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Zhen, Chen. "Celestial satellite and earthly crop yield: informational content of satellite-based crop yield forecasts." Thesis, Montana State University, 2001. http://etd.lib.montana.edu/etd/2001/zhen/ZhenC2001.pdf.
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Since the late 70s, burgeoning efforts have been allocated to study the potential of monitoring crop conditions and forecasting crop yields via remote sensing from the satellite. An overwhelming majority of these studies shows that remote sensing from the satellite express high predictive power in crop forecasting. In this thesis, using satellite images to forecast wheat yield from 1989 to 2000 in six Montana Crop Reporting Districts (CRD), several statistical improvements were achieved over extant crop forecasting models. First, different weights were allowed for satellite images obtained at different points of time, accounting for the likely heterogeneous contributions of various crop phenological stages to the final crop yield. Second, crop acreage information was directly modeled. This, to some extent, alleviates the low-resolution problem of existing satellite imagery. Third, jackknife out-of-sample forecasts were generated to formally measure the well-known instability problem of using satellite imagery in crop forecasting across seasons. In addition, the satellite-based crop yield forecasts were compared with those of the U.S. Department of Agriculture (USDA), whose forecasts were based on traditional methods. It is shown that although meaningful crop forecasts can be generated from the satellite imagery late season, the additional yield information that can be extracted from the satellite tends to be limited. Because in the major wheat producing CRDs, the USDA forecasts are already very accurate and little independent information is observed in the satellite-based forecasts. Results suggest the needs to pinpoint crop phenological stages and to calibrate region-specific crop forecasting model.
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Husaker, Douglas, and Dale Bucks. "Crop Yield Variability in Irrigated Wheat." College of Agriculture, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/200484.
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Optimum design and management of irrigated wheat production is limited by the scarcity of information available on yield variability. The purpose of this study was to evaluate the spatial variability in soil-water parameters and the effects compared to grain yield response under level-basin irrigation. Three levels of seasonal irrigation water and two border lengths were used. Grain yields were found to increase significantly with the amount of water applied and soil water depletion (estimate of crop evapotranspiration), although yield variability was greater with reduced or deficit irrigations. Variations in soil water content were responsible for about 22% of the variability in grain yield, indicating that other soil and crop- related factors had a significant influence on production. Spatial dependence was exhibited over a greater distance at the wetter compared with the drier irrigation regimes.
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Ramirez, Almeyda Jacqueline <1985>. "Lignocellulosic Crops in Europe: Integrating Crop Yield Potentials with Land Potentials." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amsdottorato.unibo.it/7854/1/Tesi_J.Ramirez_2017_Lignocellulosic%20crops%20potentials%20in%20EU.pdf.
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Given the ambitious EU targets to further decarbonise the economy, it can be expected that the demand for lignocellulosic biomass will continue to grow. Provisioning of part of this biomass by dedicated biomass crops becomes an option. This study presents integrated approach for crop allocation based on land availability and crop requirements. The model analysis to investigate the potential extension of unused land and its suitability for lignocellulosic crops was carried out in 37 European countries at the NUTS3 level. The CAPRI model predicts future land use changes and was used as a basic input to assess the agricultural biomass potentials in Europe. It was then identified the total land resource with a post-modeling assessment for three different potentials to the year 2020 and 2030, according to sustainability criteria formulated in the Renewable Energy directive (RED). Furthermore, crop-specific suitability maps were generated for each crop based on the variability of biophysical factors such as climate, soil properties and topographical aspects. The yields and cost levels that can be reached in Europe with different perennial crops in different climatic, soil and management situations. The AquaCrop model developed by FAO was used and fed with phenological parameters per crop and detailed weather data to simulate the crop growth in all European Nuts 3 regions. Yield levels were simulated for a maximum and a water-limited yield situation and further converted to match with low, medium and high input management systems. The costs production was assessed with an Activity Based Costing (ABC) model, developed to assess the roadside Net Present Value (NPV) cost of biomass. The yield, crop suitability and cost simulation results were then combined to identify the best performing crop-management mix per region.
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Chouinard, Hayley Helene. "Reduction of yield variance through crop insurance." Thesis, Montana State University, 1994. http://etd.lib.montana.edu/etd/1994/chouinard/ChouinardH1994.pdf.
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The variance of a producer's yield provides uncertainty and may be considered the risk a producer faces. crop insurance may provide protection against yield variability. If yields are necessarily low, an insured producer may receive an indemnity payment. Currently, crop insurance is based on each individual's yield. If the individual's yield falls below a specified level, the individual will receive an indemnity. An alternative crop insurance program bases indemnities on . an area yield. If the yield of the predetermined area falls below a specific level, all insured producers will receive an indemnity. This thesis examines the yield variability reduction received by purchasing various forms of area yield and individual yield crop insurance and the actuarially fair premium costs associated with them. When a producer purchases insurance two decisions are made. First, the producer selects a trigger level which determines the critical yield which generates an indemnity payment. Second, the producer may be able to select a coverage level which is the amount of acreage covered by the contract. Each contract examined allows different levels for the trigger and coverage levels. The variance reduction provided from each contract is the variance of the yield without insurance less the variance of the yield with an insurance contract. The results indicate most producers receive some variance reduction from the area yield contracts. And, producers who have yields which are closely correlated with the area yield receive more variance reduction from the area yield insurance than from the individual yield insurance contracts. However, the area yield contracts which provide on average more yield variance reduction than the individual yield contracts, also have much higher actuarially fair premium costs. The area yield insurance contracts should be considered as an alternative to individual yield insurance, but the premium costs must be evaluated also.
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Kreps, Tyler Leigh Hite Diane. "Crop yield response to drought in Alabama." Auburn, Ala, 2009. http://hdl.handle.net/10415/1880.
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Gayam, Narsi Reddy. "Risk in agriculture : a study of crop yield distributions and crop insurance." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35537.
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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006.<br>Includes bibliographical references (leaves 52-53).<br>Agriculture is a business fraught with risk. Crop production depends on climatic, geographical, biological, political, and economic factors, which introduce risks that are quantifiable given the appropriate mathematical and statistical methodologies. Accurate information about the nature of historical crop yields is an important modeling input that helps farmers, agribusinesses, and governmental bodies in managing risk and establishing the proper policies for such things as crop insurance. Explicitly or implicitly, nearly all farm decisions relate in some way to the expectation of crop yield. Historically, crop yields are assumed to be normally distributed for a statistical population and for a sample within a crop year. This thesis examines the assumption of normality of crop yields using data collected from India involving sugarcane and soybeans. The null hypothesis (crop yields are normally distributed) was tested using the Lilliefors method combined with intensive qualitative analysis of the data. Results show that in all cases considered in this thesis, crop yields are not normally distributed.<br>(cont.) This result has important implications for managing risk involving sugarcane and soybeans grown in India. The last section of this thesis examines the impact of crop yield non normality on various insurance programs, which typically assume that all crop yields are normally distributed and that the probability of crop failure can be calculated given available data.<br>by Narsi Reddy Gayam.<br>M.Eng.in Logistics
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Assefa, Yared. "Time series and spatial analysis of crop yield." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/15142.
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Master of Science<br>Department of Statistics<br>Juan Du<br>Space and time are often vital components of research data sets. Accounting for and utilizing the space and time information in statistical models become beneficial when the response variable in question is proved to have a space and time dependence. This work focuses on the modeling and analysis of crop yield over space and time. Specifically, two different yield data sets were used. The first yield and environmental data set was collected across selected counties in Kansas from yield performance tests conducted for multiple years. The second yield data set was a survey data set collected by USDA across the US from 1900-2009. The objectives of our study were to investigate crop yield trends in space and time, quantify the variability in yield explained by genetics and space-time (environment) factors, and study how spatio-temporal information could be incorporated and also utilized in modeling and forecasting yield. Based on the format of these data sets, trend of irrigated and dryland crops was analyzed by employing time series statistical techniques. Some traditional linear regressions and smoothing techniques are first used to obtain the yield function. These models were then improved by incorporating time and space information either as explanatory variables or as auto- or cross- correlations adjusted in the residual covariance structures. In addition, a multivariate time series modeling approach was conducted to demonstrate how the space and time correlation information can be utilized to model and forecast yield and related variables. The conclusion from this research clearly emphasizes the importance of space and time components of data sets in research analysis. That is partly because they can often adjust (make up) for those underlying variables and factor effects that are not measured or not well understood.
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Kantanantha, Nantachai. "Crop decision planning under yield and price uncertainties." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/24676.
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Thesis (Ph.D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007.<br>Committee Co-Chair: Griffin, Paul; Committee Co-Chair: Serban, Nicoleta; Committee Member: Liang, Steven; Committee Member: Sharp, Gunter; Committee Member: Tsui, Kwok-Leung
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Stephens, David J. "Crop yield forecasting over large areas in Australia." Thesis, Stephens, David J (1995) Crop yield forecasting over large areas in Australia. PhD thesis, Murdoch University, 1995. https://researchrepository.murdoch.edu.au/id/eprint/51647/.
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Inter-annual variations in crop yield are intricately linked to fluctuations in the weather. Accurate yield forecasts prior to harvest are possible if crop-weather relationships are integrated into models that are responsive to the major yield determining factors.
A network of meteorological stations was selected across the Australian wheat belt and monthly rainfall regressed with wheat yields from the surrounding shires. Autumn rains that permit an early sowing and finishing rains after July are important for higher yields. As the rainfall distribution becomes more winter dominant in nature, both crop yield variability and the usefulness of early winter rainfall decreases. Waterlogging has a large negative effect in the south-west of Western Australia, such that the rainfall distribution is more important than the amount in this region.
A national sowing date survey determined that regional sowing dates have become earlier during the 1980’s and that these vary considerably, especially to the north-east. In Western Australia, earlier sowing combined with higher nitrogen inputs from fertilizers and legumes caused a significant upward trend in recent yields. Trends have been smaller in other states.
Yields were also regressed with broad scale atmospheric indicators. Up to a year in advance of harvest, changes in the amplitude of the trough in the upper level westerlies (South Pacific) precede major anomalies in yields. Trends in the Southern Oscillation Index (SOI) around sowing time account for half the variance in the national yield, due to a persistence in following rainfall anomalies.
Agrometeorological index models that combine the features of simulation and regression are shown to be the most appropriate models for yield forecasting. At a shire level they account for an average 55% of the yield variance in Western Australia, but 60 to 80% of the variation in eastern states yields. Satellite spectral data also resolved similar amounts of yield variance when sensor calibration bias was removed. With a mean regional index determined by station weighting, crop-weather models account for 87 to 92% of the variance of state and national yields. Tests with operational model forecasts equalled, or were more accurate than, official forecasts in 4 out of 5 years. Seasonal outlooks incorporated into model calculations brought further gains in accuracy in extreme years.
Overall, the broad scale extent of yield anomalies across the Australian wheat belt is highlighted. Extreme yields, which are of most interest to the grain industry, are inseparably coupled to the ENSO phenomenon and the broad scale atmospheric circulation. Crop-weather models adjust rapidly to these anomalies in the weather and should be applied in an operational environment to provide early indications of crop prospects.
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Al-Shammari, Dhahi Turki Jadah. "Remote sensing applications for crop type mapping and crop yield prediction for digital agriculture." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29771.
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This thesis addresses important topics in agricultural modelling research. Chapter 1 describes the importance of land productivity and the pressure on the agricultural sector to provide food. In chapter 2, a summer crop type mapping model has been developed to map major cotton fields in-season in the Murray Darling Basin (MDB) in Australia. In chapter 3, a robust crop classification model has been designed to classify two major crops (cereals and canola) in the MDB in Australia. chapter 4 focused on exploring changes in prediction quality with changes in the spatial resolution of predictors and the predictions. More specifically, this study investigated whether inputs should be resampled prior to modelling, or the modelling implemented first with the aggregation of predictions happening as a final step. In chapter 5, a new vegetation index is proposed that exploits the three red-edge bands provided by the Sentinel-2 satellite to capture changes in the transition region between the photosynthetically affected region (red region) and the Near-Infrared region (NIR region) affected by cell structure and leaf layers. Chapter 6 was conducted to test the potential of integration of two mechanistic-type model products (biomass and soil moisture) in the DDMs models. Chapter 7 was dedicated to discussing each technique used in this thesis and the outcomes of each technique, and the relationships between these outcomes. This thesis addressed the topics and questioned asked at the beginning of this research and the outcomes are listed in each chapter.
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Tarhuni, Abdalla Mohamed. "The potential for improved yield and yield stability in faba bean (Vicia faba L.) cultivar mixtures." Thesis, University of Liverpool, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235564.
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Clark, Nathan J. "Investigating the relationship between yield risk and agri-environmental indicators." Lexington, Ky. : [University of Kentucky Libraries], 2002. http://lib.uky.edu/ETD/ukyagec2002t00040/Clark.pdf.
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Thesis (M.S.)--University of Kentucky, 2002.<br>Title from document title page. Document formatted into pages; contains viii, 51 p. : ill, maps. Includes abstract. Includes bibliographical references (p. 49-50).
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Almuayrifi, Mohammed Saleh B. "Effect of fertilisation, crop protection, pre-crop and variety choice on yield of phenols content diseases severity and yield of winter wheat." Thesis, University of Newcastle upon Tyne, 2013. http://hdl.handle.net/10443/2196.
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There is increasing pressure from government legislation and supermarket quality assurance schemes to reduce chemosynthetic pesticide-inputs in conventional production systems. This has resulted in the need to study potential management based approaches to develop alternative management (e.g. rotational design or crop nutrition) strategies and/or crop breeding/variety selection based approaches to reduce disease pressure or crop resistance to biotic stress. Two long-term, factorial field trials (the NSCS and the NUE-crops trials) were used to assess effects of fertiliser input types (composted manure vs mineral fertilisers), fertiliser input levels, pre-crop/rotational position, crop protection (with and without the use of chemosynthetic pesticides) and wheat genetics/variety choice on phenolic profiles in flag leaves, foliar disease severity and grain yield in winter wheat. Interactions between crop management practices and growing season were investigated using univariate and redundancy analysis approaches. Flag leaf concentrations of phenolic compounds differed between years and plant growth stages and were higher (approx 40%) in crops fertilised with organic compared to mineral fertilisers, but there were virtually no effects of crop protection on phenolic profiles. In contrast, both disease severity and crop yield were significantly affected by crop protection and fertilisation practices. The use of conventional, pesticide based crop protection resulted in lower disease severity and higher yields and mineral NPK fertilisers resulted in lower Septoria and higher mildew and stripe rust severity. Effects of precrop/rotational position and wheat genetics/variety choice, and interactions between precrop, fertilisation, crop protection and/or variety choice were also detected for phenolic profiles, disease severity and grain yield. RDA identified (a) positive associations between organic fertilisation and radiation, and concentrations of phenolic compounds in leaves, (b) positive associations between organic crop protection and relative humidity, and disease severity and (c) negative associations between concentrations of most phenolic compounds and disease severity. Results indicate that it is possible to increaseing concentrations of phenolic compounds in cereals via changes to fertilisation practices, and that this may (a) reduce disease severity and/or increase crop yield in cropping systems which omit chemosynthetic pesticides, but (b) may have no effect on disease and reduced crop yields in cereal cropping systems which use pesticides. However, varietal differences in leaf phenolic expression under organic fertilisation could not be linked to differences in disease severity and yields.
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Monteiro, Leonardo Amaral. "Sugarcane yield gap in Brazil: a crop modelling approach." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-08032016-142721/.
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Currently, the cropping area is around 10 million hectares, in which the sugarcane fields are expanding for marginal regions, mainly where grains and pasture were previously cultivated. From that, the objectives of this study were: to calibrate and evaluate a sugarcane yield model using data from 12 fields conducted under high technology field conditions; to evaluate the performance of a gridded system (NASA/POWER) to increase the spatial density of the weather stations in Brazil, to be employed as input data of crop simulation models; to map, in micro-region scale, the potential (Yp), the best farmer\'s (Ybf) and average actual (Yavg) sugarcane yields in Brazil, in order to determine the sugarcane yield gaps by water deficit (YGWD) and by crop management (YGCM), and to define strategies for a most sustainable sugarcane crop production. The yield model showed a good performance in the yield simulation, during the calibration and validation phases. The estimated yield in the calibration phase was 81.9 Mg ha-1 while the observed one was 82.3 Mg ha-1. In the validation phase, the estimated yield was 82.9 Mg ha-1 and the observed was 86.9 Mg ha-1. These results suggested that this kind of model can be used for yield estimation, mainly for agricultural planning purposes, at regional and national scales. The NASA/POWER weather data showed a reasonable performance when compared to observed data that control Yp (solar radiation and air temperature). On the other hand, although the annual average rainfall were very similar in all locations evaluated, this variable presented unsatisfactory statistical coefficients (R2 = 0.60 and MAPE = 233.4%), being suggested, therefore, to replacement of rainfall data from the gridded system by the ones from local rainfall stations (ANA). In the majority of the locations, the percentage errors of Yp were ±15%, while the attainable yield was overestimated by 14% when estimated without replace the rainfall data by the ANA\'s data. Otherwise, when the rainfall data were modified by the ones from ANA, a better adjustment was obtained, revealing an overestimation of only 5%. Finally, 259 virtual weather stations were generated with NASA/POWER data and rainfall from ANA database to estimate yields. The yield types were spatialized through software ArcGis 9.3® at micro-region level. The yield gaps by water deficit and crop management were determined. It was observed that the sugarcane yield losses in Brazil are mainly caused by water deficit (74% of total yield gap), while 26% was due crop management. These results contribute for a better understanding about the factors that control sugarcane production and, therefore, they can be used to define strategies, such use of drought tolerant cultivars, irrigation, and soil decompaction, to make sugarcane production in Brazil more efficient and sustainable.<br>Atualmente, a cana de açúcar ocupa uma área de aproximadamente 10 milhões de hectares, revelando um pronunciado avanço dos canaviais para regiões marginais, onde anteriormente predominavam os cultivos de grãos e pastagens. Assim, os objetivos deste estudo foram calibrar e avaliar um modelo de estimativa da produtividade de colmos da cana de açúcar em 12 locais, sob elevado padrão tecnológico e operacional de cultivo; avaliar o desempenho de um sistema de dados meteorológicos em grid (NASA/POWER, 1°x1°) para incrementar a densidade espacial de estações meteorológicas no Brasil para serem empregados em modelos de simulação de culturas; e mapear, a produtividade potencial (Yp), a produtividade obtida pelos produtores com elevado nível tecnológico (Ybf) e a produtividade real média (Yavg) de colmos no Brasil, para, posteriormente, determinar a quebra de produtividade da cana de açúcar decorrente do déficit hídrico (YGWD) e do manejo da cultura (YGCM), a fim de indicar estratégias para um cultivo mais sustentável. O modelo agrometeorológico de estimativa apresentou desempenho satisfatório na simulação das produtividades, tanto na fase de calibração como na validação. A produtividade estimada na calibração foi de 81.9 Mg ha-1 enquanto que a observada foi 82.3 Mg ha-1. Na validação, a produtividade estimada foi 82,9 Mg ha-1 e a observada foi 86,9 Mg ha-1. Esses resultados sugerem a possibilidade do emprego desse modelo para a estimativa da produtividade da cultura da cana-de-açúcar, principalmente em termos de planejamento agrícola em média e grande escalas. O sistema NASA/POWER apresentou desempenho satisfatório em relação às variáveis meteorológicas que controlam a Yp (radiação solar e temperatura do ar). Por outro lado, embora os totais anuais de precipitação tenham sido bastante semelhantes, a precipitação apresentou coeficientes estatísticos apenas razoáveis, principalmente para aplicações em modelos de simulação da produtividade (R2 = 0,60 e MAPE = 233,4%), sendo sugerido, portanto, o uso de dados dessa variável provenientes de estações pluviométricas locais. Na grande maioria dos locais avaliados o erro percentual da produtividade potencial variou entre ±15%, enquanto que a produtividade atingível foi superestimada em 14% quando esta foi estimada com os dados de precipitação do sistema NASA/POWER. Por outro lado, quando os dados de precipitação foram modificados pelos dados de estações pluviométricas da ANA, houve apenas 5% de superestimativa da produtividade. Por fim, foram geradas 259 estações meteorológicas virtuais com os dados do sistema NASA/POWER e a precipitação das estações pluviométricas da ANA. Posteriormente, os yield gaps por efeito do déficit hídrico e do manejo da cultura foram determinados. Os resultados indicaram que o principal fator restritivo da produtividade da cana de açúcar no Brasil é o déficit hídrico (74% do YG total), enquanto que as práticas de manejo da cultura sub-ótimas contribuem com 26% da quebra total. Isso contribuiu para um melhor entendimento dos aspectos que afetam a produção de cana de açúcar em diferentes regiões brasileiras, sendo, portanto, possível se delimitar estratégias, como o uso de cultivares tolerantes à seca, a irrigação e a descompactação dos solos, que tornem a cultura mais resiliente e produção canavieira mais eficiente e sustentável.
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Napier, Christopher Cameron. "Crop Yield using Novel Parametric L-system plant modelling." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2024. https://ro.ecu.edu.au/theses/2907.
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This research considers a system for the recognition of real plant parts through image analysis based upon synthetic plant modelling. It aims to use data pipelines and synthetic datasets to define recognizable features that assist in the efficient analysis of real plants and plant images. This research asks about the efficacy of L-systems in accurately simulating wheat crop characteristics. It specifically focusses on readable, understandable, accurate, and complex L-system algorithms. The research examines wheat crops in terms of phenotypes and examines the accuracy of a dataset in support of real image annotation. The methodology used was experimental in nature and based around the generation of virtual plants and plant images to generate realistic synthetic plant 3D models. This research created a novel L-system framework. This generated an algorithmically derived synthetic dataset (L-NAP) which could be used to recognize and manage features for the precise consideration of wheat crop yield estimations. This study demonstrates the value of L-systems to create a viable dataset using less aggregated data, that retains accuracy, stability, complexity, and applied usability.
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Blackmore, Simon. "The role of yield maps in precision farming." Thesis, Cranfield University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269521.
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Stanley, Jordan. "Yield-Limiting Factors in North Dakota Soybean Fields." Thesis, North Dakota State University, 2017. https://hdl.handle.net/10365/28382.
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Average soybean [Glycine max (L.) Merrill] yields in North Dakota remain below north central USA averages, and crop yield potentials. The effect of planting date (PD), cultivar relative maturity (RM), and seeding rate (SR), on yield, were evaluated in 821 producer fields in 2014-2016 seasons. Crop management varied by location. State average PD was 19 May, and planting after 1 May reduced yield average 0.4% d-1. Planting a cultivar with 0.1 RM earlier than recommended reduced yield by 1.3%. Producers estimated seedling mortality at 10%; when observed, it was 12.3%. An additional 7.9% reduction of established population occurred in-season. In-season plant reductions of 4.5% were also observed in research trials. North Dakota producers should plant closer to 1 May if conditions are favorable, select latest-maturing cultivars adapted for area, maximize established plant population relative to seeding rate, and determine causes of in-season plant reductions to adapt management practices if necessary.
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Cole, Clay Brady. "Impact of Heterozygosity and Heterogeneity on Cotton Lint Yield Stability." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-03132007-145659/.
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Adequate stability of cotton (Gossypium hirsutum L.) lint yield is an integral criterion for cultivar release; however, the magnitude of lint yield variation today is close to six times greater than variation observed in the 1920?s. Yield stability has often been associated with genetic diversity. Observing cotton lint yield in diverse population types containing various levels and kinds of genetic diversity over many environments could reveal information about stability and how it relates to diversity. An 18-environment field study was undertaken to observe lint yield stability in four population types of cotton. These populations were pure lines grown in pure stands (homozygous/homogeneous), pure lines grown in blended stands (homozygous/heterogeneous), hybrids grown in pure stands (heterozygous/homogeneous), and hybrids grown in blended stands (heterozygous/heterogeneous). Lint yield components were also observed to determine the contribution each had towards lint yield stability. Differences were determined by observing the coefficient of variation (CV) for mean yield and yield components of population types and over environments. We found the heterozygous populations to be more stable than the homozygous populations. This was attributed to the hybrids and blends of hybrids out-yielding the parents and blends of parents in the low-yielding environments. This advantage was not observed in the high-yielding environments and, in effect, reduced the amount of variation observed over all environments. The number of bolls/hectare was the only yield component that showed definitive differences for stability between population types with the heterozygous populations having significantly higher stability than the homozygous populations. The superior stability of the heterozygous populations was attributed to an increased lint production in the lower yielding environments stemming from an increased number of bolls/hectare.
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Mditshwa, Sithembele. "Estimating maize grain yield from crop growth stages using remote sensing and GIS in the Free State Province, South Africa." Thesis, University of Fort Hare, 2017. http://hdl.handle.net/10353/6016.
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Early yield prediction of a maize crop is important for planning and policy decisions. Many countries, including South Africa use the conventional techniques of data collection for maize crop monitoring and yield estimation which are based on ground-based visits and reports. These methods are subjective, very costly and time consuming. Empirical models have been developed using weather data. These are also associated with a number of problems due to the limited spatial distribution of weather stations. Efforts are being made to improve the accuracy and timeliness of yield prediction methods. With the launching of satellites, satellite data are being used for maize crop monitoring and yield prediction. Many studies have revealed that there is a correlation between remotely sensed data (vegetation indices) and crop yields. The satellite based approaches are less expensive, save time, data acquisition covers large areas and can be used to estimate maize grain yields before harvest. This study applied Landsat 8 satellite based vegetation indices, Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Moisture Stress Index (MSI) to predict maize crop yield. These vegetation indices were derived at different growth stages. The investigation was carried out in the Kopanong Local Municipality of the Free State Province, South Africa. Ground-based data (actual harvested maize yields) was collected from Department of Agriculture, Forestry and Fisheries (DAFF). Satellite images were acquired from Geoterra Image (Pty) Ltd and weather data was from the South African Weather Service (SAWS). Multilinear regression approaches were used to relate yields to the remotely sensed indices and meteorological data was used during the development of yield estimation models. The results showed that there are significant correlations between remotely sensed vegetation indices and maize grain yield; up to 63 percent maize yield was predicted from vegetation indices. The study also revealed that NDVI and SAVI are better yield predictors at reproductive growth stages of maize and MSI is a better index to estimate maize yield at both vegetative and reproductive growth stages. The results obtained in this study indicated that maize grain yields can be estimated using satellite indices at different maize growth stages.
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Tan, Wan-Zhong. "Relationships between foliar disease and loss of grain yield in barley with particular reference to powdery mildew." Thesis, Cardiff University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283592.
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Deryng, Delphine. "Climate change and global crop yield : impacts, uncertainties and adaptation." Thesis, University of East Anglia, 2014. https://ueaeprints.uea.ac.uk/50712/.
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As global mean temperature continues to rise steadily, agricultural systems are projected to face unprecedented challenges to cope with climate change. However, understanding of climate change impacts on global crop yield, and of farmers' adaptive capacity, remains incomplete as previous global assessments: (1) inadequately evaluated the role of extreme weather events; (2) focused on a small subset of the full range of climate change predictions; (3) overlooked uncertainties related to the choice of crop modelling approach and; (4) simpli�ed the representation of farming adaptation strategies. This research aimed to assess climate change impacts on global crop yield that accounts for the knowledge gaps listed above, based on the further development and application of the global crop model PEGASUS. Four main research topics are presented. First, I investigated the roles of extreme heat stress at anthesis on crop yield and uncertainties related to the use of seventy-two climate change scenarios. I showed large disparities in impacts across regions as extreme temperatures adversely a�ects major areas of crop production and lower income countries, the latter appear likely to face larger reduction in crop yields. Second, I coordinated the �rst global gridded crop model intercomparison study, comparing simulations of crop yield and water use under climate change. I found modelled global average crop water productivity increases by up to 17�20.3% when including carbon fertilisation e�ects, but decreases to {28�13.9% when excluding them; and identi�ed fundamental uncertainties and gaps in our understanding of crop response to elevated carbon dioxide. Third, to link climate impacts with adaptation, I introduced the recently developed concept of representative agricultural pathways and examined their potential use in models to explore farming adaptation options within biophysical and socio-economic constraints. Finally, I explored tradeo�s between increasing nitrogen fertiliser use to close the global maize yield gap and the resulting nitrous oxide emissions. I found global maize production increases by 62% based on current harvested area using intensive rates of nitrogen fertiliser. This raises the share of nitrous oxide emissions associated with maize production from 20 to 32% of global cereal related emissions. Finally, these results demonstrated that in some regions increasing nitrogen fertiliser application, without addressing other limiting factors such as soil nutrient imbalance and water scarcity, could raise nitrous oxide emissions without enhancing crop yield.
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Мареха, Ірина Сергіївна, Ирина Сергеевна Мареха, Iryna Serhiivna Marekha, Алла Миколаївна Дядечко, Алла Николаевна Дядечко, and Alla Mykolaivna Diadechko. "Foreign experience of determining crop yield losses from air pollutants." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/13455.
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It has long been known that crops can be injured by air pollutants. Air pollution is a major stress causing yield losses in California crops. Statewide monitoring indicates that ozone, the main component of air pollution, is transported from urban to agricultural areas, many of which lie within or near high-ozone regions.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/13455
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Whelan, Helen G. "The effect of crop yield potential on disease yield loss relationships in barley (Hordeum vulgare L.)." Lincoln University, 1992. http://hdl.handle.net/10182/1980.
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Proportional loss models commonly used in disease surveys are based on the assumption that per cent yield loss is the same in all crops, regardless of their yield potential. Estimates of regional crop loss may be inaccurate if the relationship between disease and yield loss is affected by crop yield potential. The importance of crop yield potential in disease: yield loss modelling was investigated and models for more accurate regional crop loss estimates were developed, taking crop yield potential into account. Two spring sown barley (cv. Triumph) experiments were conducted in 1987/88 and 1988/89 in Canterbury, New Zealand, to study the effect of crop yield potential on the relationship between disease and yield loss. Crop yield potentials of 323 to 806gDM/m² were generated in seven crops by varying nitrogen and water inputs, sowing date (mid-spring and early-summer) and season. Leaf rust (Puccinia hordei Otth) epidemics of different severity were generated by applying fungicides at different times, frequencies and rates to control the natural epidemics. Disease was measured as per cent disease severity (%DS), green leaf area, radiation interception and near-infrared radiation (NIR) reflectance from crop canopies. Yield was measured as total and grain dry weight. Epidemics were severe in the fully diseased plots from GS 34 and 46 to maturity in the late and early sown crops respectively. Disease reduced grain yield by 50 to 63% in 1987/88 and 24 to 38% in 1988/89 in the fully diseased plots. Disease: yield loss models were derived by regression analysis for each crop in 1987/88. Single point, multiple point and area under curve models were derived from %DS and GLAI variables, and proportional (%) and actual (gDM/m²) grain yield. The effect of yield potential was determined by comparing regression equation coefficients for each crop with crop yield potential. An area under green leaf area index curve (AUGLAIC): actual yield model was best suited to determining the effect of yield potential on yield loss. This model was selected because AUGLAIC summarised the effect of disease on plant growth over the season and actual yield represented the crop yield potential in the absence of disease and the response of actual yield to disease. Crop yield potential did not affect actual yield loss caused by leaf rust. Disease measured as AUGLAIC explained most of the variation in yield (R²adj=0.93) for all crops in both years. Assessment of GLAI is not suitable for estimation of regional crop loss because of the requirement for a rapid and low cost method. Reflectance of NIR from the crop canopy was investigated as an alternative to GLAI measurements. Reflectance was correlated significantly (P<0.001) with GLAI (r=0.66 to 0.89) and green area index (r=0.76 to 0.92). Reflectance measured at grain-filling (GS 85-87) explained most (R²adj=0.94) of the variation in yield for all crops in both years. The relationship between AUGLAIC and yield was validated with data from independent diseased and healthy barley crops. The AUGLAIC: yield model described the effects of disease on yield accurately but overestimated yield by 49 to 108% in the healthy crops. Models based on accumulated PAR (photosynthetically active radiation) intercepted by green leaves explained the observed deviations in yield of these crops from the AUGLAIC: yield model. Accumulated PAR models accounted for differences in incident radiation, canopy structure, radiation interception by green leaves, radiation use efficiency and harvest index which are important in determining dry matter production and grain yield. Accumulated PAR models described the effects of disease on crop growth which were not represented by GLAI alone. Variation in crop yield potential at the regional scale is important in disease: yield loss modelling and can be accounted for by using either separate equations for each yield potential crop or crop category, robust models, inclusion of a form function for yield potential or choice of disease and yield variables which integrate yield potential.
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Enger, Matthew. "IMPACTS OF CONCENTRATED FLOW PATHS ON CROP YIELDS AND WATER QUALITY IN SOUTHERN ILLINOIS ROW CROP AGRICULTURE." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2380.
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Sediment and nutrient loss from agricultural landscapes contributes to water quality impairment and has the potential to impact crop yield. Best management practices (BMPs) such as riparian buffers have been designed to combat these issues; however, concentrated flow paths (CFPs) reduce their effectiveness and are often overlooked in agricultural fields. Conventional management of CFPs is to fill and grade them, however this provides only a short term solution leading to their reformation and increased sediment loss. The objectives of this project were: i) to determine if the filling of CFPs influence crop growth (yield and biomass), ii) determine a distance at which crop growth is no longer influenced by CFPs, iii) assess the impact that topography and CFPs have on crop growth, iv) analyze water quality in surface runoff leaving crop fields via CFPs, and v) develop an economic analysis for CFP’s influence on crop returns. Six small agricultural catchments, CFPs, and topographic positions (i.e., depositional, backslope, and shoulder) were delineated using ArcGIS and LiDAR data. In each catchment, six 4 m2 plots were established along CFPs where crop biomass and crop yield were measured. Additionally, six plots with no influence from CFPs were established as reference plots. Surface water quality was assessed by taking edge-of-field grab samples at the CFP outlet during significant rain events (i.e., precipitation exceeding 2.5 cm). Water samples were analyzed for total suspended solids (TSS), total phosphorus (TP), dissolved reactive phosphorus (DRP), ammonium-nitrogen (NH4+-N), and nitrate-N (NO3- -N). Through this study it was shown that CFPs served as a conduit for transporting nutrient and sediment laden runoff to receiving waters, that increasing/decreasing distance from CFPs had an impact on crop yields, and that there was no crop yield advantage from the filling of CFPs vs. leaving them unfilled. Median values for NO3-N (1.85 mg L-1) and TSS (140 mg L-1) in the Fill catchments were higher than the No-Fill catchments (0.77 mg L-1 and 35.5 mg L-1, respectively), while DRP and TP concentrations were higher in the No-Fill catchments (1.31 mg L-1 and 2.37 mg L-1, respectively) compared to the Fill catchments (0.91 mg L-1 and 1.83 mg L-1, respectively) over the growing season. Crop biomass and yield results between the depositional and backslope positions were similar regardless of treatment, but were lower than the reference plots and shoulder position. Results from the economic analysis on the cost of farming in/near CFPs indicated that the economic return was greatly dependent on precipitation. CFPs are generally concave positions on the landscapes and have been eroded to a clayey subsoil, both resulting in greater water accumulation and retention than elsewhere in the field. During wetter years, an economic loss was incurred nearest to the CFP and during drier years, sites nearest to CFPs saw positive returns. Farmers and land managers may consider implementing stabilization measures, such as grassed waterways, in CFPs since crop yields are typically lower in wetter years, there’s increased cost to maintain these areas, and accelerated sediment loss can exacerbate the crop yield losses and impact on water quality.
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Goodwin, Richard Philip. "Crop yield prediction in the UK using the reflected solar radiation." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312374.
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Avval, M. Bannayan. "Developing and applying crop simulation models for forecast winter wheat yield." Thesis, University of Nottingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285454.
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Brien, Gabriel T. (Gabriel Thomas). "Contribution of environmental factors to crop yield variation in the US." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111516.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 68-71).<br>The magnitude of crop production per unit area has increased in the US in the last 50 years due to the green revolution (Femandez-Comejo, 2004). Yet, even with these increases, there is still variability in crop yield that is present in modem, intensive agricultural systems (Porter and Semenov, 2005). This variability has a negative effect on food security which depends on a minimum amount of food being available at a given point in time. By definition, food cannot be secure unless it is guaranteed to a certain level (Maxwell, 1996). Hence, an understanding of crop yield variability is essential to the question of food security. Using a linear mixed effects analysis for a particular US state and a particular crop, environmental factors that affect variability were shown, in both irrigated and rainfed crop situations to explain over 80% of yield variance. The variance was linked to two major factors: daily air temperature and soil moisture. For rainfed yield, temperature effects explained 40% of the yield variance while soil moisture explained 43% of yield variance. For irrigated yield temperature effects explained 87% of the yield variance. The results suggest that yield variance occurs from variation in the season averages, and in specific points in the growing season, for the major factors highlighted. This assessment is confirmed by moisture and temperature sensitivity characteristics of the crop in question. It is shown by exploratory, time series, and spatial analysis that low yield observations have contrasts in growing season conditions both during key crop reproduction periods and over the entire season. Herein it is argued that variation in temperature effects and moisture have the highest effect on crop yield particularly when they occur during the reproductive phase of the plant.<br>by Gabriel T. Brien.<br>M. Eng.
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Melamed, Ricardo. "Corn growth, development and yield response to tillage - crop rotation systems." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1407403698.
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Osorio, Morillo Raul Jefferson. "GIS approach to estimate windbreak crop yield effects in Kansas-Nebraska." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/36203.
Full textAbstract:
Master of Science<br>Department of Horticulture and Natural Resources<br>Charles J. Barden<br>Windbreaks were originally promoted across the Great Plains region of the U.S to reduce wind erosion in general. A review paper published nearly 30 years ago showed yield increases for a variety of crops associated with windbreaks. However, with the widespread use of no-till systems in all farming and advanced crop genetics, the question is “Do windbreaks still provide a yield benefit?” This study compared multiple years of data from protected and unprotected fields across Kansas and few sites in Nebraska looking at relative crop yield differences of five crops: soybeans, wheat, corn, sorghum and sunflowers. Georeferenced data already existed, generated by automated combine yield monitors, and stored on farmer's computers. There were three sets of data collected for each field. The first level is general field level information, using aerial photography and on-site observations to measure the characteristics of the windbreak (length, height and density). The second was from the yield monitor; this data was analyzed with ArcGIS 10.3.1 to visualize windbreak interaction with crop yield. Multiple means comparisons (protected versus unprotected) through two sample T-tests were conducted to determine if the yield in protected areas of fields was significantly different from the yield in unprotected areas. The third data-layer is climate data that was factored into yield analysis to compare wet, normal and dry growing seasons through a Chi-Square 2x2 test analysis. Optical density of windbreaks from leaf-on/off ground-based photos was assessed using SigmaScan Pro 5.0 software as possibly an important factor influencing the windbreak effect. Finally, the yield loss was estimated from the windbreak footprint to see if yield increases are enough to compensate for the area taken out of crop production. Results showed that soybeans (81 crop/years) had the most positive response to windbreak effect with a yield increase 46% of the time, with a 16% average yield increase. Sorghum (31 crop/years) had the highest average yield increase with 25%. Narrow windbreaks (1 to 2 tree rows with an average of 52 ft. width) and those on the north edge of fields resulted in yield increases which compensated for the footprint of the windbreak more often than wider windbreaks on the south edges of fields. Significant yield increases were less than the decreases in the protected area. There was no evidence to show the windbreak effect on yield had any association with critical month precipitation for any crop or orientation group. According to the results obtained, modern hybrids and varieties are possibly less responsive to yield increases due to windbreak effect than older crop varieties. Future studies should collect more data from fields with different windbreak widths distributed more widely across the region to confirm these results. Overall, this project updated our knowledge of windbreak/crop yield interactions and may possibly influence their future role as a conservation practice in the Great Plains.
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Ogunbo, Samuel O. "Show-Me stability : a new method for evaluating crop yield means /." free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9946284.
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Peterson, Shelley. "Spatial variability of soil nitrogen, crop yields and delta yield in relation to variable rate nitrogen fertilization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ35922.pdf.
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Orlowski, Jan Alexander Kazimierz. "The ENSO Cycle and Predictability of US Crop Yields." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17166.
Full textAbstract:
While the impacts of the El Nino Southern Oscillation (ENSO) are well documented on topics ranging from agricultural production to socio-economic factors, a closer consideration of key interaction terms in this complex relationship is pivotal for better understanding of future production impacts and as well as relevant policy implications. In this thesis, the ENSO link to staple crop production in the US is derived through an econometric approach, in particular taking advantage of recent advances in the nonlinear parameterization of climate variables such as temperature. Via the comparison of competing model specifications, across all major Corn and Soybean producing regions in the United States, the findings of the present study suggest the ENSO link with crop yields manifests itself primarily via extreme degree days. Following this conclusion, this study further extends previous literature by examining the effect of ENSO anomalies on agricultural production in an out-of-sample setting. Optimal producer strategies can be a powerful adaptive measure to anticipated/forecasted ENSO outcomes, predominantly planting date and crop mix. Key results prove valuable to such strategies, particularly in those regions where the channel of ENSO influence for production is obvious, and statistically significant in a pseudo-forecasting environment.
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Shearman, Victoria Jane. "Changes in the yield limiting processes associated with the genetic improvement of wheat." Thesis, University of Nottingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368340.
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Landau, Sabine. "A parsimonious model of wheat yield response to environment." Thesis, University of Nottingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389366.
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Norton, E. R., and J. C. Silvertooth. "Development of a Yield Projection Technique for Arizona Cotton." College of Agriculture, University of Arizona (Tucson, AZ), 2000. http://hdl.handle.net/10150/197473.
Full textAbstract:
A series of boll measurements were taken at numerous locations in cotton producing areas across Arizona in 1999 in an attempt to continue to develop a yield prediction model with a project that began in 1993. Results from 1995 showed the strongest relationship between final open boll counts and yield compared to a number of other measurements. Based on these results, data collection on boll counts began in 1996 and has continued in 1997, 1998, and 1999. Boll counts were taken as the number of harvestable bolls per meter. All boll count measurements were made within one week of harvest. Number of bolls per unit area were then correlated to lint yield and an estimate for the number of bolls per area needed to produce a bale of lint was calculated. Estimates using all four years of data combined indicate that approximately 38 bolls per meter are needed to produce one bale of lint per acre.
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Sigdel, Sailesh. "Seeding Time and Interseeded Cover Crop Species Influence Sugarbeet Yield and Quality." Thesis, North Dakota State University, 2020. https://hdl.handle.net/10365/31884.
Full textAbstract:
Field experiments were conducted to evaluate cover crop interseeding time and species effect on sugarbeet production during 2018 and 2019 growing seasons. Cover crops were first interseeded in June and second interseeding was done in late June or early July. Four cover crops species, Austrian pea (Pisum sativum L.), winter rye (Secale cereale L.), winter camelina [Camelina sativa (L.) Crantz], and brown mustard (Brassica juncea L.), were examined. First interseeding resulted in significantly higher cover crop biomass than second interseeding. In 2018, the highest recoverable sugar yield was observed with pea (13.9 Mg ha-1) and camelina (6.6 Mg ha-1) first-interseeded, at Ada and Downer, MN, respectively. In 2019, camelina (11.2 Mg ha-1) at Ada, MN, and pea (12.4 Mg ha-1) at Prosper, ND both second-interseeded, had the highest recoverable sugar yield. Cover crops had no negative impacts on sugarbeet, but the selection of species and planting time are critical.
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NDAYISENGA, VALENCE. "APPROPRIATE FOOD PRODUCTION THROUGH INCREASING CROP YIELD AND INTRODUCING NEW CROPS IN THE DEMOCRATIC REPUBLIC OF THE CONGO." Doctoral thesis, Università Cattolica del Sacro Cuore, 2018. http://hdl.handle.net/10280/53793.
Full textAbstract:
La mancanza di una buona dieta ben bilanciata nutrizionalmente, porta al persistente sottosviluppo, in particolare per la capacità fisica e intellettuale delle persone e ha un impatto negativo sullo sviluppo del Paese. La presente tesi di dottorato mirava a valutare le strategie per produrre un cibo appropriato sufficiente, sicuro e sostenibile attraverso la sperimentazione di diverse tecniche di coltivazione e cultivar locali di manioca per identificare quali tecniche e cultivar sono più performanti per aumentare la resa. Dall’altra parte, al fine di contribuire alla diversificazione della produzione del cibo e al miglioramento del piatto tradizionale congolese costituita da più di 80% di carboidrati in particolare la manioca, studi su nuove colture riconosciute contenere dei buoni livelli in proteine, vitamine e minerali come Patata dolce a polpa arancione (Ipomoea batatas) riconosciuta essere ricca soprattutto in provitamina A e quinoa (Chenopodium quinoa Willd.) riconosciuta in particolare per il suo buon contenuto di aminoacidi ben bilanciato sono state condotte. Come risultato, tra tre tecniche di coltivazione (Ridge, Mound e Flat) per la produzione di manioca e 5 cultivar locali di manioca (Dunda, Kakuanga, Kasongoy, Kasonie, Ngoymuamba) valutati, la coltivazione su Ridge e il culltivar Ngoymuamba hanno dato il risultato più alto (19,2 Mg ha-1 di tuberi freschi), mentre Dunda è stata la cultivar che ha prodotto molto meno (6,8 Mg ha-1 di tuberi freschi). Le cultivar di patata dolce a polpa arancione studiati, hanno dimostrato che il contenuto in β-carotene è ragionevolmente alto perché 87 g di tuberi fresche sono sufficienti per coprire la dose giornaliera raccomandata in vitamina A per gli adulti. Per quinoa, tre cultivar (Pasankalla, Puno, Titicaca) hanno dimostrato di produrre una resa considerevole in quanto la produzione in granella è stata rispettivamente di 2,2 Mg ha-1; 1,9 Mg ha-1; 1,3 Mg ha-1 per Titicaca, Pasankalla e Puno.<br>The lack of a good diet well balanced nutritionally, leads to the persistent underdevelopment, particularly for the physical and intellectual capacity of the people and impacts negatively on the development of the country. The present doctoral thesis aimed to assess strategies to produce an appropriate food sufficient, safe and sustainable through experimenting different cultivating techniques and local cultivars of cassava for identifying which techniques and cultivars are more performant to increase yield. On the other hand, in order to contribute to the diversification of food production and improvement of the traditional Congolese diet constituted by more than 80% of carbohydrates particularly cassava, new crops recognized to have a better content in protein, minerals, and vitamins such as Orange-Fleshed Sweet Potato (Ipomoea batatas) recognized to be rich especially in provitamin A and quinoa (Chenopodium quinoa Willd.) recognized particularly for its well-balanced amino acids content were studied. As results, among three Planting methods (Ridge, Mound, and Flat) for producing cassava and 5 local cultivars of cassava (Dunda, Kakuanga, Kasongoy, Kasonie, Ngoymuamba) assessed, ridge and culltivar Ngoymuamba resulted to give the highest yield (19.2 Mg ha-1 in fresh roots), while Dunda was the cultivar which produced the lowest yield (6.8 Mg ha-1 in fresh roots). The Orange-Fleshed Sweet Potato cultivars studied showed that its content in β-carotene is reasonably high as 87 g per day can cover the whole daily allowances of vitamin A in adults’ people. On the quinoa side, three cultivars (Pasankalla, Puno, Titicaca) demonstrated to produce considerable yield as the production in grain was 2.2 Mg ha-1, 1.9 Mg ha-1, 1.3 Mg ha-1, respectively for Titicaca, Pasankalla and Puno.
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NDAYISENGA, VALENCE. "APPROPRIATE FOOD PRODUCTION THROUGH INCREASING CROP YIELD AND INTRODUCING NEW CROPS IN THE DEMOCRATIC REPUBLIC OF THE CONGO." Doctoral thesis, Università Cattolica del Sacro Cuore, 2018. http://hdl.handle.net/10280/53793.
Full textAbstract:
La mancanza di una buona dieta ben bilanciata nutrizionalmente, porta al persistente sottosviluppo, in particolare per la capacità fisica e intellettuale delle persone e ha un impatto negativo sullo sviluppo del Paese. La presente tesi di dottorato mirava a valutare le strategie per produrre un cibo appropriato sufficiente, sicuro e sostenibile attraverso la sperimentazione di diverse tecniche di coltivazione e cultivar locali di manioca per identificare quali tecniche e cultivar sono più performanti per aumentare la resa. Dall’altra parte, al fine di contribuire alla diversificazione della produzione del cibo e al miglioramento del piatto tradizionale congolese costituita da più di 80% di carboidrati in particolare la manioca, studi su nuove colture riconosciute contenere dei buoni livelli in proteine, vitamine e minerali come Patata dolce a polpa arancione (Ipomoea batatas) riconosciuta essere ricca soprattutto in provitamina A e quinoa (Chenopodium quinoa Willd.) riconosciuta in particolare per il suo buon contenuto di aminoacidi ben bilanciato sono state condotte. Come risultato, tra tre tecniche di coltivazione (Ridge, Mound e Flat) per la produzione di manioca e 5 cultivar locali di manioca (Dunda, Kakuanga, Kasongoy, Kasonie, Ngoymuamba) valutati, la coltivazione su Ridge e il culltivar Ngoymuamba hanno dato il risultato più alto (19,2 Mg ha-1 di tuberi freschi), mentre Dunda è stata la cultivar che ha prodotto molto meno (6,8 Mg ha-1 di tuberi freschi). Le cultivar di patata dolce a polpa arancione studiati, hanno dimostrato che il contenuto in β-carotene è ragionevolmente alto perché 87 g di tuberi fresche sono sufficienti per coprire la dose giornaliera raccomandata in vitamina A per gli adulti. Per quinoa, tre cultivar (Pasankalla, Puno, Titicaca) hanno dimostrato di produrre una resa considerevole in quanto la produzione in granella è stata rispettivamente di 2,2 Mg ha-1; 1,9 Mg ha-1; 1,3 Mg ha-1 per Titicaca, Pasankalla e Puno.<br>The lack of a good diet well balanced nutritionally, leads to the persistent underdevelopment, particularly for the physical and intellectual capacity of the people and impacts negatively on the development of the country. The present doctoral thesis aimed to assess strategies to produce an appropriate food sufficient, safe and sustainable through experimenting different cultivating techniques and local cultivars of cassava for identifying which techniques and cultivars are more performant to increase yield. On the other hand, in order to contribute to the diversification of food production and improvement of the traditional Congolese diet constituted by more than 80% of carbohydrates particularly cassava, new crops recognized to have a better content in protein, minerals, and vitamins such as Orange-Fleshed Sweet Potato (Ipomoea batatas) recognized to be rich especially in provitamin A and quinoa (Chenopodium quinoa Willd.) recognized particularly for its well-balanced amino acids content were studied. As results, among three Planting methods (Ridge, Mound, and Flat) for producing cassava and 5 local cultivars of cassava (Dunda, Kakuanga, Kasongoy, Kasonie, Ngoymuamba) assessed, ridge and culltivar Ngoymuamba resulted to give the highest yield (19.2 Mg ha-1 in fresh roots), while Dunda was the cultivar which produced the lowest yield (6.8 Mg ha-1 in fresh roots). The Orange-Fleshed Sweet Potato cultivars studied showed that its content in β-carotene is reasonably high as 87 g per day can cover the whole daily allowances of vitamin A in adults’ people. On the quinoa side, three cultivars (Pasankalla, Puno, Titicaca) demonstrated to produce considerable yield as the production in grain was 2.2 Mg ha-1, 1.9 Mg ha-1, 1.3 Mg ha-1, respectively for Titicaca, Pasankalla and Puno.
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Teo, Chee-Kiat. "Application of satellite-based rainfall estimates to crop yield forecasting in Africa." Thesis, University of Reading, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434333.
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Osman, E. M. H. "Crop yield forecasting at national and regional levels using remote sensing techniques." Thesis, Cranfield University, 2003. http://dspace.lib.cranfield.ac.uk/handle/1826/11058.
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Crop yield forecasting models are needed to help farmers and decision makers cheaply
detect crop condition early enough to assess and mitigate its impacts on grain
production. A precise estimate of crop production requires an accurate measure of the
total cultivated area and well-established knowledge of crop yield. The first
requirement is no longer a problem as is technically solved through various techniques
such as area frame sampling. With respect to the second, great efforts have been made
to find an accurate definition of the crop yield with respect to the actual factors that
shape its growth through out the season. Agrometeorological models have found a
wide range of applications in agricultural research and technology and are playing an
increasing role in translating information about climate variability into assessments,
predictions and recommendations tailored to the needs of agricultural decision makers.
However these models have generally been developed and tested for application at the
scale of a homogeneous plot. They are criticized for their inability to address large-scale
yield estimates at regional or even national levels in addition to their high cost of
application. This is because field conditions during the period of crop establishment at
the regional scale may be quite variable and poorly represented by standard parameter
values of the crop model.
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Acharya, Umesh. "Can We Increase Crop Yield Adopting Tile Drainage in Fargo Clay Soil?" Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28849.
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Subsurface drainage has recently become common for agriculturally productive soils and key to maintain and improve crop production in poorly drained, frigid clay soils. The first study was conducted for four years (2014-17) at Casselton, ND to determine best combination of drainage, tillage and crop rotation for higher corn yield. Our finding suggested corn yield was highest with no drainage, CS and CH combination in years with drought conditions. The second study was conducted for three years (2015-17) to evaluate subsurface drainage spacing (9, 12, and 15m) and depth (0.9 and 1.2m) combination on corn, soybean and sugarbeet yields and residual soil nitrate-nitrogen (NO3-N) contents. Results indicated that 9 m drain spacing produced highest corn and soybean yield when average across three years in contrast with drain depth that has no effect on corn and soybean yield except for sugarbeet where the 1.2m depth yielded higher than the 0.9m depth.<br>North Dakota Corn Council<br>North Dakota Soybean Council<br>North Dakota Water Resources Research Institute
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Osman, El Mamoun H. "Crop yield forecasting at national and regional levels using remote sensing techniques." Thesis, Cranfield University, 2003. http://dspace.lib.cranfield.ac.uk/handle/1826/11058.
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Crop yield forecasting models are needed to help farmers and decision makers cheaply detect crop condition early enough to assess and mitigate its impacts on grain production. A precise estimate of crop production requires an accurate measure of the total cultivated area and well-established knowledge of crop yield. The first requirement is no longer a problem as is technically solved through various techniques such as area frame sampling. With respect to the second, great efforts have been made to find an accurate definition of the crop yield with respect to the actual factors that shape its growth through out the season. Agrometeorological models have found a wide range of applications in agricultural research and technology and are playing an increasing role in translating information about climate variability into assessments, predictions and recommendations tailored to the needs of agricultural decision makers. However these models have generally been developed and tested for application at the scale of a homogeneous plot. They are criticized for their inability to address large-scale yield estimates at regional or even national levels in addition to their high cost of application. This is because field conditions during the period of crop establishment at the regional scale may be quite variable and poorly represented by standard parameter values of the crop model.
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McClung, Tamara Nicole. "Sweet Corn Germination, Growth, and Yield After a Rye Winter Cover Crop." Thesis, The University of Arizona, 2013. http://hdl.handle.net/10150/311795.
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Martinez, Leoncio 1957. "Water Use, Yield, and Crop Coeffiecients for Stawberries (Fragaria x annanasa D.)." Diss., The University of Arizona, 1995. http://hdl.handle.net/10150/191188.
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Strawberry plants (Fragaria x annanasa D.) were grown in drip irrigated plots covered with gray/black plastic mulch at the Campus Agricultural Center, University of Arizona, Tucson, AZ. During the 1993-94 season varieties Chandler and Oso Grande were grown while in the 1994-95 season varieties Chandler and Selva were grown. Crop coefficients to estimate crop evapotranspiration for Chandler were determined on calendar day and growing degree day (GDD) basis. For the harvest period, the crop coefficients ranged from 0.35 for early March to 0.6 for early June. GDD were computed using 6 °C as the base temperature and 26 °C as the upper threshold temperature. Although GDD is useful to estimate water needs, it did not predict the starting date of harvest because other factors such as day length, transplanting date, and chilling period are involved. In the 1994-95 season, dry, medium and wet irrigation treatments were established for the Chandler. The well irrigated plants yielded 328 g/plant, equivalent to 21.2 metric tons/ha. The dry treatment received 33 % less water than the medium treatment and resulted 25% less yield. There were no statistical differences in yield between the medium and wet treatments, although the wet treatment received 33% more water than the medium treatment. The Oso Grande and Selva were tested and they yielded 46 and 22% less than Chandler, respectively. The harvest period extended for 70 to 100 days and premium size berries were produced during the first half of the harvesting season.
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Wang, Zheng. "Effect of Different Schedules of Baby Corn (Zea Mays L.) Harvests on Baby Corn Yield, Grain Yield, and Economic Profit Value." TopSCHOLAR®, 2009. http://digitalcommons.wku.edu/theses/131.
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Maize (Zea mays L.) ranks third as a food crop after wheat and rice and is characterized not only as a cereal crop but also as a vegetable. Maize used as a vegetable is known as “baby corn”. Baby corn consists of unfertilized young ears harvested 2 or 3 days after silk emergence. The present study was implemented in 2009 at Western Kentucky University Agriculture Research and Education Center (36.93 N, 86.47 E) in Bowling Green, Kentucky. The purpose of the study was to compare the effect of different schemes of harvest on baby corn (BC) yield, grain maize (GM) yield, and estimated economic return. Experimental harvest treatments were 1) no BC harvest, only GM harvest, 2) first harvest as BC, final harvest as GM, 3) first and second harvests as BC, final harvest as GM, and 4) first, second, and third harvests as BC, final harvest as GM. Average estimated BC yields (Kg/ha) for Treatments 2, 3, and 4 were 1445.1, 2681.8, and 3437.5; GM yields (Kg/ha) for Treatments 1, 2, and 3 were 12522.2, 8226.5, and 1380.9; respectively. Since few grain kernels were found after three harvests for BC (Treatment 4), no usable GM yield was produced. BC and GM yields were used for evaluating the economic returns. Results indicated that the sequence of best economic returns would be obtained by harvesting BC three times (Treatment 4), first two harvests for BC and the final for GM (Treatment 3), first harvest for BC and subsequent for GM (Treatment 2), and only for GM harvest (Treatment 1). Although the pattern for only BC harvest was the most profitable system, the human labor requirement and critical timing of harvest limited its production. In states similar to Kentucky, BC could only be grown as an additional crop or to supplant a limited amount of traditional GM hectarage.
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Husman, S. H., and J. C. Silvertooth. "Plant Population Effects on Pima S-6 Lint Yield." College of Agriculture, University of Arizona (Tucson, AZ), 1992. http://hdl.handle.net/10150/208640.
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A replicated field study was conducted at the Maricopa Agricultural Center in 1991 to investigate the effect of plant population density on Pima S-6 lint yield. Treatments ranged from a low of 10,465 plants per acre to a high of 65,000 plants per acre. There were no significant yield differences observed with populations between 17,000 plants per acre and 65,000 plants per acre. Significant yield decreases occurred when populations were reduced below 17,000 plants per acre.
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Norton, E. R., and J. C. Silvertooth. "Development of a Yield Projection Technique for Arizona Cotton." College of Agriculture, University of Arizona (Tucson, AZ), 1996. http://hdl.handle.net/10150/210756.
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A series of boll measurements were taken at several locations across the state in 1995 in an attempt to develop a yield prediction model. Measurements were taken out of two strip plot variety trials at the University of Arizona Maricopa Agricultural Center and in the Coolidge area, and also out of two commercial fields in Buckeye and Paloma Ranch over a period of approximately 2 months from peak bloom through cut-out. Data analysis revealed a best fit model that included seedcotton yield as a function of boll count, boll size, boll diameter, and heat units accumulated after planting (HUAP). A series of open boll counts were also taken from over 120 experimental units across the state within one week of harvest. The data revealed strongest relationships between final open boll counts and yield.
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Hollinger, David L. "Crop Condition and Yield Prediction at the Field Scale with Geospatial and Artificial Neural Network Applications." Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1310493197.
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Dillon, Kevin Alan. "Double-Crop Soybean Vegetative Growth, Seed Yield, and Yield Component Response to Agronomic Inputs in the Mid-Atlantic, USA." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/49380.
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Maximizing productivity and profitability are the primary reasons for double-cropping soybean with small grain in the Mid-Atlantic, USA. Reduced double-crop yield can be attributed to: delayed planting that results in a shortened growing season and less vegetative growth; later-maturing cultivars that terminate main stem growth after flowering and have less growth and nodes; less soil moisture and plant-available nutrients due to small grain uptake; greater air and soil temperatures during vegetative stages that reduce early-season growth; and more favorable conditions for disease development during pod and seed formation. Field experiments were conducted in 2012 and 2013 in eastern Virginia to 1) evaluate cultivar stem growth habit, seeding rate, seed-applied inoculant, starter nitrogen (N) applied at planting, and foliar fungicide on soybean vegetative growth, total N uptake (TNU), seed yield and quality, and yield components; 2) determine the effect of starter N rate, applied with and without inoculant, on soybean vegetative growth, TNU, seed yield and quality, and yield components; and 3) evaluate the response of maturity group (MG) IV and V soybean cultivars to foliar fungicide.
Greater seeding rates, inoculant, N, and fungicide typically were not required together to increase yield. Although cultivar interacted with other factors, early-maturing indeterminate 95Y01 yielded more than late-maturing determinate 95Y20 at 4 of 6 locations. Seeding rate interacted with other factors, but the greater seeding rate increased MG IV yield at 1 of 6 locations and decreased MG V yield at 2 of 6 locations. Starter N increased seed yield by 6 kg ha-1 per kg N applied until yield plateaued at 16 kg N ha-1, which continued to 31 kg N ha-1. When N rate was increased greater than 31 kg N ha-1, yield decreased. Fungicide increased yield for MG IV and V cultivars at 4 of 6 and 3 of 6 locations, respectively and prevented yield loss via mid- to late-season disease control, delayed leaf drop, and greater seed size. Optimum fungicide timing depended on environment and disease development. These data assisted in understanding agronomic inputs' combined or individual effects on double-crop soybean growth, canopy, N uptake, seed yield, and yield components.<br>Ph. D.
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Griffiths, Martyn Wynne. "Effects of late-season foliar applications of sulphur, and their interactions with nitrogen, on wheat yield and quality." Thesis, University of Wolverhampton, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.330296.
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