# GenTORE_WP3 This project environment will contain the code of the H2020 GenTORE project (https://www.gentore.eu). ## Context GenTore aims at developing tools for monitoring and phenotyping of resilience and efficiency. WP3 specifically focuses on on-farm tools to phenotype proxies of resilience & efficiency, based on commercially available precision livestock measures such as milk meters and activity sensors. ### T3.1 - on-farm tools based on commerically available sensors ## Codes ### Calculation of Lifetime Resilience Score - **gentore_LRS_calculation.accdb**: Database with example data and weights needed to calculate LRS, as well as queries to do these calculations - **gentore_LRS_calculation.docx**: Word file with explanation of the calculations ### Sensor features - Type B - **F1_RankResilience.m**: Calculates the ranking of all animals for which the lifetime performance is available based on their resilience performance - **F2_SensorFeatures.m**: Calculates sensor features based on daily activity and daily milk production data - **F3_ActivityFeatures.m**: Calculates sensor features based on activity data only - **IsoPert.m**: detects milk yield perturbations and puts them in a table together with their characteristics - **kmo.m**: Kaiser-Meyer-Olkin Measure of Sampling Adequacy- tests a degree of common variance - **LacFeat2.m**: alternative feature calculations (milk yield) - **Pattern.m**: detects patterns in a time series - **S2_PredictFirstLactationSF.m**: prediction of the SF with the models (output = Adriaens et al. 2020) ### Core sensor features - Type A **F4_CoreSF.m**: as developed by @Wijbrand Ouweltjes ## Data A sample data set can be requested via ines.adriaens@wur.nl ## Resources [https://pubmed.ncbi.nlm.nih.gov/32475663/](url) Adriaens, I., Friggens, N., Ouweltjes, W., Scott, H., Aernouts, B., Statham, J. with Adriaens, I. (corresp. author) (2020). Productive lifespan and resilience rank can be predicted from on-farm first parity sensor time series but not using a common equation across farms. JOURNAL OF DAIRY SCIENCE, 103 (8), 7155-7171. doi: 10.3168/jds.2019-17826