Discrimination Procedure Research Articles

Differentiation of peach cultivars by image analysis based on the skin, flesh, stone and seed textures

The peaches belonging to different cultivars can be characterized by differentiation in properties. The aim of this study was to evaluate the usefulness of individual parts of fruit (skin, flesh, stone and seed) for cultivar discrimination of peaches based on textures determined using image analysis. Discriminant analysis was performed using the classifiers of Bayes net, logistic, SMO, multi-class classifier and random forest based on a set of combined textures selected from all color channels R, G, B, L, a, b, X, Y, Z and for textures selected separately for RGB, Lab and XYZ color spaces. In the case of sets of textures selected from all color channels (R, G, B, L, a, b, X, Y, Z), the accuracy of 100% was observed for flesh, stones and seeds for selected classifiers. The sets of textures selected from RGB color space produced the correctness equal to 100% in the case of flesh and seeds of peaches. In the case of Lab and XYZ color spaces, slightly lower accuracies than for RGB color space were obtained and the accuracy reaching 100% was noted only for the discrimination of seeds of peaches. The research proved the usefulness of selected texture parameters of fruit flesh, stones and seeds for successful discrimination of peach cultivars with an accuracy of 100%. The distinguishing between cultivars may be important for breeders, consumers and the peach industry for ensuring adequate processing conditions and equipment parameters. The cultivar identification of fruit by human may be characterized by large errors. The molecular or chemical methods may require special equipment or be time-consuming. The image analysis may ensure objective, rapid and relatively inexpensive procedure and high accuracy for peach cultivar discrimination.

Interactive effects of (±)-trans-U50488 and its stereoisomers with cannabinoids

The adverse effects of mu opioid agonists have spurred a renewed interest in using kappa opioid receptor (KOR) agonists as analgesics. KOR agonists also have potential for development as diuretics for the treatment of edema and hypertension. Here, we evaluated the discriminative stimulus, antinociceptive, and diuretic effects of the kappa agonist (±)-trans-U-50488 and its stereoisomers (−)-(1S,2S)-U-50488 or (+)-(1R,2R)-U-50488) alone and in combination with the cannabinoid agonist (−)-CP 55,940. To establish (±)-U-50488 as a discriminative stimulus, rats (n = 12) were trained to discriminate intraperitoneal (i.p.) administration of 5.6 mg/kg of (±)-trans-U-50488 from saline under a fixed-ratio 20 (FR-20) schedule of food reinforcement. Then, antinociception was assessed using two procedures: warm water tail withdrawal and von Frey paw withdrawal. Diuretic effects were assessed in separate rats (n = 6/group). Doses of (±)-U-50488 and (−)-U-50488 that served as discriminative stimuli produced significant increases in urine output, but at lower doses than those that produced antinociception. In contrast, (+)-U-50488 alone had no discriminative stimulus or diuretic effects at the doses tested, but did produce antinociception in the von Frey assay. When three cannabinoids and morphine were tested in the (±)-U-50488 discrimination procedure to determine the similarity of these drugs' discriminative stimulus effects to those for (±)-U-50488, the rank order similarity was (−)-CP 55,940 > (−)-trans-THC > (+)-WIN 55,212–2 ≥ morphine. (−)-CP 55,940 alone (0.056 mg/kg) partially substituted for the discriminative stimulus effects of (±)-U-50488 and produced significant diuretic and antinociceptive effects. (−)-CP 55,940 in combination with (±)-U-50488 also produced a two-fold leftward shift in the discriminative stimulus curve for (±)-U-50488, and near-additive antinociception with (±)-U-50488 and (+)-U-50488. Further, the diuretic effect of (−)-CP 55,940 was enhanced by a dose of (+)-U50488, which itself did not alter urine output. These data together indicate that a combination of cannabinoid and kappa opioid agonists can enhance diuresis, but may have limited potential for serving as opioid-sparing pharmacotherapeutics for treatment of pain.

Gabapentin attenuates somatic signs of precipitated THC withdrawal in mice

Cannabis is the most frequently used federally illicit substance in the United States. However, there are currently no FDA-approved pharmacotherapies to mitigate the withdrawal symptoms associated with cessation in heavy users. A promising, readily available, non-cannabinoid therapy are the gabapentinoids. Although currently approved for epilepsy and neuropathic pain, gabapentinoids are increasingly used for their “off-label” efficacy in treating various psychiatric conditions and substance abuse. Gabapentin (GBP) synergizes with cannabinoid agonism in neuropathic pain models, substitutes for Δ9-tetrahydrocannabinol (THC) in drug discrimination procedures, and reduced withdrawal symptoms in an outpatient clinical trial. However, there are limited data on the biological plausibility of the therapeutic action of gabapentinoids in cannabinoid withdrawal in preclinical models. The purpose of the current study was to determine the efficacy of GBP on attenuating THC withdrawal in mice, using an array of tests targeting withdrawal-induced and withdrawal-suppressed behaviors. Separate cohorts of male and female mice were administered THC (10 mg/kg, s.c.) or vehicle for 5.5 days, and withdrawal was precipitated by the CB1 antagonist rimonabant (2 or 3 mg/kg, i.p.) on the sixth day. GBP (≥10 mg/kg) reduced somatic signs of withdrawal (i.e., paw tremors and head twitches), but had no effect in locomotor activity or conditioned place preference. GBP (50 mg/kg) also restored withdrawal-suppressed responding on a progressive ratio reinforcement schedule. However, GBP (50 mg/kg) had no effect in withdrawal-suppressed marble burying or tail suspension struggling and did not normalize the stress response induced by THC withdrawal, as indicated by plasma corticosterone. These data suggest gabapentin may be effective at treating cannabinoid withdrawal symptoms including somatic and affective symptoms but may act independently of endocrine stress activation.

Portable electronic tongue based on screen-printed electrodes coupled with chemometrics for rapid differentiation of Brazilian lager beer

Quality and authenticity monitoring are activities of growing necessity worldwide. However, methods of rapid evaluation and low cost need to be further explored to intensify and optimize the monitoring process. Hence, the present study proposes a procedure for discrimination of lager beers (premium and standard American lager beers) using commercially available screen-printed electrodes (SPEs) (carbon (SPCE), gold (SPGE), and carbon nanotube (SPEs-CNT)) and chemometric classification methods (soft independent modeling of class analogy (SIMCA) and partial least squares regression discriminant analysis (PLS-DA)). Overall, PLS-DA models obtained, on average, 88% for sensitivity, specificity, and precision in the validation dataset. The SIMCA models, on the other hand, showed, on average, 72% of sensitivity, 82% specificity and 80% of precision. The electronic tongue's final configuration of an SPCE coupled with PLS-DA showed a predictive power of 94%, using only one SPCE with the capacity of analyze up to 35 beers per SPEs.

Discriminant analysis with mixed non normal variables

The mixed variable discriminant analysis procedure assumes that observations are distributed multivariate normal with different group means but same variance-covariance matrix. However, attention has not been given in discriminant analysis when the assumption of normality no longer holds. Therefore, we present a simple but new approach to mixed variable discriminant analysis when available observations (or its mixture) are not distributed multivariate normal. Specifically, a mixture of bernoulli and exponential and, poisson and bernoulli variates in discriminant analysis were presented in this work. Under a given condition, the suggested mixed non normal discriminant procedure demonstrated ability to allocate a mixture of non normal observations with minimal error.

Phase equilibrium in n-octane/water separation units: vapor pressures, vapor and liquid molar fractions

Abstract The present study reports result from research into vapor–liquid–liquid phase equilibrium for n-octane highly diluted in water and water highly diluted in n-octane blends, using a dynamic method implemented in a constant volume CREC-VL-Cell. In the CREC-VL-Cell, a very high level of mixing is achieved, allowing for dispersions to be formed in the liquid phase and good mixing in the gas phase. This VL-Cell and its auxiliary equipment provide an increasing temperature ramp in the 30–110 °C range. It is found that the CREC-VL-Cell is of special value, for studying immiscible or partially miscible blends, such as is the case of n-octane in water. With the data obtained, which includes vapor pressures and temperatures, data analyses involving mass and molar balances, allow establishing overall liquid and vapor molar fractions. The recorded vapor pressures together with the calculated liquid and vapor molar fractions offer valuable data for VL thermodynamic model discrimination. For instance, it can be shown that vapor pressures, vapor and liquid molar fractions, as calculated with the Aspen-Hysys Peng Robinson Equation of State (Hysys-Aspen PR-EoS) provide only a first approximation of the experimental data, with significant discrepancies in the prediction of an n-octane disengagement temperatures. Thus, the determination of combined measured vapor pressures and calculated overall liquid molar fractions in the CREC-VL-Cell, offers a valuable and accurate procedure for thermodynamic model validation and discrimination.

Choice between and within the classes of Poisson-Tweedie and Poisson-exponential-Tweedie count models

In both flexible Poisson Tweedie (PT) and Poisson-exponential-Tweedie (PET) over-dispersed count models, the common power parameter works as an automatic distribution selection. It mainly separates two subclasses of zero-inflated () and heavy-tailed (p > 2). Although extensive works have been conducted in discriminating between continuous and semicontinuous distribution functions, not much attention has been paid to discriminating between discrete distribution functions. Estimations based on the likelihood approach for PT and PETs are challenging owing to the presence of an infinity sum and intractable integrals in their probability mass functions. Thus, we attempt to perform a Monte Carlo simulation to approximate them. In this paper, we invest the ratio of the maximized likelihoods within each subclass of these two models for discrimination purposes based on classic measures of dispersion, zero-inflation and heavy tail of both PT and PET models. Grounded only on dispersion index, we also discriminate two particular cases of the Hermite distribution with respect to its geometric version (p = 0) and the negative binomial one with its geometric version (p = 2). Probabilities of correct selection for several combinations of dispersion parameters, means and sample sizes are examined by simulations. We carry out a numerical comparison study to assess the discrimination procedures in these subclasses of two families.

A scanner error discriminator based on short-time Fourier transform in pulse train interferometry

We propose a novel fringe-analysis approach that addresses the issue of scanner error discrimination in pulse train interferometry. Our approach exploits the fact that variations in the scan velocity of a moving mirror cause the fringes to be nonuniform. This paper describes our discrimination procedure and its development using a short-time Fourier transform (STFT)-based scheme. The STFT-based time–frequency decomposition can be used to visualize the change of the interference fringe signal with time. The details of our approach are introduced within the framework of femtosecond optical frequency comb-based interferometry for the first time. Our experimental results demonstrate the reliability of the proposed algorithm for the linear scan determination of a moving mirror.

Effects of grass- and concentrate-based finishing systems on the quality of meat from the

Context Recent heightened interest of consumers in the origins of their food, together with broader general awareness of environmental matters, has led to an increase in the demand for meat obtained from grazing systems. The importance of local breeds adapted to medium- and low-input production is fully recognised as a means of guaranteeing the sustainability of these farming methods. A finishing system based on pastures and the use of local breeds could both meet the demands of consumers and increase economic returns for Sardinian farmers. Aims The work evaluated the effects of different finishing treatments (pasture PAS-0C vs hay–concentrate-based diets HAY-C) on the quality of meat from young Sarda bulls and the usefulness of meat chemicals as markers to discriminate between finishing systems. Methods Twenty-eight young Sarda bulls were assigned randomly to the following two treatments: finished on natural pasture (PAS-0C group, n = 7), and fed on natural pasture hay ad libitum and concentrate (HAY-C group, n = 21). The latter group comprised three levels characterised by an increasing daily dose of concentrates, as follows: 2.5 kg/animal (HAY-2.5C), 3.3 kg/animal (HAY-3.3C), and ad libitum (HAY-ALC). After slaughter at a fixed age (416 ± 25 days), carcass yield, pH of the Longissimus thoracis (LT) muscle, colour parameters, cooking loss, proximate analysis, α-tocopherol and cholesterol concentration, and fatty acid composition of intramuscular fat of LT were all determined. The discriminating power of the meat chemicals between the two main finishing systems (PAS-0C vs HAY-C) and among the three groups receiving concentrates and hay (HAY-2.5C, HAY-3.3C and HAY-ALC) was assessed using linear discriminant analysis. Key results Pasture-based treatment decreased the intramuscular fat and increased the α-tocopherol concentration of meat and the proportion of some desirable fatty acids (α-linolenic acid and its derivatives eicosapentaenoic acid, docosapentaenoic acid), and improved the value of the ratio of n-6:n-3, without affecting the ultimate pH, colour parameters, and cooking loss. The discriminant procedure was able to discriminate accurately between the two main finishing systems and among the three groups receiving concentrate and hay (P < 0.0001 and P < 0.005 of the Hotelling’s T-squared test respectively). The concentration of α-tocopherol was key to the discrimination of the two main finishing systems, whereas the content of C17:0 and C18:0i were particularly effective in discriminating among the three groups fed with hay concentrate. Conclusions Grazing improves some of the meat traits of young Sarda bulls compared with the effects of a hay-concentrate-based finishing diet. The concentration of α-tocopherol in meat is an effective marker for discriminating the effects of pasture from those of a concentrate-based finishing diet Implications The results highlight the role of pasture-based diet in finishing young Sarda bulls, and could provide a wealth of knowledge for Sardinian beef farmers for delivering meat produce that stands out in the market and meets the demand of consumers more concerned about food origin and its healthiness.

Understanding the Origin of SSR in Series-Compensated DFIG-Based Wind Farms: Analysis Techniques and Tuning

This paper is dedicated to presenting control-tuning methodologies for the rotor-side converter (RSC) and grid-side converter (GSC) of series-compensated DFIG-based wind farms (WF) and to determining the origin of subsynchronous resonance (SSR). Unlike conventional approaches to re-tuning controller gains to achieve desirable performance, these methodologies only consider the mathematical models of the states variables to be controlled. A PI cascade topology is used to control the RSC and GSC. An inner loop is required for current control and an outer loop for voltage control. Special consideration is taken for tuning the RSC because this converter is coupled with the mechanical variables as mechanical rotor speed of the DFIG. Compared with standard tuning, a better system behavior during a resonance condition is achieved with the proposed tuning methodology. Regarding the analysis of the SSR origin, the modal impedance (MI) technique is used as a tool to study SSR issues; its advantages compared to the driving point impedance technique are highlighted. In this context, the small-signal-stability (SSS) analysis is performed to evaluate the overall system. With the combination of MI and SSS, the phenomena of induction generator effect, torque interaction, and torque amplification are analyzed. As a result, the modes involved in the SSR phenomenon are identified and a discrimination procedure is described to determine the origin of the SSR.

THE EMERGENCE OF COMBINATIONS OF BEHAVIOR IN AN EQUIVALENCE CLASS WITHOUT EXPLICIT TRAINING OF A FUNCTION

Three experiments using undergraduate participants examined the emergence of responding in an equivalence class despite the absence of any functions being explicitly trained to any stimulus within the class. In Experiment 1, a one-to-many conditional discrimination procedure was used to establish two three-member equivalence classes (A1, B1, C1 & A2, B2, C2) using nonsense syllables. Participants were then presented with printed versions of the stimuli inside plastic boxes alongside a box of Lego pieces and asked to respond as they felt appropriate. Results showed that Lego pieces were placed on top of the printed stimuli by four out of six participants; consistent class responding occurred for one participant. In Experiment 2, the procedure from Experiment 1 was replicated using the same participants, but this time two stimulus members (B1 & C1) were replaced by images of Blue and Green Lego pieces respectively. Responding within classes was more consistent across participants and there was some evidence of blended responding at A1. Experiment 3 replicated the procedure used in Experiment 2, this time with experimentally naive participants. Results are discussed in the context of procedures used to investigate the emergence of novel behavior.

Liquid-phase synthesis of butyl tert-butyl ether catalysed by ion-exchange resins: kinetic modelling through in-depth model discrimination

The kinetic equation and the reaction mechanism of the BTBE synthesis are obtained from an exhaustive model discrimination procedure.

The Redundancy Effect on Human Predictive Learning: Evidence against a Propositional Interpretation

The redundancy effect is the finding of greater learning when an X stimulus is trained in an A+ AX+ blocking procedure, than when a Y stimulus is trained in a BY+ CY- discrimination procedure. These findings are new and theoretically challenging for all conditioning theories that calculate learning based on a common error. For this reason, we alternatively examined the possibility that the phenomenon is the result of a propositional reasoning. In an experiment, we replicated the basic effect and we found out that the addition of instructions on the occurrence of the consequences at a submaximal level does not have a significant impact on the redundancy effect. These findings are discussed with regard to a propositional and associative approach based on the assumption that the experimental stimuli share a common feature.

Diversity of biometric and morphological traits among sheep breeds in Nigeria

Towards assessment of variations within and between sheep; biometric and morphological data of the four breeds of sheep found in Nigeria were collected using multi-stage samplin method. A total of 46 Balami, 30 Uda, 36 Yankasa and 37 WAD were sampled. Stepwise multiple regression procedure was used to find the best linear combination of metric variables that best predict the body weight. Principal component analysis of biometric and morphological traits was carried out. Simple discriminant analysis procedure was used to classify the breeds. Cluster analysis was done using the model building specificationinterface. Head length (HL), chest girth (CG), leg length (LL), and tail length were the only linear body measurements that were significant (P<0.01) in predicting body weight of sheep in the overall prediction equation. Body weight and all the linear body measurements had their highest loadings on principal component 1 (PC1). Tassel was the only variable that had its highest loading on PC2. Tail type and state (location) were the variables that bestdescribes the third component (PC3). Sex and hair type were variables that best described the forth component (PC4). Discriminant analysis showed that 70.59% of sheep sampled as Balami were classified as pure breed. Sheep sampled as WAD and Yankasa had 100% conformation while Balami and Uda had 70.59% and 60%, respectively in conformation to the classifying features of their breed based on discriminant analysis. The farthest genetic distance (5.48) was observed between Balami and WAD while the shortest genetic distance (1.26) was observed between Balami and Uda. Improvement of growth traits of sheep breedsin Nigeria is recommended through the use of either Balami or Uda as sire and either WAD or Yankasa as dam.

Multivariate statistical analysis of stable isotope signatures and element concentrations to differentiate the geographical origin of retail milk sold in Singapore

Singapore's reliance on imported foods makes the country susceptible to food fraud and food safety related incidents. To ensure authenticity of food source and indirectly food quality and safety, the development of an independent system that can trace the origin of a food is important to compliment the existing paper-based approach. A scientific approach to food traceability using isotope ratio and element concentration measurements was demonstrated using dairy milk as an example matrix. An iterative stepwise linear discriminant analysis procedure applied to the isotope ratios and element concentrations of 57 milk samples separated them into their six different country of origins. Si, Se, Li, B, Rb, Ba, P, Mn, Mo, Pb and the δ13C and δ15N of the defatted milk casein were found to be the key parameters providing maximum discrimination. The model was successfully evaluated with a blind-test, comprising of 10 samples with origins unknown to the analysts.

Development and validation of a risk model for the prediction of cardiovascular hospital admission using CMR-based phenotype in patients with known or suspected cardiovascular disease

Abstract Background Cardiovascular diseases remain the leading cause of morbidity worldwide and impose the highest economic burden among noncommunicable diseases. Much of these costs are related to hospitalizations for adverse cardiovascular events, which may be reduced by targeted management of high-risk patients. Cardiac markers derived from CMR imaging have been shown to be strong independent predictors of prognosis within specific cohorts. However, its capacity to broadly contribute to risk models aimed at predicting incident cardiac hospitalization has not been demonstrated. Purpose Using a large clinical outcomes registry of patients clinically referred for CMR, develop and validate a nomogram for prediction of cardiovascular hospital admission. Methods A total of 7127 consecutive patients were prospectively recruited between 02/2015 and 07/2019. All patients completed standardized health questionnaires and CMR imaging protocols. A nomogram was developed for prediction of cardiovascular hospitalization, inclusive of admission for heart failure, MI, cardiac arrest, heart transplant, LVAD implantation, or stroke. The risk model was derived from 80% (n=5702) of the cohort using Cox modelling that included CMR, medication, laboratory, and patient-reported health variables. Model validation was assessed by discrimination and calibration procedures applied to the remaining 20% of patients (n=1425). A minimum follow-up of six months was mandated. Results The derivation cohort was comprised of 38% females with a median age of 56 (IQR 44–65) years. During a median follow-up of 934 days, 514 (9.0%) events occurred. The validation cohort was similarly comprised of 37% females with a median age of 57 (IQR 44–66) years. During a median follow-up of 970 days, 142 (10.0%) events occurred. Numerous CMR parameters were significantly different between those experiencing versus not experiencing the primary composite outcome, including: LVEF (44% vs 59%, p<0.0001), RVEF (52% vs 55%, p<0.0001), LV mass (65g/m2 vs 56g/m2, p<0.0001), and LA volume (43mL/m2 vs 34mL/m2, p<0.0001). These and other CMR-derived characteristics were independently predictive of the composite outcome by univariate modelling (Figure 1A). An eight-variable nomogram (Figure 1B) was developed using a stepwise multivariate model that exhibited high discrimination in both the derivation and validation cohorts (C-index 0.81 and 0.83, respectively). Continuous model calibration curves indicated satisfactory external performance. The model was able to discriminate risk of hospitalization at 1-year with a dynamic range of 20–99%. Conclusion Using data available at time of CMR imaging, we derived and validated a Cox-based nomogram that offers robust prediction of future cardiovascular admissions. This tool may provide value for the identification of patients who may benefit from targeted surveillance and management strategies, and may offer a foundation for improved patient-specific cost modelling. Figure 1 Funding Acknowledgement Type of funding source: None

DISCRIMINATIVE PROCESSES INVOLVED IN REASONING: EMERGENCE OF INTRAVERBALS

Intraverbal emergence has been broadly studied. The aim of this paper was analyzing discriminative and related processes involved in that emergence. The variables and results of all known articles that demonstrated emergence were analyzed by comparing the discriminative and related procedures used by the researchers and the emergence outcomes. Discriminative processes involved in learning simple and conditional discriminations, the correlation between stimuli to establish stimulus-stimulus relations, the previous acquisition of the responses of the emergent intraverbals, the previous history with stimuli of the sort of the involved stimuli, the effect of repeating probes, the optimal sequence of teaching and probing, the negative transfer of learning a second response to the same stimulus, and the effects of symmetry were found to explain most emergence results. The lack of some of the related factors resulted in failures to obtain emergence. The successful procedures suggest techniques for promoting the emergence of intraverbals in typically developing children as well as in persons with learning difficulties or developmental delays. Because of the nature of intraverbals, most instances of emergence evidence reasoning.

The Effect of Phantom Stimulation and Pseudomonophasic Pulse Shapes on Pitch Perception by Cochlear Implant Listeners

It has been suggested that a specialized high-temporal-acuity brainstem pathway can be activated by stimulating more apically in the cochlea than is achieved by cochlear implants (CIs) when programmed with contemporary clinical settings. We performed multiple experiments to test the effect on pitch perception of phantom stimulation and asymmetric current pulses, both supposedly stimulating beyond the most apical electrode of a CI. The two stimulus types were generated using a bipolar electrode pair, composed of the most apical electrode of the array and a neighboring, more basal electrode. Experiment 1 used a pitch-ranking procedure where neural excitation was shifted apically or basally using so-called phantom stimulation. No benefit of apical phantom stimulation was found on the highest rate up to which pitch ranks increased (upper limit), nor on the slopes of the pitch-ranking function above 300 pulses per second (pps). Experiment 2 used the same procedure to study the effects of apical pseudomonophasic pulses, where the locus of excitation was manipulated by changing stimulus polarity. A benefit of apical stimulation was obtained for the slopes above 300 pps. Experiment 3 used an adaptive rate discrimination procedure and found a small but significant benefit of both types of apical stimulation. Overall, the results show some benefit for apical stimulation on temporal pitch processing at high pulse rates but reveal that the effect is smaller and more variable across listeners than suggested by previous research. The results also provide some indication that the benefit of apical stimulation may decline over time since implantation.

Successive incrementing non-matching-to-samples in rats: An automated version of the odor span task.

The odor span task is a procedure frequently used to study remembering of multiple stimuli in rodents. A large arena is used and odor stimuli are presented using scented cups. Selection of each odor is reinforced when first presented, but not on subsequent presentations; correct selections depend on remembering which stimuli were previously presented. The use of an arena setting with manual stimulus presentation makes the odor span task labor-intensive and limits experimental control; thus, an automated version of the task would be of value. The present study used an operant chamber equipped with an olfactometer and trained rats using successive conditional discrimination procedures under an incrementing non-matching-to-samples contingency. High rates of responding developed to odor stimuli when they were session-novel with low rates of responding to subsequent presentations of that odor. Additional experiments assessed variations of the procedure to determine the role of the frequency of odor presentation and the retention interval separating sample and comparison. Discrimination was impaired with long retention intervals suggesting the importance of this variable. These findings confirmed that rats differentiate between stimuli that are session-novel and those previously encountered and support the use of an automated procedure as an alternative to the odor span task.

Use of discriminant statistical procedures for an early detection of persistent lactations in dairy cows

With the development of precision dairy farming, data on individual daily milk production are easily available in many herds. The aim of the present research was to develop an algorithm able to early detect dairy cows with a potential persistent lactation using daily production data. In this study, 2295 lactations belonging to primiparous (1015) and multiparous (1280) Holstein cows from two different farms equipped with the Afimilk system were used. Based on daily milk yield at 305 days in milk (DIM), animals were grouped into three production classes: low (LC) with milk yield <20 kg, middle (MC) with milk yield between 20 kg and 32 kg, and high (HC) with milk yield >32 kg, respectively. Lactations of MC or HC were considered as suitable for becoming long lactations. Four different models (Wood, Ali & Schaeffer, Legendre polynomials and 4th degree polynomials) were fitted to individual lactations by using the first 90, 120 and 150 DIM. Estimated model parameters were considered as variables in two multivariate discriminant techniques. The canonical discriminant analysis was used to test for possible differences between the extreme classes LC and HC. The discriminant analysis was performed to assign animals to the two production classes. The canonical discriminant analysis significantly separated LC from HC both for primiparous and multiparous cows. Among the different lactation models, the 4th degree polynomial was the most precise when the discriminant analysis was used to assign animals to the two production classes. In particular, by using the data of the first 150 DIM, the percentage of LC lactations incorrectly assigned to HC was 5% for primiparous and 7% for multiparous. Errors slightly increased when data of 120 (6% and 8% for primiparous and multiparous) and 90 (7% and 12% for primiparous and multiparous) DIM were used.The entire procedure could be automated by implementing, for example, the Afifarm’s report with a statistical computer software and it could be applied at farm level or using data from different associated farms. In practice, a historical database with previous complete lactations should be firstly created. As a new lactation proceeds, the recorded milk production data are fitted by using the 4th degree polynomial model and the estimated parameters submitted to the discriminant analysis. The lactation will be assigned to LC or HC.