Metode za ranu procjenu laktacijskog tijeka u holstein prvotelki

The aim of this research was to define methods for early prediction (based on I. milk control record) of lactation flow in Holstein heifers as well as to choose optimal one in terms of prediction fit and application simplicity. Total of 304,569 daily yield records automatically recorded on a 1,136 first lactation Holstein cows, from March 2003 till August 2008., were included in analysis. According to the test date, calving date, the age at first calving, lactation stage when I. milk control occurred and to the average milk yield in first 25th, T1 (and 25th-45th, T2) lactation days, measuring monthcalving month-age-production-time-period subgroups were formed. The parameters of analysed nonlinear and linear methods were estimated for each defined subgroup. As models evaluation measures, adjusted coefficient of determination, and average and standard deviation of error were used. Considering obtained results, in terms of total variance explanation (R2 adj), the nonlinear Wood’s method showed superiority above the linear ones (Wilmink’s, Ali-Schaeffer’s and Guo-Swalve’s method) in both time-period subgroups (T1 - 97.5 % of explained variability; T2 - 98.1 % of explained variability). Regarding the evaluation measures based on prediction error amount (eavg±eSD), the lowest average error of daily milk yield prediction (less than 0.005 kg/day), as well as of lactation milk yield prediction (less than 50 kg/lactation (T1 time-period subgroup) and less than 30 kg/lactation (T2 time-period subgroup)); were determined when Wood’s nonlinear prediction method were applied. Obtained results indicate that estimated Wood’s regression parameters could be used in routine work for early prediction of Holstein heifer’s lactation flow.Ciljevi su provedenog istraživanja bili definirati metode za ranu procjenu (temeljem podatka utvrđenog pri I. kontroli mliječnosti) laktacijskog tijeka u prvotelki holstein pasmine te izabrati optimalnu s aspekta predikcijske točnosti te aplikacijske jednostavnosti. Analizom je obuhvaćeno ukupno 304.569 zapisa dnevne količine mlijeka izmjerenih na 1136prvotelki holstein pasmine u razdoblju od ožujka 2003. do kolovoza 2008. godine. U ovisnosti o datumu mjerenja, datumu teljenja, dobi pri prvom teljenju, stadiju laktacije pri I. provedenoj kontroli mliječnosti te prosječnoj dnevnoj proizvodnji u prvih 25, T1 (te 25-45, T2) dana laktacije, kreirane su podgrupe mjesec mjerenja - mjesec teljenja - dob - proizvodnost - vremenski period. Parametri analiziranih nelinearnih i linearnih metoda procijenjeni su za svaku definiranu podgrupu. Kao mjere evaluacije korišteni su korigirani koeficijent determinacije te prosjek i standardna devijacija pogreške. Utvrđeni rezultati, s aspekta udjela pojašnjene varijabilnosti (R2 adj), ukazuju na superiornost nelinearne Woodove metode u odnosu na linearne (Wilminkova, Ali-Schaefferova, te Guo-Swalvejeva metoda) u obje podgrupe vremenskog perioda (T1 - 97,5% pojašnjene varijabilnosti; T2 - 98,1% pojašnjene varijabilnosti). Obzirom na iznos predikcijske pogreške (eavg±eSD), najmanja pogreška procjene dnevne (manje od 0,005 kg/dan), te laktacijske količine mlijeka (manje od 50 kg/laktaciji (T1 vremenski - period podgrupa), te manje od 30 kg/laktaciji (T2 vremenski - period podgrupa)); utvrđena je pri aplikaciji Woodove nelinearne metode procjene. Rezultati utvrđeni provedenim istraživanjem ukazuju na mogućnost uporabe procijenjenih Woodovih regresijskih parametara za rutinsku ranu procjenu laktacijskog tijeka u prvotelki holstein pasmine

Metode za ranu procjenu laktacijskog tijeka u holstein prvotelki

The aim of this research was to define methods for early prediction (based on I. milk control record) of lactation flow in Holstein heifers as well as to choose optimal one in terms of prediction fit and application simplicity. Total of 304,569 daily yield records automatically recorded on a 1,136 first lactation Holstein cows, from March 2003 till August 2008., were included in analysis. According to the test date, calving date, the age at first calving, lactation stage when I. milk control occurred and to the average milk yield in first 25th, T1 (and 25th-45th, T2) lactation days, measuring monthcalving month-age-production-time-period subgroups were formed. The parameters of analysed nonlinear and linear methods were estimated for each defined subgroup. As models evaluation measures, adjusted coefficient of determination, and average and standard deviation of error were used. Considering obtained results, in terms of total variance explanation (R2 adj), the nonlinear Wood’s method showed superiority above the linear ones (Wilmink’s, Ali-Schaeffer’s and Guo-Swalve’s method) in both time-period subgroups (T1 - 97.5 % of explained variability; T2 - 98.1 % of explained variability). Regarding the evaluation measures based on prediction error amount (eavg±eSD), the lowest average error of daily milk yield prediction (less than 0.005 kg/day), as well as of lactation milk yield prediction (less than 50 kg/lactation (T1 time-period subgroup) and less than 30 kg/lactation (T2 time-period subgroup)); were determined when Wood’s nonlinear prediction method were applied. Obtained results indicate that estimated Wood’s regression parameters could be used in routine work for early prediction of Holstein heifer’s lactation flow.Ciljevi su provedenog istraživanja bili definirati metode za ranu procjenu (temeljem podatka utvrđenog pri I. kontroli mliječnosti) laktacijskog tijeka u prvotelki holstein pasmine te izabrati optimalnu s aspekta predikcijske točnosti te aplikacijske jednostavnosti. Analizom je obuhvaćeno ukupno 304.569 zapisa dnevne količine mlijeka izmjerenih na 1136prvotelki holstein pasmine u razdoblju od ožujka 2003. do kolovoza 2008. godine. U ovisnosti o datumu mjerenja, datumu teljenja, dobi pri prvom teljenju, stadiju laktacije pri I. provedenoj kontroli mliječnosti te prosječnoj dnevnoj proizvodnji u prvih 25, T1 (te 25-45, T2) dana laktacije, kreirane su podgrupe mjesec mjerenja - mjesec teljenja - dob - proizvodnost - vremenski period. Parametri analiziranih nelinearnih i linearnih metoda procijenjeni su za svaku definiranu podgrupu. Kao mjere evaluacije korišteni su korigirani koeficijent determinacije te prosjek i standardna devijacija pogreške. Utvrđeni rezultati, s aspekta udjela pojašnjene varijabilnosti (R2 adj), ukazuju na superiornost nelinearne Woodove metode u odnosu na linearne (Wilminkova, Ali-Schaefferova, te Guo-Swalvejeva metoda) u obje podgrupe vremenskog perioda (T1 - 97,5% pojašnjene varijabilnosti; T2 - 98,1% pojašnjene varijabilnosti). Obzirom na iznos predikcijske pogreške (eavg±eSD), najmanja pogreška procjene dnevne (manje od 0,005 kg/dan), te laktacijske količine mlijeka (manje od 50 kg/laktaciji (T1 vremenski - period podgrupa), te manje od 30 kg/laktaciji (T2 vremenski - period podgrupa)); utvrđena je pri aplikaciji Woodove nelinearne metode procjene. Rezultati utvrđeni provedenim istraživanjem ukazuju na mogućnost uporabe procijenjenih Woodovih regresijskih parametara za rutinsku ranu procjenu laktacijskog tijeka u prvotelki holstein pasmine

BIOMASA KULTIVARA ENGLESKOG LJULJA ZASIJANIH NAKON 5 GODIŠNJEG SKLADIŠTENJA SJEMENA NA RAZLIČITIM TEMPERATURAMA

Seeds of two perennial ryegrass (Lolium perenne L.) cultivars (diploid ‘Bartwingo’ and tetraploid ‘Calibra’) were stored in hermetically sealed glass jars at four different temperatures (-80, -20, 10 and 20°C) for five years. After the storage period the seeds were sowed in containers filled with commercial substrate. Initial growth and development occurred under natural sunlight and manual watering to maintain optimum substrate moisture. After 60 days of vegetation plants were taken from the substrate, developed plants were counted, their roots were washed and whole plants were measured for shoot and root dry-weight and total biomass.Stems and leaves per plant were counted too. The research has revealed significant effects (p<0.01) of storage temperature, cultivar and their interaction to all of the investigated traits. When averaged over cultivars the highest values were observed upon storage temperature of -20°C for all the traits except root dry-weight which did not differ between -20 and -80°C. The lowest values of all investigated traits were observed upon storage at 20°C. When averaged over storage temperatures, diploid cultivar had greater number of stems and leaves and the tetraploid one had greater root dry-weight, shoot dry-weight and total biomass.Sjeme dva kultivara (diploidni \u27Bartwingo\u27 i tetraploidni \u27Calibra\u27) engleskog ljulja (Lolium perenne L.) je bilo uskladišteno u hermetički zatvorenim staklenkama na četiri različite temperature (-80, -20, 10 i 20°C) tijekom pet godina. Nakon razdoblja skladištenja sjeme je zasijano u kontejnere s komercijalnim supstratom. Početni rast i razvoj odvijali su se pod prirodnim svjetlom i uz ručno zalijevanje radi održavanja optimalne vlažnosti supstrata. Nakon 60 dana vegetacije razvijene biljke su uzete iz supstrata, prebrojene su, korijenje im je oprano i potom su im izmjerene suhe mase izdanka, korijena i cijelih biljčica. Izbrojan je i broj stabljika i listova po biljci. Istraživanje je pokazalo značajne učinke (p<0.01) temperature skladištenja, kultivara i njihovih interakcija na sva ispitivana svojstva. U prosjeku po kultivarima, najveće vrijednosti svojstava ustanovljene su nakon skladištenja na -20°C, osim za svojstvo suhe mase korijena koja se nije razlikovala između -20 i -80°C. Najniže vrijednosti svih ispitivanih svojstava ustanovljene su nakon skladištenja na 20°C. S obzirom na temperature skladištenja diploidni kultivar je u prosjeku imao veći broj stabljika i listova po biljci, a tetraploidni je imao veću suhu masu korijena, suhu masu izdanka i ukupnu biomasu

Vibration and Temperature Measurement Based Indicator of Journal Bearing Malfunction

This paper aims to present the development and implementation of the new malfunction indicator in journal bearings, based on vibrational and thermal records, called DFJB-Defect Factor Journal Bearing. Briefly, the indicator contains the specifically processed information about the bearing vibrations and temperature, on the basis of which the DFJB is calculated using fuzzy logic, and thus the state of the journal bearing may be determined. It should be pointed out that the DFJB is developed in a manner that besides the temperature and the total number of absolute vibrations, it may also integrate following parameters of monitoring: the parameters of rotating vibrations, vibrations spectrum, the thickness of oil film in the journal bearing, the intensity of the ultrasound emission of the bearing etc. These parameters may in certain cases offer more reliable malfunction identification. Experimental investigations conducted in this work, on real machine equipment and in real exploitation conditions, have shown this method to be reliable in the identification of malfunctions in journal bearings. As a result of implementation of DFJB, the time necessary to collect measuring data is significantly shortened, whereas the diagnosis procedure for journal bearings is highly simplified. This is particularly important in complex technical systems with a vast number of measuring points, which often result in the overload of the operator

Diagnostics and failure of plain bearings

Plain bearings have wide application in heavy mechanical engineering like mills, turbines, crushers, rolling mills and forging machines, presses and similar. Early detection of plain bearing failures is necessary in terms of systems maintenance and reliability as well as from the aspect of economy and protection of these production facilities. Failure and damage of plain bearings are most commonly manifested as wear, tear and plastic deformation of the material. Fracture and plastic deformation are damages related to strength, while wear, with all their manifestations, is associated with tribological processes. The research in this paper has shown that, in a reliable way, these problems can be detected at the very stage of their formation by vibration analysis and thermal analysis of bearing condition. This paper presents a part of the research done in the Laboratory for Applied Mechanics and Constructions at the Faculty of Mechanical Engineering in East Sarajevo. In this paper, the selection of plain bearing failures was performed, diagnostic models whose reliability was investigated in above mentioned Laboratory as well as on real industrial machines during their expulsion were developed

Methods for early prediction of lactation flow in Holstein heifers

The aim of this research was to define methods for early prediction (based on I. milk control record) of lactation flow in Holstein heifers as well as to choose optimal one in terms of prediction fit and application simplicity. Total of 304,569 daily yield records automatically recorded on a 1,136 first lactation Holstein cows, from March 2003 till August 2008., were included in analysis. According to the test date, calving date, the age at first calving, lactation stage when I. milk control occurred and to the average milk yield in first 25th, T1 (and 25th-45th, T2) lactation days, measuring monthcalving month-age-production-time-period subgroups were formed. The parameters of analysed nonlinear and linear methods were estimated for each defined subgroup. As models evaluation measures,adjusted coefficient of determination, and average and standard deviation of error were used. Considering obtained results, in terms of total variance explanation (R2 adj), the nonlinear Wood’s method showed superiority above the linear ones (Wilmink’s, Ali-Schaeffer’s and Guo-Swalve’s method) in both time-period subgroups (T1 - 97.5 % of explained variability; T2 - 98.1 % of explained variability). Regarding the evaluation measures based on prediction error amount (eavg±eSD), the lowest average error of daily milk yield prediction (less than 0.005 kg/day), as well as of lactation milk yield prediction (less than 50 kg/lactation (T1 time-period subgroup) and less than 30 kg/lactation (T2 time-period subgroup)); were determined when Wood’s nonlinear prediction method were applied. Obtained results indicate that estimated Wood’s regression parameters could be used in routine work for early prediction of Holstein heifer’s lactation flow

Mathematical model for temperature change of a journal bearing

In this work, a representative mathematical model has been developed, which reliably describes the heating and cooling of a journal bearing as a result of its malfunctioning, and the model has been further confirmed on a test bench. The bearing model was validated by using analytical modeling methods, i. e. the experimental results were compared to the data obtained by analytical calculations. The regression and variance analysis techniques were applied to process the recorded data, to test the mathematical model and to define mathematical functions for the heating/cooling of the journal bearing. This investigation shows that a representative model may reliably indicate the change in the thermal field, which may be a consequence of journal bearing damage

Methods for early prediction of lactation flow in Holstein heifers

The aim of this research was to define methods for early prediction (based on 1. milk control record) of lactation flow in Holstein heifers as well as to choose optimal one in terms of prediciton fit and application simplicity. Total of 304,569 daily yield records automatically recorded on a 1,136 first lactation Holstein cows, from March 2003 till August 2008., were included in analysis. According to the test date, calving date, the age at first calving, lactation stage when 1. milk control occurred and the average milk yield in first 25th, T1 (and 25th-45th, T2) lactation days, measuring month-calving month-age-production-time-period subgroup were formed. The parameters of analysed nonlinear and linear methods were estimated for each defined subgroup. As models evaluation measures, adjusted coefficient of determination, and average and standard deviation of error were used. Considering obtained results, in terms of total variance explanation (R2 adj), the nonlinear Wood\u27s method showed superiority above the linear ones (Wilmink\u27s Ali-Schaeffer\u27s and Guo-Swalve\u27s method) in both time-period subgroups (T1-97.5% of explained variabilityT2-98.1% of explained variability). Regarding the evaluation measures basedon prediciton error (eavd+-eSD), the lowest average error of daily milk yield prediction (less than 0.005 kg/day) as well as of lactation milk yield prediction (less than 50kg/lactation (T1 time-period subgroup) and less than 30 kg/lactation (T2 time group-period subgroup)): were determined when Wood\u27s nonlinear prediction method were applied. Obtained results indicate that estimated Wood\u27s regression parameters could be used in routine work for early prediction of Holstein heifer\u27s lactation flow