6 resultados para Multiple Regression
em eResearch Archive - Queensland Department of Agriculture
Resumo:
SUMMARY Seasonal conditions in the pre to post natal period and selected periods before and during wool growth were described using climatic measures and estimates of the quality and quantity of pasture on offer derived from a validated pasture production model (GRASP). The variation in greasy and clean fleece weight, yield, staple length, fibre diameter, neck and side wrinkle score of Merinos grazing Mitchell grass in north west Queensland was explained in terms of these pasture and climatic measures and animal characteristics such as reproductive status, age and skin area. Multiple regression equations predicting clean and greasy fleece weight from the proportion of days in the wool growth period that the green pool in the pasture was less than one kg/ha, the percentage utilisation of the pasture, age, reproductive status and skin area of the ewes explained 87% and 79% of the variation respectively. Equations with similar predictors explained 58-85% of the variation of the other components. The inclusion of pasture conditions in the pre to post natal period did not significantly improve the predictions of the animal’s later performance. 22nd Biennial Conference.
Resumo:
Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.
Resumo:
Batches of glasshouse-grown flowering sorghum plants were placed in circular plots for 24 h at two field sites in southeast Queensland, Australia on 38 occasions in 2003 and 2004, to trap aerial inoculum of Claviceps africana. Plants were located 20-200 m from the centre of the plots. Batches of sorghum plants with secondary conidia of C. africana on inoculated spikelets were placed at the centre of each plot on some dates as a local point source of inoculum. Plants exposed to field inoculum were returned to a glasshouse, incubated at near-100% relative humidity for 48 h and then at ambient relative humidity for another week before counting infected spikelets to estimate pathogen dispersal. Three times as many spikelets became infected when inoculum was present within 200 m of trap plants, but infected spikelets did not decline with increasing distance from local source within the 200 m. Spikelets also became infected on all 10 dates when plants were exposed without a local source of infected plants, indicating that infection can occur from conidia surviving in the atmosphere. In 2005, when trap plants were placed at 14 locations along a 280 km route, infected spikelets diminished with increasing distance from sorghum paddocks and infection was sporadic for distances over 1 km. Multiple regression analysis showed significant influence of moisture related weather variables on inoculum dispersal. Results suggest that sanitation measures can help reduce ergot severity at the local level, but sustainable management will require better understanding of long-distance dispersal of C. africana inoculum.
Using morphological traits to identify persistent lucernes for dryland agriculture in NSW, Australia
Resumo:
This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments. Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.
Resumo:
Objective To identify measures that most closely relate to hydration in healthy Brahman-cross neonatal calves that experience milk deprivation. Methods In a dry tropical environment, eight neonatal Brahman-cross calves were prevented from suckling for 2–3 days during which measurements were performed twice daily. Results Mean body water, as estimated by the mean urea space, was 74 ± 3% of body weight at full hydration. The mean decrease in hydration was 7.3 ± 1.1% per day. The rate of decrease was more than three-fold higher during the day than at night. At an ambient temperature of 39°C, the decrease in hydration averaged 1.1% hourly. Measures that were most useful in predicting the degree of hydration in both simple and multiple-regression prediction models were body weight, hindleg length, girth, ambient and oral temperatures, eyelid tenting, alertness score and plasma sodium. These parameters are different to those recommended for assessing calves with diarrhoea. Single-measure predictions had a standard error of at least 5%, which reduced to 3–4% if multiple measures were used. Conclusion We conclude that simple assessment of non-suckling Brahman-cross neonatal calves can estimate the severity of dehydration, but the estimates are imprecise. Dehydration in healthy neonatal calves that do not have access to milk can exceed 20% (>15% weight loss) in 1–3 days under tropical conditions and at this point some are unable to recover without clinical intervention.
Resumo:
Abiotic factors are fundamental drivers of the dynamics of wild marine fish populations. Identifying and quantifying their influence on species targeted by the fishing industry is difficult and very important for managing fisheries in a changing climate. Using multiple regression, we investigated the influence of both temperature and rainfall on the variability of recruitment of a tropical species, the brown tiger prawn (Penaeus esculentus), in Moreton Bay which is located near the southern limit of its distribution on the east coast of Australia. A step-wise selection between environmental variables identified that variations in recruitment from 1990 to 2014 were best explained by a combination of temperature and spawning stock biomass. Temperature explains 35% of recruitment variability and spawning stock biomass 33%. This analysis suggests that increasing temperatures have increased recruitment of brown tiger prawn in Moreton Bay.