Sicilo-Sarde dairy flock test-day data were analysed (1) to check predicting ability of ten milk recording procedures, based on information from a single monthly or bimonthly milking and (2) to look for the best pair of factors for predicting daily milk yield from either morning or afternoon milkings for the alternate testing method (AT). Prior to analyses, data were adjusted for variation factors with known significant effect. Number of test-day observations was 4755 from 458 lactations of 288 ewes. Losses of precision associated with simplified methods were evaluated by comparing estimated lactation yields with those observed both in a reference plan, where the two daily milkings were recorded at 2-weekly intervals and in the official A4 milk recording (monthly recording of the two daily milkings). Ranking of simplified plans based on their accuracy was still the same under either monthly or twice-monthly frequency. Estimates of lactation yields showed more lack of precision when the usual monthly designs were compared with twice-monthly sampling of both a.m. and p.m. milkings. Losses of precision ranged from 5.1%, for the A4 plan, to 14.6%. Thus, milk production should be estimated from both mikings when their measurement is economically feasible. When only one milking is weighed, designs based on-or beginning with-the a.m. milking were more accurate. There was no evidence of improvement in sampling accuracy by adjustment for milking interval or production level. For practical and economic reasons, the design alternating a.m. and p.m. milkings, without adjustment, is suggested for ovine milk recording. In such a case, new factors for estimating daily production from the measured milking (1.7, 2.3) should be used rather than the factors currently in use (2, 2) because they improved the loss of precision by more than 13% in a monthly recording system.

L’effet de l’agent conservateur (sans conservation, dichromate de potassium ou bronopol) et des conditions de transport (température ambiante et réfrigération) sur le taux cellulaire (SCC) de laits individuels de vaches a été étudié à deux reprises durant la lactation. Mille cinquante (expérience 1) et 924 (expérience 2) mesures de SCC ont été effectuées à l’aide d’un appareil Fossomatic à partir de laits individuels respectivement de 25 et de 22 vaches du même lot. Par ailleurs, chaque lait individuel a été divisé en plusieurs aliquotes et analysé à différents temps après le prélèvement (5 h, et 1, 2, 3, 4, 5 et 6 jours) pour estimer les pertes de précision associées au temps d’analyse, selon que les aliquotes sont conservées, réfrigérées ou non. Ni l’agent conservateur ni les conditions de transport n’ont eu d’effets significatifs sur le taux cellulaire pour les deux expériences qui ont différé par le niveau cellulaire dans le lait. La précision des mesures associée à chaque âge dépendait du stade de lactation, les erreurs étant de loin faibles lorsque la quantité de lait était plus abondante et le SCC était donc moins élevé. Pour des raisons pratiques, l’analyse du lait pour le SCC devrait être effectué au plus tard dans les 48 h après prélèvement.

The growth of existing customers' database made by the availability of a large volume of customer data and modern information technologies make the use of data mining tools both a necessity and an opportunity. Several research studies have drawn attention to the interest of applying knowledge discovery in data (KDD) and data mining methods to extract customer knowledge. These methods would improve the customer knowledge management (CKM) process and equip decision-makers with better knowledge about their customers to better serve them. The purpose of this paper is to show customer relationship (CRM) process steps and related objectives with appropriate data mining methods and techniques for better marketing decision making.