Relevant bibliographies by topics / Yields

Academic literature on the topic 'Yields'

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Published: 4 June 2021
Last updated: 5 March 2023

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Journal articles on the topic "Yields"

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Villanueva-Mosqueda, Eduardo, and Michael J. Havey. "Genetic Analyses of Seed Yield in Onion." Journal of the American Society for Horticultural Science 126, no. 5 (September 2001): 575–78. http://dx.doi.org/10.21273/jashs.126.5.575.

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Development of two-way onion (Allium cepa L.) hybrids is difficult due to poor seed yields on inbred female parents. Seed yield of onion is affected by inbreeding depression and the seed-production environment. A standard diallel was used to estimate combining abilities for seed yield among seven inbred onion lines. Males and hybrids differed significantly (P < 0.05) for seed yields. Combinations of relatively high-by-high seed-yielding inbred parents were not always the best combinations; combinations of medium-by-medium or medium-by-high seed yielders also produced good F1 seed yielders. For the seven inbred lines, significant correlations (P < 0.05) were observed between mean seed yield per bulb and scape height. Parent-offspring regressions revealed no significant relationship between seed yields of randomly selected, open-pollinated bulbs and their S1 families. Results indicate that relative seed yields of individual bulbs after self-pollination cannot be used to predict seed yields of progeny families. However, the seed yield of inbred lines of onion may reflect the potential seed yield of F1 male-sterile lines.
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Tautges, Nicole, Claire Flavin, Thomas Michaels, Nancy Ehlke, John Lamb, Jacob Jungers, and Craig Sheaffer. "Rotating alfalfa with dry bean as an alternative to corn-soybean rotations in organic systems in the Upper Midwest." Renewable Agriculture and Food Systems 34, no. 1 (June 6, 2017): 41–49. http://dx.doi.org/10.1017/s1742170517000321.

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AbstractDry bean (Phaseolus vulgaris) can be grown as a local food source and as an alternative to soybean (Glycine max) to diversify organic crop rotations. To understand the benefits of diversification of organic cropping systems, the effects of preceding alfalfa (Medicago sativa) and corn (Zea mays) crops on yields of five dry bean types and one soybean type, and the effect of bean type on following spring wheat (Triticum aestivum) yields, were tested at four Minnesota locations. Dry bean and soybean yields following alfalfa were 25% greater than yields following corn at two of four locations, though bean yields following corn were greater at one location. A preceding alfalfa crop benefited bean yields at locations where hog manure or no manure was applied to corn, whereas bean yields following corn fertilized with cow manure were similar to or greater than bean yields following alfalfa. Among dry bean types, black bean yielded similarly to soybean at three of four locations, but dark red kidney bean consistently yielded 25–65% lower than soybean. Navy, pinto and heirloom dry bean types yielded similarly to soybean at two of four locations. Across locations, weed biomass was 3–15 times greater in dry bean than in soybean and dry bean yield response to weed competition varied among bean types. However, dry bean, regardless of the preceding crop, demonstrated the potential to produce yields comparable with soybean in organic systems and the substitution of dry bean for soybean did not affect subsequent wheat yields. More studies are needed to identify nitrogen fertility dynamics in organic systems as they relate to dry bean yield.
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HOEKSTRA, G. J., L. W. KANNENBERG, and B. R. CHRISTIE. "GRAIN YIELD COMPARISON OF PURE STANDS AND EQUAL PROPORTION MIXTURES FOR SEVEN HYBRIDS OF MAIZE." Canadian Journal of Plant Science 65, no. 3 (July 1, 1985): 471–79. http://dx.doi.org/10.4141/cjps85-068.

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The objective of this study was to compare yielding ability and competitive effects in pure stands and equal-proportion mixtures of maize hybrids. Seven maize (Zea mays L.) hybrids were grown for 2 yr in pure stand and in all equal-proportion, two-component mixtures at plant densities of 61 500 and 136 000 plants per hectare. In 1978, a year of severe moisture stress, mixtures yielded 6% more grain on average than expected on the basis of pure stand yields. Half of the mixtures yielded more than the pure stand yield of the high-yielding component; however, one mixture yielded significantly less than predicted based on pure stand yields. In 1979, mixtures yielded as expected based on pure stand yields. The yield difference between 1978 and 1979 for mixtures was less than the difference between pure stands indicating that mixtures were, on average, more consistent in performance across environments than their components. The yield advantage of mixtures in 1978, however, was too low to recommend growing blends as a production practice. Relative yields of individual hybrids were different in pure stands compared to mixtures. Furthermore, the order of hybrids ranked according to their pure-stand yields differed from the order based on yielding ability in mixtures. In general, a direct relationship existed between yielding ability in mixtures and competititve influence. Hybrids with a high average yield across mixtures yielded more in mixtures with low-yielding hybrids than in mixtures with high-yielding hybrids. Conversely, low-yielding hybrids produced less grain when in mixtures with a high-yielding hybrid than in mixtures with a low-yielding hybrid. However, the one hybrid which was consistently the most competitive was not the highest yielding under stress conditions.Key words: Blends, corn, grain yield, hybrid mixtures, population stress, Zea mays
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Kulla, L., J. Tutka, and R. Marušák. "Forest yield index and its applicability to the assessment of future forest yields." Journal of Forest Science 55, No. 1 (February 3, 2009): 41–50. http://dx.doi.org/10.17221/45/2008-jfs.

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The paper suggests and examines a simplified relative indicator of forest production, with special regard to possibilities of its use in projecting future forests. Forest yield index (<I>I</I><sub>Y</sub>), based on an economic parameter “value of final cutting yield” was proposed, and examined in the model territory of Kysuce in north-western Slovakia. The current values of final cutting yield, dependent on tree species, site index and the length of rotation period served as a basis for the assessment of expected yields. The possibilities and limitations of index applicability in long-term strategic forest management decision-making are discussed, considering the uncertainty of ecological and economic conditions during the long forest production cycle, as well as the complexity of tree species growth and production in the mixed forests, uneven aged forests and forests under climate change.
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Pelikán, J. "Yield evaluation of varieties from the world collection of birdsfoot trefoil (Lotus corniculatus L.)." Plant, Soil and Environment 48, No. 6 (December 11, 2011): 265–70. http://dx.doi.org/10.17221/4240-pse.

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In field trials in 1998&ndash;2000, ten varieties of the world collection of birdsfoot trefoil (Lotus corniculatus) were evaluated for herbage and hay yields. In all the years of testing yields from three cuttings and total annual production were evaluated. In 1999, seed yield was also recorded. As a&nbsp;control, alfalfa (Medicago sativa) variety was included in the experiment. The test varieties showed good productivity in the first and especially in the second year of testing, most of them exceeded alfalfa in herbage yield in individual cuttings and in total productions. As for hay yield, the differences were not so great. Local varieties showed very good productivity, predominantly in herbage yields. Of foreign varieties, the best herbage, hay and seed yielder was the Hungarian variety Puszta. There were no statistical differences in seed yield between the varieties. The yields were, however, relatively low.
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Jubinski, Daniel, and Amy F. Lipton. "Equity volatility, bond yields, and yield spreads." Journal of Futures Markets 32, no. 5 (May 26, 2011): 480–503. http://dx.doi.org/10.1002/fut.20521.

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Bevilaqua, Julia, Galina B. Hale, and Eric Tallman. "Corporate yields and sovereign yields." Journal of International Economics 124 (May 2020): 103304. http://dx.doi.org/10.1016/j.jinteco.2020.103304.

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Pilbeam, C. J., G. Duc, and P. D. Hebblethwaite. "Effects of plant population density on spring-sown field beans (Vicia faba) with different growth habits." Journal of Agricultural Science 114, no. 1 (January 1990): 19–33. http://dx.doi.org/10.1017/s0021859600070957.

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SUMMARYDeterminate varieties of Vicia faba are smaller and may require higher plant population densities than their conventional indeterminate counterparts to attain high yields. This hypothesis was examined at the University of Nottingham farm at Sutton Bonington, UK, and at INRA, Dijon, France in 1986 and 1987. The determinate varieties Ticol and TP667 and indeterminate M5.1 and Maris Bead were sown in the spring to give a range of densities of 10–100 plants/m2.Yields generally increased as population density increased. The optimum density for determinate varieties was higher than for indeterminate varieties. Indeterminate varieties yielded more than determinate varieties at all plant densities, perhaps because of their larger canopy. Seed yields were affected by year and location. Greater yields were associated with heavier seeds and more seeds per pod.Although several yield components, when expressed per unit area, were significantly correlated with seed yield, their coefficients of determination were never very large. This confirmed the plasticity of yield in field beans.
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Taylor, B. R., and J. Y. Chambi. "Sesame Agronomy in South-east Tanzania. I. Plant Population and Sowing Method." Experimental Agriculture 22, no. 3 (July 1986): 243–51. http://dx.doi.org/10.1017/s0014479700014411.

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SUMMARYField trials are described in which the seed yield response of row-sown sesame to increasing plant population was examined, and in which row-sowing was compared with broadcasting at different seed rates. Maximum yields were obtained at an intended 200 to 250 × 103 plants ha−1 but yields were not greatly affected by a wider range of populations. Broadcasting, the normal local practice, gave yields slightly higher than those from rows 50 cm apart, the un-thinned rate of 800 × 103 viable seeds sown ha−1 yielded as well as treatments thinned to the optimum population, and double this seed rate, unthinned, gave the lowest yields, especially in rows.
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Narwal, S. S., D. S. Dahiya, G. Singh, and D. S. Malik. "Response of maize cultivars to sowing in the winter." Journal of Agricultural Science 109, no. 2 (October 1987): 303–7. http://dx.doi.org/10.1017/s0021859600080722.

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SummaryIn a 2-year field study, all the maize cultivars tried (Partap-1 Ageti-76, Ganga-5 and DHM-103) produced similar length of ears and equivalent grain yields. However, Partap-1 and Ganga-5 produced greater 100-kernel weight and greater grain yield per ear but fewer ears per hectare than Ageti-76 and DHM-103. The yield attributes and grain yields of maize sown on 19 December, 29 December and 8 January were identical and were superior to those of the 19 January sowing. Maize sown on 19 December, 29 December and 8 January exhibited longer ears, more ears and fully developed kernels and thereby produced greater grain yields than the 18 January sowing.During 1983–4, in the 19 December and 29 December sowings all the cultivars gave identical grain yields. In the 8 January sowing Partap-1 and Ageti-76 produced similar yields and proved better than Ganga-5 and DHM-103. In the 18 January sowing Ageti-76, Ganga-5 and DHM-103 yielded more than Partap-1.
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Dissertations / Theses on the topic "Yields"

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Granados, Juan D. "Complexity yields to simplicity." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1314207325.

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Widodo. "The Effects of Spacings & Cultivars on Biological Yields, Yields, Component of Yield & Harvest Index of Green Bush Snap Bean (Phaseolus vulgaris L.)." TopSCHOLAR®, 1989. https://digitalcommons.wku.edu/theses/2967.

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The effects of cultivars and plant spacings on biological yield, seed yield, seeds per pod, average seed weight, and harvest index of beans (Phaseolus vulgaris L.) were studied in 1987 and 1988. Two cultivars, 'Blue Lake 27' and 'Kentucky Wonder 125' and four plant spacings -- 7, 14, 21, and 28 cm, constituted eight treatments that were arranged in a split-plot with four replications. Each experimental unit or hill consisted of five plants -- four in the corners and one in the center of a square. Spacings treatment were established by varying the distance between the center plant and the four corner plants. Corner plants provided competition; only the center plant was harvested for experimental data. The data were subjected to analysis of variance procedure for a split-plot design, assuming a fixed model. The cultivars had similar biological yield curves during the 1987 growing season and did not differ significantly for biological yield at the final harvest either year. Kentucky Wonder 125 produced significantly higher average seed weight and harvest index, but fewer seeds per pod, than did Blue Lake 274. In 1987, seed yield per plant was higher for Blue Lake 274 than for Kentucky Wonder 125; however, the cultivars did not differ significantly for seed yield per plant in 1988. Spacing treatment effects were not significant when expressed through seed yield per plant, seeds per pod, average seed weight, or harvest index. Spacings affected biological yield significantly in 1988, but not in 1987. The linear response of biological yield to spacing was positive and significant both years. The linear effect of spacings on pod yield was significant in 1988, but not in 1987. Drought conditions in 1987 and 1988 adversely affected bean growth and seed production. The experimental error, as evidenced by large coefficients of variation for treatment means, was unusually high. Consequently, some true cultivar and spacing effects may not have been detected.
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Graham, Allan Wayne. "Environmental Liabilities and Bond Yields." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/28937.

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Environmental remediation liabilities are generated primarily as a result of past actions by a firm. The most important of these liabilities for domestic U.S. firms are related to Superfund sites as designated by the Environmental Protection Agency (EPA). These liabilities are important for domestic firms because of their size, which is estimated to be approximately $300 billion (Congressional Budget Office 1994) and because of public concern for the environment. This study examines the relation among bond ratings, bond yields, and EPA-based estimates of contingent environmental remediation liabilities to test if the relationships hold as theory implies it would. Extant theory suggests that financial variables, such as environmental remediation liabilities, have incremental explanatory power beyond the information included in bond ratings for bond yield. The purpose of this study is to determine the importance of external estimates of a firm's contingent environmental liabilities for a firm's cost of debt. In addition, the manner in which a firm's contingent environmental liabilities are included in the costs of debt is examined in this study. The results of this study indicate that external estimates for environmental liabilities are associated with the bond ratings and bond yield for a data set of new bond issues collected from the period 1995 to 1997. Despite that firms are increasing their recognition of environmental liabilities, either due to regulatory pressure or other factors, the measures based on EPA data still have significant explanatory power. The results imply that firms are either still lagging in appropriate recognition or that the external measures proxy for amounts imputed by the capital markets for some probable unspecified future costs. The latter explanation is supported by additional evidence in this study that the largest monetary measure of the liability is the most significantly associated with bond ratings and bond yields. Further, the results indicate that the external estimates are incorporated in bond ratings as part of the firm's default risk and have no direct influence over bond yield beyond that included in the bond ratings. This implies that bond ratings are particularly important for any evaluation of investment in debt securities from firms that have contingent environmental liabilities.
Ph. D.
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Cook, Rebecca. "Chance Meeting Yields Research Bonanza." College of Agriculture, University of Arizona (Tucson, AZ), 1993. http://hdl.handle.net/10150/295741.

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Badyal, Jasvinder Pal Singh. "Exotic options with stochastic dividend yields." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286311.

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Shanks, Sarah M. "The Memory Yields: B.F.A. Thesis Exhibition." Ohio University Honors Tutorial College / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1401583720.

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Gonçalves, Júlia Alves Roque. "Yield gap explaining factors and solutions to improve yields in a maize farm in Portugal." Master's thesis, ISA, 2019. http://hdl.handle.net/10400.5/21289.

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Mestrado em Engenharia Agronómica / Instituto Superior de Agronomia. Universidade de Lisboa
Over the decades, it has been found that agricultural intensification, that is, the increase in production per hectare, is substantially urgent and necessary, justified by the observed and expected population increase and the impossibility of agricultural expansion. One of the methods for achieving this goal is the study and investigation of yield gaps, which may be explained by unfavorable soil and climate conditions, or less adequate input management. Given the socio-economic importance of maize crop in Portugal and the need for case studies that exemplify agricultural intensification methods, this dissertation aims to discover which are the reducing factors that justify the gap between the maximum and actual yields, known as yield gaps, which were analyzed between plots and years, and how large was the yield gap over the 10 years. Through a database of irrigation appropriations, nitrogen applications, sowing dates and climate data, collected over 10 years and provided by Milho Amarelo company, located in the Santarem region, other variables were calculated, such as degree-day accumulation, cultural evapotranspiration and intercepted radiation. These data were analyzed annually according to the whole cycle and according to different phenological phases (vegetative and reproductive). Once all variables were obtained and organized, statistical methods of bivariate and multivariate analysis were performed. The magnitude of yield gap was calculated according to the Approach 2 indicated by FAO 41. The results show that interaction of sowing dates with climatic conditions are in the nature of this deviation, with gap’s magnitude ranging from 5% to 20%, depending on the climatic conditions of the year
N/A
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Sampson, Helen G. (Helen Grace). "Biomass and protein yields, N2-fixation and N transfer in annual forage legume-barley (Hordeum vulgare L.) cropping systems." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68257.

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In this study, six annual legumes and the perennial, red clover (Trifolium pratense L.) were monocropped (MC) and intercropped (IC) with barley in a field study with three N levels, 0, 30 and 60 kg N ha$ sp{-1}$. At O kg N ha$ sp{-1}$, N$ sb2$-fixation and N transfer were estimated by the $ sp{15}$N isotope dilution (ID) method. At 60 kg N ha$ sp{-1}$, a direct $ sp{15}$N labelling method was employed to study N transfer. The hypotheses were that the annual species would be more productive within one growing season than red clover, that increased N levels would increase herbage dry matter (DM) and crude protein (CP), that the proportion of N derived from N$ sb2$-fixation in IC-legumes would be higher than that of MC-legumes and that within intercrops there would be evidence of N transfer. In neither year was the total DM yield of red clover, MC or IC, less than the rest of the legumes. In 1991, the total DM yield of intercrops responded to 30 kg N ha$ sp{-1}$; in neither year did the estimated total CP yield of MC-legumes or intercrops respond to N levels. Only in 1992 was there evidence of N$ sb2$-fixation and the proportion of N derived from fixation by IC-legumes was 145% higher than that of MC-legumes. Only the $ sp{15}$N direct labelling method gave evidence of N transfer, to associated legume and barley plants in 1991, and to associated legume plants in 1992.
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Smith, Matthew K. "Trend yields and the crop insurance program." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/13748.

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Master of Agribusiness
Department of Agricultural Economics
Allen M. Featherstone
Multiple Peril Crop Insurance (MPCI) is a federally subsidized crop insurance program designed to mitigate risk for farmers across the United States. Many changes in technology and weather have increased yields in recent years. This has caused some to argue for the crop insurance program to consider yield trends when setting yields for the producer. This thesis evaluates alternative Actual Production History (APH) methods for corn to determine differences in the methods and the resulting APH. The key issue to be evaluated is that a producer’s APH may not be reflective of their “yield goal.” The thesis examined how the APH can differ under alternative methods of calculating an APH. Some methods examined are currently used by the Risk Management Agency (RMA). Other methods are hypothetical alternatives. This study examines alternative methods on a national, county, and a farm level. This thesis demonstrates that adjusting APHs for yield trends provides a higher APH than an un-trended APH. The 7 Year Olympic Trended APH provides the highest APH in most cases for all the methods examined. The RMA Un-trended APH proved to provide the least yield on average for all methods examined. This demonstrates the importance of adjusting for yield trends to factor in agricultural technology advancements over time.
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Mitchell, Hal Lee. "Predicting Pallet Part Yields From Hardwood Cants." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/41288.

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Pallet cant quality directly impacts pallet part processing and material costs. By knowing the quality of the cants being processed, pallet manufacturers can predict costs to attain better value from their raw materials and more accurately price their pallets. The study objectives were 1) to develop a procedure for accurately predicting hardwood pallet part yield as a function of raw material geometry and grade, processing equipment, and pallet part geometry, 2) to develop a model for accurately predicting raw material costs for hardwood pallet parts as a function of yield, 3) to examine current pallet industry methods of determining hardwood cant quality, and 4) to develop and evaluate hardwood cant grading rules for use in the pallet industry. Yield studies were necessary to accurately quantify the relationship between yield and cant quality. Thirty-one yield studies were conducted throughout the Eastern United States at pallet mills producing pallet parts from hardwood cants. 47, 258 board feet of hardwood cants were graded, and the usable pallet part yield and yield losses were determined for each grade. Yield losses were separated into three components: kerf loss, dimension loss, and defect loss. Kerf and dimension losses are a function of raw material and part geometry and were calculated without regard to cant quality. Defect loss is dependant on cant quality and was calculated for each cant grade as a function of total yield, kerf loss, and dimension loss. Mathematical models were developed from twenty-eight mill studies to predict each yield loss component as a function of cant dimensions, grade, and orientation, cutting bill parameters, pallet part dimensions, and kerf. Dimension and kerf losses were predicted geometrically. Regression analysis was used to predict defect loss. Results indicated that these models accurately predicted the total yield of usable pallet parts and pallet part material costs as a function of cant quality and price. Results also indicated that the pallet industry's current method of counting the number of "bad" ends per cant bundle to determine cant quality is not adequate. The effectiveness of the proposed cant grading rules was determined by grading cants and analyzing the cant grade distributions and corresponding pallet part yields. The grade rules produced statistically different quality divisions between grades. However, a more practical single cant grade based on the minimum quality for the proposed grade 2 rules is recommended.
Master of Science
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Books on the topic "Yields"

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Binsbergen, Jules H. van. Equity yields. Cambridge, MA: National Bureau of Economic Research, 2011.

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Fageria, N. K. Maximizing crop yields. New York: Marcel Dekker, 1992.

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Ramlau-Hansen, Henrik. Yields on lottery bonds. Copenhagen: Laboratory of Actuarial Mathematics, University of Copenhagen, 1987.

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A duke never yields. New York: Berkley Sensation, 2013.

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Adedeji, Abimbola. Determinants of eurobond yields. Edinburgh: University of Edinburgh, Department of Business Studies, 1991.

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A duke never yields. London: Eternal Romance, 2013.

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Witteveen, Ann. Investigation into the surplus producing areas of southern Sudan. [Nairobi: WFP-TSU, 2001.

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R, Hazell P. B., International Food Policy Research Institute., and Deutsche Stiftung für Internationale Entwicklung., eds. Summary proceedings of a workshop on cereal yield variability. Washington, D.C: International Food Policy Research Institute, 1986.

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Rickard, John. The cocktail problem: The relationship between composite yield and component yields. Melbourne: University of Melbourne. Graduate School of Management, 1987.

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Ramdane, Dris, and Jain S. Mohan, eds. Production practices and quality assessment of food crops. Dordrecht: Kluwer Academic, 2004.

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Book chapters on the topic "Yields"

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Ploeg, Jan Douwe van der. "Yields." In Peasants and the Art of Farming, 89–124. Rugby, Warwickshire, United Kingdom: Practical Action Publishing, 2013. http://dx.doi.org/10.3362/9781780448763.005.

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Inman-Bamber, Geoff. "Sugarcane Yields and Yield-Limiting Processes." In Sugarcane: Physiology, Biochemistry, and Functional Biology, 579–600. Chichester, UK: John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118771280.ch21.

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Pieri, Christian J. M. G. "Sustainable Yields." In Fertility of Soils, 119–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84320-4_13.

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Isaac, David, and Terry Steley. "Equated Yields." In Property Valuation Techniques, 47–61. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-21573-7_5.

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Isaac, David, and Terry Steley. "Equivalent Yields." In Property Valuation Techniques, 72–81. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-21573-7_7.

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Prantzos, Nikos. "Stellar Yields." In Encyclopedia of Astrobiology, 1596. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_1514.

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Shapiro, Eric, David Mackmin, and Gary Sams. "Property yields." In Modern Methods of Valuation, 126–37. Twelfth edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019.: Estates Gazette, 2019. http://dx.doi.org/10.1201/9781315145419-8.

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Khaliq, Abdul, Amir Shakeel, Muhammad Kashif, and Ghulam Mustafa. "Stagnant Yields." In Developing Sustainable Agriculture in Pakistan, 283–310. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351208239-15.

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Pieri, Christian J. M. G. "Yields in Project Areas." In Fertility of Soils, 61–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84320-4_7.

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Isaac, David, and Terry Steley. "Interest Rates and Yields." In Property Valuation Techniques, 39–46. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-21573-7_4.

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Conference papers on the topic "Yields"

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BACK, JOHN. "Pion yields." In 10th International Workshop on Neutrino Factories, Super beams and Beta beams. Trieste, Italy: Sissa Medialab, 2009. http://dx.doi.org/10.22323/1.074.0084.

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Pond, Andrew D. "Predicting mask yields through the use of a yield model." In 14th Annual BACUS Symposium on Photomask Technology and Management, edited by William L. Brodsky and Gilbert V. Shelden. SPIE, 1994. http://dx.doi.org/10.1117/12.195828.

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Lee, Chad. "Increasing soybean yields." In Proceedings of the 24th Annual Integrated Crop Management Conference. Iowa State University, Digital Press, 2013. http://dx.doi.org/10.31274/icm-180809-109.

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"Analysis of Valuation Yields." In 5th European Real Estate Society Conference: ERES Conference 1998. ERES, 1998. http://dx.doi.org/10.15396/eres1998_184.

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"Forecasting UK Office Yields?" In 9th European Real Estate Society Conference: ERES Conference 2002. ERES, 2002. http://dx.doi.org/10.15396/eres2002_114.

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Adamo, D. A., S. Fabrizi, and M. G. Vergati. "A Light Functional Dimension Estimation Model for Software Maintenance." In 2007 IEEE International Conference on Exploring Quantifiable IT Yields (EQUITY). IEEE, 2007. http://dx.doi.org/10.1109/equity.2007.1.

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Labrujere, George, Hans de Weme, and Adri van der Wurff. "Life expectancy: managing the IT portfolio of a pension administrator." In 2007 IEEE International Conference on Exploring Quantifiable IT Yields (EQUITY). IEEE, 2007. http://dx.doi.org/10.1109/equity.2007.10.

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Tijdink, Ton, and Eric Nieuwland. "Measuring the business value of availability." In 2007 IEEE International Conference on Exploring Quantifiable IT Yields (EQUITY). IEEE, 2007. http://dx.doi.org/10.1109/equity.2007.11.

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Curley, Martin, and Jim Kenneally. "Methods and Metrics to improve the Yield of IT using the IT-CMF - an Intel Case Study." In 2007 IEEE International Conference on Exploring Quantifiable IT Yields (EQUITY). IEEE, 2007. http://dx.doi.org/10.1109/equity.2007.12.

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Port, Dan, Rick Kazman, Haruka Nakao, and Masa Katahira. "Practicing What is Preached: 80-20 Rules for Strategic IV&V Assessment." In 2007 IEEE International Conference on Exploring Quantifiable IT Yields (EQUITY). IEEE, 2007. http://dx.doi.org/10.1109/equity.2007.13.

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Reports on the topic "Yields"

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van Binsbergen, Jules, Wouter Hueskes, Ralph Koijen, and Evert Vrugt. Equity Yields. Cambridge, MA: National Bureau of Economic Research, September 2011. http://dx.doi.org/10.3386/w17416.

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A.C.Wahl. Systematics of Fission-Product Yields. Office of Scientific and Technical Information (OSTI), May 2002. http://dx.doi.org/10.2172/809574.

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A.C. Wahl. Systematics of Fission-Product Yields. Office of Scientific and Technical Information (OSTI), May 2002. http://dx.doi.org/10.2172/809946.

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Forcella, Frank, Russell W. Gesch, Gary B. Amundson, and Dean H. Peterson. Cuphea Yields in Iowa, 2002. Ames: Iowa State University, Digital Repository, 2003. http://dx.doi.org/10.31274/farmprogressreports-180814-1143.

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Forcella, Frank, Russell W. Gesch, Gary B. Amundson, and Dean H. Peterson. Cuphea Yields in Iowa, 2002. Ames: Iowa State University, Digital Repository, 2003. http://dx.doi.org/10.31274/farmprogressreports-180814-1288.

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Forcella, Frank, Russell W. Gesch, Gary B. Amundson, and Dean H. Peterson. Cuphea Yields in Iowa, 2002. Ames: Iowa State University, Digital Repository, 2003. http://dx.doi.org/10.31274/farmprogressreports-180814-877.

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Tonchev, A., J. Silano, A. Ramirez, and R. Malone. Energy Dependent Fission Product Yields. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1884622.

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Green, D. Effect of inert material on ZZ mass resolution for H yields ZZ yields eeee. Office of Scientific and Technical Information (OSTI), April 1991. http://dx.doi.org/10.2172/5909271.

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Gritsan, A. Polarization Puzzle in B {yields} {phi} K* and Other B {yields} VV at BABAR. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/833099.

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Cavigelli, Michel. Mid-Atlantic Corn and Soybean Yields Show Great Variability in Response to Precipitation during Critical Growth Stages. USDA Northeast Climate Hub, May 2018. http://dx.doi.org/10.32747/2018.6892663.ch.

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Abstract:
The mid-Atlantic coastal plain, where the FSP is located, has higher than average variability in corn and soybean yields compared to the most productive agricultural regions in the US. Precipitation is the primary driver of crop yield variability in this region and drought is often responsible for low yields.
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