Detection | SVM, KNN | Accuracy, TN, TP, FN, FP | Repeated Hold-Out |
[106] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Mastitis Detection | RF | Accuracy, Recall, Specificity, F1 Score, Cohen’s Kappa, PPV, NPV | Repeated k-fold CV, Hold-Out |
[107] | Sensor Data | Body Condition Score | DT, ANN, Linear Regression | MAE, R2 | k-fold CV |
[108] | Sensor Data | Body Condition Score | 3-dimensional surface fitting | MAE, MBE, R2 | Hold-Out |
[109] | Sensor Data | Body Condition Score | CNN | Accuracy, PPV, Recall, F1 Score | Hold-Out |
[110] | Cow Characteristics and Clinical Information, Diet/Feeding, Farm Characteristics and Management, Meteorological Conditions, Milk Characteristics | Heat Stress | DT | Accuracy | Hold-Out |
[111] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Milk Characteristics, Sensor Data | Ketosis Detection | Naïve Bayes | Accuracy, Recall, Specificity, PPV, Youdens Index, Cohen’s Kappa, MCC, NPV | k-fold CV |
[112] | Sensor Data | Body Condition Score | Faster R-CNN | IoU, TP, TN, FP, FN, Accuracy, PPV, Average PPV, Average PPV, fps | Hold-Out |
[113] | Cow Characteristics and Clinical Information | Mastitis Detection | SVM, RF, Naïve Bayes, ANN | Accuracy, AUC | Nested CV |
[114] | Sensor Data | Body Condition Score | CNN (pre-trained) | Accuracy, Training Speed, Model Size | Hold-Out |
[115] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Lameness Detection | ANN | Accuracy | Hold-Out |
[116] | Sensor Data | Mastitis Detection | GA, Supervised ANN, quick classifier | Cohen’s Kappa, Recall, Specificity, PPV, NPV, Accuracy | Repeated Hold-Out |
[117] | Sensor Data | Lameness Detection | multi-class SVM | Accuracy, PPV | k-fold CV |
[118] | Sensor Data | Body Condition Score | CNN, ensemble | Accuracy, PPV, Recall, F1 Score, | Hold-Out |
[119] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Bodyweight | RF | r, CCC, R2, RMSE, MAE, RPD, RPIQ | Repeated k-fold CV |
[120] | Milk Characteristics, Milking Parameters | Mastitis Detection | DT, Stump DT, Parallel DT, RF | Accuracy, Info Gain, Gini Index, Gain Ratio | k-fold CV |
[121] | Sensor Data | Digital Dermatitis | YOLOv2 architecture | Accuracy, Cohen’s Kappa | Hold-Out |
[122] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Mastitis Detection | M5P Tree, ANOVA | Accuracy | Train/Validation/Test |
[123] | Sensor Data | Lameness Detection | SVM, RF, KNN, DT | Accuracy | Hold-Out |
[124] | Cow Characteristics and Clinical Information, Farm Characteristics and Management, Milk Characteristics, Milking Parameters | Mastitis Detection | C4.5 | Accuracy | Repeated k-fold CV |
[125] | Sensor Data | Lameness Detection | RF, KNN, SVM, DT | Accuracy | Hold-Out |
[126] | Milk Characteristics | Metabolic Status | SMO, RF, alternating DT, Naïve Bayes Updatable | Accuracy, Recall, Specificity, PPV, F1 Score | LOOA |
[127] | Cow Characteristics and Clinical Information, Lactation Information, Meteorological Conditions, Milk Characteristics | Heat Stress | DT, MLR | Recall, Specificity, Balanced Accuracy, Accuracy | Hold-Out |
[128] | Cow Characteristics and Clinical Information, Lactation Information | Mastitis Detection | DT, RF, Naïve Bayes | Accuracy, Recall, Specificity, AUC | k-fold CV, Hold-Out |
[129] | Milk Characteristics | Tuberculosis Status | CNN | Accuracy, Specificity, PPV, NPV, Recall, MCC | Hold-Out |
[130] | Sensor Data | Mastitis Detection | SVM, RF, ANN, Adaboost, Naïve Bayes, LR | Recall, Specificity, Accuracy, Cohen’s Kappa | Nested CV |
[131] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics, Sensor Data | Lameness Detection | Gradient Boosted DT | Accuracy, AUC, Recall, Specificity | k-fold CV, Hold-Out |
[132] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Lactation Information, Milk Characteristics | Metabolic Status | DT, Naïve Bayes, Bayesian Network, SVM, ANN, Bootstrap Aggregation, RF, KNN | PPV, NPV, Recall, Specificity, Error Rate | Repeated k-fold CV |
[133] | Meteorological Conditions | Respiration Rate | penalized linear regression, RF, gradient boosted machines, ANN | RMSE, MAE, R2 | Train/Validation/Test |
[133] | Meteorological Conditions | Skin Temperature | penalized linear regression, RF, gradient boosted machines, ANN | RMSE, MAE, R2 | Train/Validation/Test |
[133] | Meteorological Conditions | Vaginal Temperature | penalized linear regression, RF, gradient boosted machines, ANN | RMSE, MAE, R2 | Train/Validation/Test |
[134] | Sensor Data | Teat Cleanliness | KNN | Cohen’s Kappa | k-fold CV, Hold-Out |
[135] | Milk Characteristics, Milking Parameters | Mastitis Detection | classification based on associations | Accuracy, Recall, Specificity, F1 Score, PPV, AUC | Repeated k-fold CV |
[136] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Milk Characteristics, Milking Parameters, Sensor Data | Mastitis Detection | RF, Gaussian Naïve Bayes, ExtraTrees, LR | PPV, AUC, Recall, Specificity | Repeated k-fold CV |
[136] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Milk Characteristics, Milking Parameters, Sensor Data | Lameness Detection | RF, Gaussian Naïve Bayes, ExtraTrees, LR | PPV, AUC, Recall, Specificity | Repeated k-fold CV |
[137] | Meteorological Conditions, Sensor Data | Heat Stress | ANN, Linear Regression | Mean Error, RMSE, R2 | Train/Validation/Test |
[138] | Cow Characteristics and Clinical Information, Diet/Feeding, Sensor Data | Noxious Events | RF, SVM, DT, KNN, Naïve Bayes | PPV, NPV, Accuracy | Hold-Out |
[139] | Sensor Data | Heat Stress | LSTM | MAE, RMSE | Train/Validation/Test |
[140] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Meteorological Conditions, Milk Characteristics, Milking Parameters, Other, Sensor Data | Mastitis Detection | RF, SVM, KNN, Gaussian Naïve Bayes, Extra Trees Classifier, LR | AUC, Recall, Specificity, Accuracy, PPV, F1 Score | Hold-Out |
[140] | Calving/Pregnancy Information, Cow Characteristics and Clinical Information, Diet/Feeding, Lactation Information, Meteorological Conditions, Milk Characteristics, Milking Parameters, Other, Sensor Data | Lameness Detection | RF, SVM, KNN, Gaussian Naïve Bayes, Extra Trees Classifier, LR | AUC, Recall, Specificity, Accuracy, PPV, F1 Score | Hold-Out |
[141] | Calving/Pregnancy Information, Lactation Information, Milk Characteristics | Bodyweight | PLS Regression | RMSE | k-fold CV, Hold-Out |
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Regression (n = 41) | ||||||||||
RMSE | R2 | r | MAE | CCC | MAPE | MSE | RPE | MPE | MSPE | |
% of studies | 56% | 46% | 27% | 24% | 17% | 15% | 15% | 15% | 10% | 7% |
Classification (n = 85) | ||||||||||
Accuracy | Recall | Specificity | PPV | F1 Score | AUC | NPV | Cohen’s K | FP | FN | |
% of studies | 77% | 66% | 49% | 48% | 27% | 26% | 15% | 12% | 9% | 6% |
Evaluation Method a | Hold-Out | LOOA | LOOCV | Nested CV | Train/Validation/Test | k-Fold CV |
---|---|---|---|---|---|---|
Hold-Out | 49 (5) b | - | - | - | - | - |
LOOA | - | 4 | - | - | - | - |
LOOCV | 1 | - | 3 | - | - | - |
Nested CV | - | - | - | 7 | - | - |
Train/Validation/Test | - | - | - | - | 17 (1) | - |
k-fold CV | 15 (4) | - | - | - | 1 c | 30 (11) |
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Shine, P.; Murphy, M.D. Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study. Sensors 2022, 22, 52. https://doi.org/10.3390/s22010052
Shine P, Murphy MD. Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study. Sensors. 2022; 22(1):52. https://doi.org/10.3390/s22010052
Chicago/Turabian StyleShine, Philip, and Michael D. Murphy. 2022. "Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study" Sensors 22, no. 1: 52. https://doi.org/10.3390/s22010052