904 resultados para Production systems and pregnancy rate
Resumo:
Ovarian follicle development continues in a wave-like manner during the bovine oestrous cycle giving rise to variation in the duration of ovulatory follicle development. The objectives of the present study were to determine whether a relationship exists between the duration of ovulatory follicle development and pregnancy rates following artificial insemination (AI) in dairy cows undergoing spontaneous oestrous cycles, and to identify factors influencing follicle turnover and pregnancy rate and the relationship between these two variables. Follicle development was monitored by daily transrectal ultrasonography from 10 days after oestrus until the subsequent oestrus in 158 lactating dairy cows. The cows were artificially inseminated following the second observed oestrus and pregnancy was diagnosed 35 days later. The predominant pattern of follicle development was two follicle waves (74.7%) with three follicle waves in 22.1% of oestrous cycles and four or more follicle waves in 3.2% of oestrous cycles. The interval from ovulatory follicle emergence to oestrus (EOI) was 3 days longer (P < 0.0001) in cows with two follicle waves than in those with three waves. Ovulatory follicles from two-wave oestrous cycles grew more slowly but were approximately 2 mm larger (P < 0.0001) on the day of oestrus. Twin ovulations were observed in 14.2% of oestrous cycles and occurred more frequently (P < 0.001) in three-wave oestrous cycles; consequently EOI was shorter in cows with twin ovulations. Overall, 57.0% of the cows were diagnosed pregnant 35 days after AI. Linear logistic regression analysis revealed an inverse relationship between EOI and the proportion of cows diagnosed pregnant, among all cows (n = 158; P < 0.01) and amongst those with single ovulations (n = 145; P < 0.05). Mean EOI was approximately I day shorter (P < 0.01) in cows that became pregnant than in non-pregnant cows; however, pregnancy rates did not differ significantly among cows with different patterns of follicle development. These findings confirm and extend previous observations in pharmacologically manipulated cattle and show, for the first time, that in dairy cows undergoing spontaneous oestrous cycles, natural variation in the duration of post-emergence ovulatory follicle development has a significant effect on pregnancy rate, presumably reflecting variation in oocyte developmental competence.
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The effect of the age of the ovulatory follicle on fertility in beef cows was investigated. Multiparous (n = 171) and primiparous (n = 129) postpartum beef cows in 2 groups (G1 and G2) received estradiol benzoate (EB; 1 mg/500 kg BW, intramuscular [i.m.]) 5.5 d (G1; n = 162) and 6.5 d (G2; n = 138) after the final GnRH of a synchronization program (5d CO-Synch + CIDR) to induce emergence of a new follicular wave (NFW), followed by prostaglandin F2 alpha (PGF2 alpha; 25 mg, i.m.) administration either 5.5 d (young follicle, YF; n = 155) or 9.5 d (mature follicle, MF; n = 145) after EB. Estrous detection coupled with AI 12 h later (estrus-AI) was performed for 60 h (MF) and 84 h (YF) after PGF(2 alpha); cows not detected in estrus within this period received timed AI (TAI) coupled with GnRH at 72 and 96 h, respectively. Within the first 72 h after PGF(2 alpha), more (P < 0.01) cows in the MF (76.3%) than YF treatment (47.7%) exhibited estrus, but through 96 h, the proportion detected in estrus (P < 0.05) and interval from PGF(2 alpha) to estrus (P < 0.01) were greater in the YF than MF treatment (88.6% vs. 76.3%, 78.9 +/- 0.8 vs. 57.5 +/- 1.6 h, respectively). Age of the ovulatory follicle at AI was greater (P < 0.01) in the MF (9.32 +/- 0.04 d) than YF (6.26 +/- 0.02 d) treatment, but follicle diameter at AI and pregnancy rates did not differ between MF (13.1 +/- 0.2 mm; 72.0%) and YF (12.9 +/- 0.1 mm; 67.1%) treatments. Regardless of treatment, the diameter of the ovulatory follicle at AI and pregnancy rate were greater (P < 0.01) with estrus-AI (13.1 +/- 0.1 mm; 75.0%) than TAI (12.6 +/- 0.2 mm; 55.4%). Cows in the MF treatment that initiated a second NFW after EB but before PGF(2 alpha) (MF2; n = 47) were induced to ovulate with GnRH and TAI at 72h, when ovulatory follicles were 4 d old and 10.2 +/- 0.2 mm in diameter. Pregnancy rate for TAI (51.1%) in MF2 did not differ from TAI pregnancy rate (55.4%) across the MF and YF treatments. In summary, the age of the ovulatory follicle affected interval to estrus and AI but did not influence pregnancy rate in suckled beef cows.
Resumo:
Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70–80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.
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This article presents a two-stage analytical framework that integrates ecological crop (animal) growth and economic frontier production models to analyse the productive efficiency of crop (animal) production systems. The ecological crop (animal) growth model estimates "potential" output levels given the genetic characteristics of crops (animals) and the physical conditions of locations where the crops (animals) are grown (reared). The economic frontier production model estimates "best practice" production levels, taking into account economic, institutional and social factors that cause farm and spatial heterogeneity. In the first stage, both ecological crop growth and economic frontier production models are estimated to calculate three measures of productive efficiency: (1) technical efficiency, as the ratio of actual to "best practice" output levels; (2) agronomic efficiency, as the ratio of actual to "potential" output levels; and (3) agro-economic efficiency, as the ratio of "best practice" to "potential" output levels. Also in the first stage, the economic frontier production model identifies factors that determine technical efficiency. In the second stage, agro-economic efficiency is analysed econometrically in relation to economic, institutional and social factors that cause farm and spatial heterogeneity. The proposed framework has several important advantages in comparison with existing proposals. Firstly, it allows the systematic incorporation of all physical, economic, institutional and social factors that cause farm and spatial heterogeneity in analysing the productive performance of crop and animal production systems. Secondly, the location-specific physical factors are not modelled symmetrically as other economic inputs of production. Thirdly, climate change and technological advancements in crop and animal sciences can be modelled in a "forward-looking" manner. Fourthly, knowledge in agronomy and data from experimental studies can be utilised for socio-economic policy analysis. The proposed framework can be easily applied in empirical studies due to the current availability of ecological crop (animal) growth models, farm or secondary data, and econometric software packages. The article highlights several directions of empirical studies that researchers may pursue in the future.
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Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.
Resumo:
Fruit size and quality are major problems in early-season stonefruit cultivars grown in Australia and South-East Asia. In Australia, Thailand and Vietnam, new training and trellising systems are being developed to improve yield and fruit quality. Australian trials found that new training systems, such as the Open Tatura system, are more productive compared with standard vase-trained trees. We established new crop-loading indices for low-chill stonefruit to provide a guide for optimum fruit thinning based on fruit number per canopy surface and butt cross sectional area. Best management practices were developed for low-chill stonefruit cultivation using growth retardants, optimizing leaf nitrogen concentrations and controlling rates and timing of irrigation. Regulated deficit irrigation (RDI) improved fruit sugar concentrations by restricting water application during stage II of fruit growth. New pest and disease control measures are also being developed using a new generation of fruit fly baits. Soft insecticides such as (Spinosad) are used at significantly lower concentrations and have lower mammalian toxicity than the organophosphates currently registered in Australia. In addition, fruit fly exclusion netting effectively eliminated fruit fly and many other insect pests from the orchard with no increase in diseases. This netting system increased sugar concentrations of peach and nectarine by as much as 30%. Economic analyses showed that the break-even point can be reduced from 12 to 6 years Open Tatura trellising and exclusion netting.
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The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.
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Numerical control (NC) for contouring operations requires precise control of position and feed rate for approximating the contour by linear moves of the cutter. A control scheme, for generating linear moves with desired slopes for the cutter, is described. This scheme provides for nine successive linear moves, and may be either expanded or implemented in succession, for approximating a contour.
Resumo:
An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.
Resumo:
A brief review of most of the publications by the author and other relevant workers on the three water-based fish culture systems was made. The present status of the culture systems in the National Food/Fish Programmes was highlighted. Strategies were advanced towards a successful implementation of the intensive water-based culture systems project as a contribution towards alleviating poverty, hunger and malnutrition under the concept of VISION 2010