{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T17:08:10Z","timestamp":1789060090492,"version":"build-2803163510"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Vet. Sci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Integrated flock monitoring systems may improve reproductive decision-making by linking maternal, male, and mating records within a single digital framework. This study evaluated whether a smart flock monitoring system integrating RFID identification, automated body-weight recording, mating-marker data, estrus observation, ram breeding soundness examination, semen evaluation, and pregnancy diagnosis could support lambing-date prediction under commercial Merino flock conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The study included 210 multiparous ewes and 11 mature rams; five rams underwent detailed breeding-soundness, semen-quality, and service-capacity evaluations. Sixty ewes underwent an 11-day progesterone-sponge synchronization protocol followed by PMSG administration and were allocated to two mating-management groups. Among routinely managed ewes, 51 formed the primary lambing-date analytical dataset, while 49 with complete natural-mating and lambing records were evaluated retrospectively using the fixed 148-day prediction rule.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Estrus duration showed marked individual variability. The interval from induced estrus to subsequent estrus was 16.33\u202f\u00b1\u202f0.28\u202fdays in Group 1 and 19.95\u202f\u00b1\u202f0.17\u202fdays in Group 2 (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001), although these intervals arose under different mating-management conditions and were interpreted separately. Ram service capacity was positively correlated with 45-day pregnancy rate (rs\u202f=\u202f0.9,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.037) and negatively correlated with sperm concentration (rs\u202f=\u202f\u22120.9,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.037). Body weight and body condition score increased from pre-breeding to late gestation and declined after lambing. The mean absolute difference between estimated and observed lambing dates in the primary analytical dataset was 3.23\u202f\u00b1\u202f2.47\u202fdays. In the natural-mating comparison, mean gestation duration was 147.24\u202f\u00b1\u202f0.28\u202fdays, and the fixed 148-day rule produced a mean absolute prediction error of 1.37\u202f\u00b1\u202f0.22\u202fdays; 77.6% of lambings occurred within \u00b11\u202fday and 95.9% within \u00b12\u202fdays of the estimated date. Singleton pregnancy and maternal body weight were associated with absolute prediction error, whereas offspring sex was associated with gestation duration, although both regression models had limited explanatory power.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Integrated smart flock monitoring can generate biologically meaningful reproductive datasets and may support practical lambing-date prediction, but the regression findings require confirmation in larger independent populations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fvets.2026.1937513","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T16:25:10Z","timestamp":1789057510000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrated smart flock monitoring of reproductive parameters for lambing date prediction in merino sheep"],"prefix":"10.3389","volume":"13","author":[{"given":"Burak","family":"Y\u0131lmaz","sequence":"first","affiliation":[{"name":"Faculty of Veterinary Medicine, Department of Reproduction and Artificial Insemination, Ankara University","place":["Ankara, T\u00fcrkiye"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koray","family":"Tekin","sequence":"additional","affiliation":[{"name":"Faculty of Veterinary Medicine, Department of Reproduction and Artificial Insemination, Ankara University","place":["Ankara, T\u00fcrkiye"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1017\/S1751731113001614","article-title":"Maternal behaviour and lamb survival: from neuroendocrinology to practical application","volume":"8","author":"Dwyer","year":"2014","journal-title":"Anim"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1079\/PAVSNNR202015013","article-title":"Dystocia: factors affecting parturition in domestic animals","volume":"15","author":"Mota-Rojas","year":"2020","journal-title":"CABI Rev"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1080\/00288233.2019.1616568","article-title":"Triplet lambs and their dams\u2014a review of current knowledge and management systems","volume":"62","author":"Kenyon","year":"2019","journal-title":"N Z J Agric Res"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1017\/S1357729800051675","article-title":"Lamb production from diverse genotypes. 1. 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