995 resultados para Nebraska Agricultural Statistics


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The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

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The recent discovery of the monumental 5000 years old tower tombs on top of the up to 1850 m high Shir plateau has raised numerous questions about the economic and infrastructural basis of the agro-pastoral-piscicultural society which likely has constructed them. The scattered oasis settlement of Maqta, situated just below the towers in a rugged desert environment has therefore been studied from 2001 to 2003 to understand its prehistoric and present role along the ancient trade route which connected the inner-Omani Sharqiya across the southern Hajar mountains with the ocean port of Tiwi. Maqta consists of a central area with 59 buildings and 12 scattered temporary settlements comprising a total of about 200 semi-nomadic inhabitants and next to 900 sheep and goats. The 22 small springs with a flow rate between 5 and 1212-l h^-1 are watering 16 terrace systems totaling 4.5 ha of which 2.9 ha are planted to date palms (Phoenix dactylifera L.), 0.4 ha to wheat landraces (Triticum durum and Triticum aestivum) during the cooler winter months, 0.4 are left fallow and 0.8 h are abandoned. During a pronounced drought period from 2001 to 2003, the springs’ flow rate declined between 38% and 72%. Most of the recent buildings of the central housing area were found empty or used as temporary stores by the agro-pastoral population watching their flocks on the surrounding dry mountains. There is no indication that there ever was a settlement older than the present one. A number of Hafit (3100–2700 BC) and Umm an-Nar (2700–2000 BC) tombs just above the central housing area and further along one of the trade routes to the coast are the only indication of an old pastoral landuse in Maqta territory where oasis agriculture may have entered only well after 1000 AD. With this little evidence of existence during the 3rd millennium BC, Maqta is unlikely to have played any major role favouring the construction of the nearby monumental Shir tower tombs other than providing water for herders and their flocks, early migrant traders or tower tomb constructors.

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Krishin Vigyan Kendras-KVKs (Farm Science Centres) have been established by the Indian Council of Agricultural Research in 569 districts. The trust areas of KVKs are refinement and demonstration of technologies, and training of farmers and extension functionaries. Imparting vocational trainings in agriculture and allied fields for the rural youth is one of its mandates. The study was undertaken to do a formative and summative (outcome and impact) evaluation of the beekeeping and mushroom growing vocational training programmes in the Indian state of Punjab. One-group pre and post evaluation design was employed for conducting a formative and outcome evaluation. The knowledge tests were administered to 35 beekeeping and 25 mushroom cultivation trainees, before and after the training programmes organized in 2004. The trainees significantly gained in knowledge. A separate sample of 640 trainees, trained prior to 2004, was selected for finding the adoption status. Out of 640, a sample of 200 was selected by proportionate sampling technique out of three categories, namely: non-adopters, discontinued-adopters and continued-adopters for evaluating the long-term impact of these training programmes. Ex-post-facto one-shot case study design was applied for this impact analysis. The vocational training programmes have resulted in continued-adoption of beekeeping and mushroom cultivation enterprises by 20% and 51% trained farmers, respectively. Age and trainee occupation had significant influence on the adoption decision of beekeeping vocation, whereas education and family income significantly affected the adoption decision of mushroom cultivation. The continued adopters of beekeeping and mushroom growing had increased their family income by 49% and 24%, respectively. These training programmes are augmenting the dwindling farm income of the farmers in Indian Punjab.

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Urban and peri-urban agriculture (UPA) contributes to food security, serves as an opportunity for income generation, and provides recreational services to urban citizens. With a population of 21 Million people, of which 60 % live in slums, UPA activities can play a crucial role in supporting people’s livelihoods in Mumbai Metropolitan Region (MMR). This study was conducted to characterize the railway gardens, determine their role in UPA production, and assess potential risks. It comprises a baseline survey among 38 railway gardeners across MMR characterized by different demographic, socio-economic, migratory, and labour characteristics. Soil, irrigation water, and plant samples were analyzed for nutrients, heavy metals, and microbial load. All the railway gardeners practiced agriculture as a primary source of income and cultivated seasonal vegetables such as lady’s finger (Abelmoschus esculentus L. Moench), spinach (Spinacia oleracea L.), red amaranth (Amaranthus cruentus L.), and white radish (Raphanus sativus var. longipinnatus) which were irrigated with waste water. This irrigation water was loaded with 7–28 mg N l^(−1), 0.3–7 mg P l^(−1), and 8–32 mg K l^(−1), but also contained heavy metals such as lead (0.02–0.06 mg Pb l^(−1)), cadmium (0.03–0.17 mg Cd l^(−1)), mercury (0.001–0.005 mg Hg l^(−1)), and pathogens such as Escherichia coli (1,100 most probable number per 100 ml). Levels of heavy metals exceeded the critical thresholds in surface soils (Cr, Ni, and Sr) and produce (Pb, Cd, and Sr). The railway garden production systems can substantially foster employment and reduce economic deprivation of urban poor particularly slum dwellers and migrant people. However this production system may also cause possible health risks to producers and consumers.

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Brazil has been increasing its importance in agricultural markets. The reasons are well known to be the relative abundance of land, the increasing technology used in crops, and the development of the agribusiness sector which allow for a fast response to price stimuli. The elasticity of acreage response to increases in expected return is estimated for Soybeans in a dynamic (long term) error correction model. Regarding yield patterns, a large variation in the yearly rates of growth in yield is observed, climate being probably the main source of this variation which result in ‘good’ and ‘bad’ years. In South America, special attention should be given to the El Niño and La Niña phenomena, both said to have important effects on rainfalls patterns and consequently in yield. The influence on El Niño and La Niña in historical data is examined and some ways of estimating the impact of climate on yield of Soybean and Corn markets are proposed. Possible implications of climate change may apply.

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Agriculture in the Mojanda Watershed is facing rainfall reductions caused by climate change. Reductions of water availability in the Watershed are also due to constant extension of the agricultural activities into the páramo ecosystem above 3000m a.s.l., with this ecosystem having immanently important functions in the local water balance. The application of pesticides threatens the quality of water and with less precipitation contaminations will further concentrate in the outflow. To analyze problems associated with agricultural practices in the area a questionnaire about agricultural practices (28) was conducted and fields (20) were surveyed for pests and diseases with a focus on potatoes (Solanum tuberosum L.), tree tomatoes (Solanum betaceum Cav.) and peas (Pisum sativum L.). Potatoes were infected to a low degree with Phytophthora infestans and according to the farmers the Andean potato weevil (Premnotrypes spec.) caused biggest losses. To combat the weevil the soils are disinfected with toxic Carbofuran (WHO Class 1B). Tree tomatoes showed symptoms of various fungal diseases. Most important was Fusarium solani causing the branches to rot and Anthracnosis (Colletotrichum gloeosporioides) causing the fruits to rot. Fungicide applications were correspondingly high. Peas were only minorly affected by Ascochyta blight (Mycosphaerella pinodes) and a root rot. Overall 19 active ingredients were applied of which fungicide Mancozeb (WHO class table 5) and insecticide Carbofuran (WHO Class 1B) were applied the most. Approved IPM methods are advised to reduce pesticide use. For tree tomatoes regular cutting of branches infected with F. solani and regular collection and disposal of infected fruits with Anthracnosis are advised. For potatoes plastic barriers around the fields prevent the Andean potato weevil from laying eggs thus reducing infestation with the larvae in the tubers. Local bioinsecticide “Biol” seems effective and without harm to the environment, although not used by many farmers. Organic fertilization promises to restore decreasing soil fertility, water holding capacity and reduce erosion. The here presented alternatives and strategies to reduce pesticide use pose an opportunity to preserve the water resources of the region.

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The role urban and peri-urban agriculture (UPA) plays in reducing urban poverty and ensuring environmental sustainability was recognized by the Millennium Development Goals (MGDs). India is the world’s largest democratic nation with a population of 1.2 billion. The rapid urbanization and high proportion of people below the poverty line along with higher migration to urban areas make India vulnerable to food crisis and urbanization of poverty. Ensuring jobs and food security among urban poor is a major challenge in India. The role of UPA can be well explained and understood in this context. This paper focuses on the current situation of UPA production in India with special attention to wastewater irrigation. This question is being posed about the various human health risks from wastewater irrigation which are faced by farmers and labourers, and, secondly by consumers. The possible health hazards involve microbial pathogens as well as helminth (intestinal parasites). Based on primary and secondary data, this paper attempts to confirm that UPA is one of the best options to address increasing urban food demand and can serve to complement rural supply chains and reduce ecological food prints in India. “Good practice urban and peri-urban agriculture” necessitates an integrated approach with suitable risk reduction mechanisms to improve the efficiency and safety of UPA production.

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Comparing the experiences of selected Latin America and the Caribbean countries and their trajectories over the past 15 years offers rich insights into the dynamics and causes for not meeting the 2015 MDGs. They also offer clues for post-MDG strategies. Central to achieving sustainable growth are government policies able to support small and medium-sized farms and peasants, as they are crucial for the achievement of several goals, centrally: to achieve food security; to provide a sound and stable rural environment able to resist external (financial) shocks; to secure healthy food; to secure local food; and to protect vibrant and culturally rich local communities. This paper analyses and compares the most successful government policies to the least successful policies carried out over the last 15 years in selected Latin American and Caribbean countries and based on this analysis, offers strategies for more promising post-MDG politics, able to reduce poverty, reduce inequality, fight back informality, and achieve more decent work in poor countries.

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This paper is an attempt to map the global land acquisitions with a focus on Indian MNCs in acquiring overseas land for agricultural purposes. It tries to outline the contemporary political economy of capital accumulation at the global level, especially, in the emerging developing economies like India and China, where the emergence of a new capitalist class has engaged itself into acquisition of land and control of other natural resources in Africa, Latin America, Eastern Europe and South East Asia, for example, water and other minerals to secure itself from the eventual losses of ongoing economic crisis and to earn profit from the volatile agricultural commodity markets. This sway of control of resources by the MNCs has got paramount State support under the helm of neoliberal policies. The paper provides scale of overseas land acquisitions at the current juncture and tries to highlight its causes and the major implications associated with it.

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In composite agricultural materials such as grass, tee, medicinal plants; leaves and stems have a different drying time. By this behavior, after leaving the dryer, the stems may have greater moisture content than desired, while the leaves one minor, which can cause either the appearance of fungi or the collapse of the over-dried material. Taking into account that a lot of grass is dehydrated in forced air dryers, especially rotary drum dryers, this research was developed in order to establish conditions enabling to make a separation of the components during the drying process in order to provide a homogeneous product at the end. For this, a rotary dryer consisting of three concentric cylinders and a circular sieve aligned with the more internal cylinder was proposed; so that, once material enters into the dryer in the area of the inner cylinder, stems pass through sieve to the middle and then continue towards the external cylinder, while the leaves continue by the inner cylinder. For this project, a mixture of Ryegrass and White Clover was used. The characteristics of the components of a mixture were: Drying Rate in thin layer and in rotation, Bulk density, Projected Area, Terminal velocity, weight/Area Ratio, Flux through Rotary sieve. Three drying temperatures; 40°C, 60° C and 80° C, and three rotation speeds; 10 rpm, 20 rpm and 40 rpm were evaluated. It was found that the differences in drying time are the less at 80 °C when the dryer rotates at 40 rpm. Above this speed, the material adheres to the walls of the dryer or sieve and does not flow. According to the measurements of terminal velocity of stems and leaves of the components of the mixture, the speed of the air should be less than 1.5 m s-1 in the inner drum for the leaves and less than 4.5 m s-1 in middle and outer drums for stems, in such way that only the rotational movement of the dryer moves the material and achieves a greater residence time. In other hand, the best rotary sieve separation efficiencies were achieved when the material is dry, but the results are good in all the moisture contents. The best rotary speed of sieve is within the critical rotational speed, i.e. 20 rpm. However, the rotational speed of the dryer, including the sieve in line with the inner cylinder should be 10 rpm or less in order to achieve the greatest residence times of the material inside the dryer and the best agitation through the use of lifting flights. With a finite element analysis of a dryer prototype, using an air flow allowing speeds of air already stated, I was found that the best performance occurs when, through a cover, air enters the dryer front of the Middle cylinder and when the inner cylinder is formed in its entirety through a sieve. This way, air flows in almost equal amounts by both the middle and external cylinders, while part of the air in the Middle cylinder passes through the sieve towards the inner cylinder. With this, leaves do not adhere to the sieve and flow along drier, thanks to the rotating movement of the drums and the showering caused by the lifting flights. In these conditions, the differences in drying time are reduced to 60 minutes, but the residence time is higher for the stems than for leaves, therefore the components of the mixture of grass run out of the dryer with the same desired moisture content.

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Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.

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The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Central notations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform. In this way very elaborated aspects of mathematical statistics can be understood easily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating, combination of likelihood and robust M-estimation functions are simple additions/ perturbations in A2(Pprior). Weighting observations corresponds to a weighted addition of the corresponding evidence. Likelihood based statistics for general exponential families turns out to have a particularly easy interpretation in terms of A2(P). Regular exponential families form finite dimensional linear subspaces of A2(P) and they correspond to finite dimensional subspaces formed by their posterior in the dual information space A2(Pprior). The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P. The discussion of A2(P) valued random variables, such as estimation functions or likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

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What test for your data? SPSS Statistics Coach can help

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Exercises and solutions for an introductory statistics course for MSc students. Diagrams for the questions are all together in the support.zip file, as .eps files