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Yield Prediction (yield + prediction)
Selected AbstractsPrediction of crop yield in Sweden based on mesoscale meteorological analysisMETEOROLOGICAL APPLICATIONS, Issue 4 2000Valentin L Foltescu This paper presents a prediction system for regional crop growth in Sweden, recently set up at SMHI (Swedish Meteorological and Hydrological Institute). The system includes a state-of-the-art crop growth model, WOFOST (WOrld FOod STudies) and inputs from meteorological mesoscale analysis. The simulated crops are spring barley, spring rape, oats and winter wheat, and the period of investigation is 1985,98. The simulated water-limited grain yield is used as a predictor in the yield prediction procedure. The technological time trend describing the yearly increase of the production level is accounted for as well. Yield prediction based on crop growth modelling is justified since the ability to forecast the yield is higher compared to that using the technological time trend alone. The prediction errors are of the order of 8 to 16%, with the lowest errors for winter wheat and spring barley. Copyright © 2000 Royal Meteorological Society [source] Yield prediction from digital image analysis: A technique with potential for vineyard assessments prior to harvestAUSTRALIAN JOURNAL OF GRAPE AND WINE RESEARCH, Issue 3 2004GREGORY M. DUNN Abstract Digital photographs were taken of four 1 m × 1 m portions of canopy of Cabernet Sauvignon grapevines, as they were being progressively de-fruited close to harvest. The program EasyAccess version 6.3 was used to select ,fruit' pixels by visually setting red, green and blue threshold values and tolerances for the first image and applying these to all other images. The program was then used to automatically count ,fruit' pixels and the total number of pixels for each image. Even though two hours separated the first and last photographs, the ratio of ,fruit' pixels to total image pixels explained 85% of the variation in yield (kg per linear m of fruiting wire) for all 16 vine × de-fruiting combinations. This improved to between 94 and 99% for individual portions of canopy. Implications from our present digital image analysis for future development of both automated and spatially aware methods to predict vineyard yield are discussed. [source] A Statistical Sediment Yield Prediction Model Incorporating the Effect of Fires and Subsequent Storm Events,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2008Jang Hyuk Pak Abstract:, Alluvial fans are continuously being developed for residential, industrial, commercial, and agricultural uses in southern California. Development and alteration of alluvial fans need to consider the possibility of mud and debris flows from upstream mountain watersheds affected by fires. Accurate prediction of sediment yield (or hyper-concentrated sediment yield) is essential for the design, operation, and maintenance of debris basins to safeguard properly the general populace. This paper presents a model for the prediction of sediment yields that result from a combination of fire and subsequent storm events. The watersheds used in this analysis are located in the foothills of the San Gabriel Mountains in southern California. A multiple regression analysis is first utilized to establish a fundamental statistical relationship for sediment yield as a function of relief ratio, drainage area, maximum 1-h rainfall intensity and fire factor using 45 years of data (1938-1983). In addition, a method for multi-sequence sediment yield prediction under fire conditions was developed and calibrated using 17 years of sediment yield, fire, and precipitation data for the period 1984-2000. After calibration, this model was verified by applying it to provide a prediction of the sediment yields for the 2001-2002 fire events in southern California. The findings indicate a strong correlation between the estimated and measured sediment yields. The proposed method for sequence sediment yield prediction following fire events can be a useful tool to schedule cleanout operations for debris basins and to develop an emergency response strategy for the southern California region where plentiful sediment supplies exist and frequent fires occur. [source] Allometric growth relationships of East Africa highland bananas (Musa AAA-EAHB) cv. Kisansa and MbwazirumeANNALS OF APPLIED BIOLOGY, Issue 3 2009K. Nyombi Abstract Highland bananas are an important staple food in East Africa, but there is little information on their physiology and growth patterns. This makes it difficult to identify opportunities for yield improvement. We studied allometric relationships by evaluating different phenological stages of highland banana growth for use in growth assessment, understanding banana crop physiology and yield prediction. Pared corms of uniform size (cv. Kisansa) were planted in a pest-free field in Kawanda (central Uganda), supplied with fertilizers and irrigated during dry periods. In addition, tissue-cultured plants (cv. Kisansa) were planted in an adjacent field and in Ntungamo (southwest Uganda), with various nutrient addition treatments (of N, P, K, Mg, S, Zn, B and Mo). Plant height, girth at base, number of functional leaves and phenological stages were monitored monthly. Destructive sampling allowed derivation of allometric relationships to describe leaf area and biomass distribution in plants throughout the growth cycle. Individual leaf area was estimated as LA (m2) = length (m) × maximum lamina width (m) × 0.68. Total plant leaf area (TLA) was estimated as the product of the measured middle leaf area (MLA) and the number of functional leaves. MLA was estimated as MLA (m2) = ,0.404 + 0.381 height (m) + 0.411 girth (m). A light extinction coefficient (k = 0.7) was estimated from photosynthetically active radiation measurements in a 1.0 m grid over the entire day. The dominant dry matter (DM) sinks changed from leaves at 1118 °C days (47% of DM) and 1518 °C days (46% of DM), to the stem at 2125 °C days (43% of DM) and 3383 °C days (58% of DM), and finally to the bunch at harvest (4326 °C days) with 53% of DM. The allometric relationship between above-ground biomass (AGB in kg DM) and girth (cm) during the vegetative phase followed a power function, AGB = 0.0001 (girth)2.35 (R2 = 0.99), but followed exponential functions at flowering, AGB = 0.325 e0.036(girth) (R2 = 0.79) and at harvest, AGB = 0.069 e0.068(girth) (R2 = 0.96). Girth at flowering was a good parameter for predicting yields with R2 = 0.7 (cv. Mbwazirume) and R2 = 0.57 (cv. Kisansa) obtained between actual and predicted bunch weights. This article shows that allometric relationship can be derived and used to assess biomass production and for developing banana growth models, which can help breeders and agronomists to further exploit the crop's potential. [source] A new second-moment closure approach for turbulent swirling confined flowsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 2 2003Pisi Lu Abstract An improved anisotropic model for the dissipation rate,,,of the turbulent kinetic energy (k), to be used together with a non-linear pressure-strain correlations model, is proposed. Experimental data from the open literature for two confined turbulent swirling flows are used to assess the performance of the proposed model in comparison to the standard , transport equation and to a linear approach to model the pressure-strain term that appears in the exact equations for the Reynolds-stress tensor. For the less strongly swirling flow the predictions show much more sensitivity to the ,transport equation than to the pressure-strain model. In opposition, for the more strongly swirling flow, the results show that the predictions are much sensitive to the pressure-strain model. Nevertheless, the improved ,transport equation together with the non-linear pressure strain model yield predictions in good agreement with experiments in both studied cases. Copyright © 2003 John Wiley & Sons, Ltd. [source] Forecasting the price of crude oil via convenience yield predictionsJOURNAL OF FORECASTING, Issue 7 2007Thomas A. KnetschArticle first published online: 14 NOV 200 Abstract The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield, which can be derived from the cost-of-carry relationship. In a recursive out-of-sample analysis, forecast accuracy at horizons within one year is checked by the root mean squared error as well as the mean error and the frequency of a correct direction-of-change prediction. For all criteria employed, the proposed forecasting tool outperforms the approach of using futures prices as direct predictors of future spot prices. Vis-à-vis the random-walk model, it does not significantly improve forecast accuracy but provides valuable statements on the direction of change. Copyright © 2007 John Wiley & Sons, Ltd. [source] Setting the absolute tempo of biodiversity dynamicsECOLOGY LETTERS, Issue 7 2007Andrew P. Allen Abstract Neutral biodiversity theory has the potential to contribute to our understanding of how macroevolutionary dynamics influence contemporary biodiversity, but there are issues regarding its dynamical predictions that must first be resolved. Here we address these issues by extending the theory in two ways using a novel analytical approach: (1) we set the absolute tempo of biodiversity dynamics by explicitly incorporating population-level stochasticity in abundance; (2) we allow new species to arise with more than one individual. Setting the absolute tempo yields quantitative predictions on biodiversity dynamics that can be tested using contemporary and fossil data. Allowing incipient-species abundances greater than one individual yields predictions on how these dynamics, and the form of the species-abundance distribution, are affected by multiple speciation modes. We apply this new model to contemporary and fossil data that encompass 30 Myr of macroevolution for planktonic foraminifera. By synthesizing the model with these empirical data, we present evidence that dynamical issues with neutral biodiversity theory may be resolved by incorporating the effects of environmental stochasticity and incipient-species abundance on biodiversity dynamics. [source] | |||||||||||||