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Literatura académica sobre el tema "Wheat Yield"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 9 de junio de 2025

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Artículos de revistas sobre el tema "Wheat Yield"

1

Terzić, Dragan, Vera Đekić, Jelena Milivojević, Snežana Branković, Vesna Perišić, Vladimir Perišić, and Dragoslav Đokić. "Yield components and yield of winter wheat in different years of research." Biologica Nyssana, Journal of Biological Sciences 9, no. 2 (January 13, 2019): 119–31. https://doi.org/10.5281/zenodo.2538604.

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Field trial with wheat varieties Perfekta, KG 56S, Aleksandra and Vizija was set on vertisol-type soil during the vegetation season 2010/11 and 2011/12. The aim of the research was to analyse the yield and grain yield components in four varieties of wheat cultivated on acid soil. The highest values of yield components and grain quality were established in the year with moderate temperatures and high precipitation in the vegetation year 2010/11. The KG 56S and Vizija varieties had the highest yield of grain, the highest number of plants and spikes per m2. The Perfekta variety showed the highest 1000 grain weight and grain weight per spike. The highest number of grains in the spike and the lowest average yield of grain during the research were recorded for the variety Aleksandra. A significant positive correlation between grain yield and grain weight per spike, the number of grains in the spike and the number of plants per m2 were established, as well as between the 1000 grain weight and the number of grains in the spike and the grain weight per spike.  

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2

ASHOK, TIWARI, N. TIWARI K., and N. PATHAK A. "Potassium for Yield Improvement of Wheat." Journal of Indian Chemical Society Vol. 71, May 1994 (May 31, 1994): 273–75. https://doi.org/10.5281/zenodo.5894773.

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Department of Sotl Science and Agricultural Chemistry, C. S Azad University of Agriculture and Technology, Kanpur-208 002 <em>Manusript received 10 April 1993. accepted 30 June 1993</em> Potassium for Yield Improvement of Wheat

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3

Altay, F., and N. Bolat. "Effect of soilborne wheat mosaic virus on winter wheat yield and yield components." Acta Agronomica Hungarica 52, no. 3 (November 1, 2004): 309–17. http://dx.doi.org/10.1556/aagr.52.2004.3.12.

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Soil-borne wheat mosaic virus (SBWMV) is an important disease of wheat production areas throughout the world, causing a great reduction in wheat and barley yields. The most effective way of controlling the disease is the use of resistant varieties in infested areas. In this study, the effects of SBWMV on yields and some yield components of eight susceptible, one moderately susceptible/resistant and nine resistant varieties were evaluated using data from 9 virus-infested and 6 non-infested sites in Eskisehir, Turkey over 6 years. The susceptible varieties yielded 5.35% more than resistant varieties in non-infested sites, while they gave 28.98% lower yield in infested sites. Significant yield loss differences were observed between the varieties in infested sites. Decreases were also observed in yield components at various levels. This study showed that SBWMV is an important disease, which survives in soil for long periods and causes significant yield decreases in wheat. Recently developed varieties have good resistance to the disease and are recommended to farmers in infested areas. Abbreviations: SBWMV, soil-borne wheat mosaic virus

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4

Kobus, Paweł. "Modelling wheat yields variability in Polish voivodeships." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 10, no. 3 (September 30, 2010): 33–40. http://dx.doi.org/10.22630/prs.2010.10.3.30.

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The paper presents an analysis of wheat yields variability in the voivodeships of Poland. The main aim of the study was to find out what are the statistical relationships between the wheat yield variability and the following factors: arable area, size of wheat production area, share of arable land used for wheat production, land quality and average yield. For that purpose a multiple linear regression was applied. It was found out that the detected spatial autocorrelation of wheat yields variability measured by standard deviations can be explained in 75% by the fitted model. Two of the considered variables showed a significant negative effect on this variability: the logarithm of arable area and the land quality, while the other two: the average wheat yield and the wheat production area displayed a significant positive effect on the variability. The effect of share of arable land used for wheat production itself was not significant.

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5

Asthir, Bavita, Shashi Bala, and Navtej Singh Bains. "Effect of Terminal Heat Stress on Yield and Yield Attributes of Wheat." Indian Journal of Applied Research 4, no. 6 (October 1, 2011): 1–2. http://dx.doi.org/10.15373/2249555x/june2014/1.

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6

Hannah, MC, and GJ O'Leary. "Wheat yield response to rainfall in a long-term multi-rotation experiment in the Victorian Wimmera." Australian Journal of Experimental Agriculture 35, no. 7 (1995): 951. http://dx.doi.org/10.1071/ea9950951.

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Seventy-six years of wheat yield data from a long-term rotation experiment at Dooen in the Victorian Wimmera were analysed to describe the response of wheat yield to seasonal rainfall, crop sequence, and time. Wheat yields from 7 different 1- to 4-course rotations involving wheat, barley, oat, field pea, grass pasture and fallow were compared as a function of growing-season (May-November) rainfall. The field layout had no within-year replication, but each phase of each rotation was represented once in each year. An approximate quadratic response of wheat yield to both current year and previous year May-November rainfall was observed for each rotation. Previous year May-November rainfall boosted wheat yields grown on fallow, but decreased the yield of wheat grown on field pea or wheat stubble. Highest wheat yields followed fallow preceded by pasture, high yields followed fallow preceded by a cereal, moderate yields followed field pea, and low yields occurred for continuous wheat. Long-term trends in wheat yields adjusted for rainfall depended on crop sequence and fluctuated more in the non-fallow, 3-course rotations. Over the 76 years, average yield declined in all rotations except the continuous wheat, which was always low, but there was evidence that yield of all continuous cropped rotations had increased during the last 2 decades.

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7

Budzyński, W. S., K. Bepirszcz, K. J. Jankowski, B. Dubis, A. Hłasko-Nasalska, M. M. Sokólski, J. Olszewski, and D. Załuski. "The responses of winter cultivars of common wheat, durum wheat and spelt to agronomic factors." Journal of Agricultural Science 156, no. 10 (December 2018): 1163–74. http://dx.doi.org/10.1017/s0021859619000054.

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AbstractA field experiment with the 35–1 fractional factorial design and five factors (k = 5) at three levels (s = 3) was performed in 2007–2010 at the Agricultural Experiment Station in Bałcyny, north-eastern (NE) Poland. The results of the experiment carried out under the agro-ecological conditions of NE Poland confirmed the high yield potential of common wheat and satisfactory yield potential of spelt and durum wheat. On average, durum wheat and spelt yields were 2.14 and 2.55 t/ha lower, respectively, than common wheat yields. Sowing date was not correlated with the yields of analysed Triticum species. Seed rate (350, 450 and 550 seeds/m2) had no significant influence on the grain yield of winter cultivars of common wheat, durum wheat and spelt. Common wheat cv. Oliwin and durum wheat cv. Komnata were characterized by the highest yields in response to nitrogen (N) fertilizer rates calculated based on the Nmin content of soil. An increase in the spring fertilizer rate by 40 kg N/ha in excess of the balanced N rate was not justified because it did not induce a further increase in the grain yield of common wheat and durum wheat. The grain yield of spelt cv. Schwabenkorn continued to increase in response to the highest rate of N fertilizer in spring (40 kg N/ha higher than the optimal rate). Intensified fungicide treatments improved grain yield in all Triticum species.

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8

Sweeney, G., RS Jessop, and H. Harris. "Yield and yield structure of triticales compared with wheat in northern New South Wales." Australian Journal of Experimental Agriculture 32, no. 4 (1992): 447. http://dx.doi.org/10.1071/ea9920447.

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The yields and yield structure of cultivars of triticales and bread wheats (with a range of phasic development patterns in both species) were compared in 2 field experiments at Narrabri in northern New South Wales. The experiments were performed on a grey cracking clay soil with irrigation to prevent severe moisture stress. Triticales, both early and midseason types, appeared to have reached yield parity with well-adapted wheat varieties. Meaned over the 2 experiments and all sowings, the triticales yields were 19% greater than the bread wheats. Triticales were generally superior to wheat in all components of yield of the spike (1000-grain weight, grain number/spikelet and spikelet number/spike), whilst the wheats produced more spikes per unit area. The triticales also had higher harvest indices than the wheats. The results are discussed in relation to the overall adaptability of triticale for Australian conditions.

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9

Jan, Křen, Houšť Martin, Tvarůžek Ludvík, and Jergl Zdeněk. "Are intensification and winter wheat yield increase efficient?" Plant, Soil and Environment 63, No. 9 (September 26, 2017): 428–34. http://dx.doi.org/10.17221/482/2017-pse.

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The results of small-plot field trials of international comparisons of a series of crop management practices for winter wheat grown during 2014–2016 on fertile soils of Central Moravia were assessed. The objective of the experiments was to obtain the highest gross margin (GM), which is the difference between revenues and direct costs. The analyses showed that an optimal level of inputs and costs for obtaining the highest GM could exist. In the assessed series of crop management practices, the optimum input costs corresponded to 11 000–12 000 CZK/ha and 6–9 input measures. At high levels of grains (above 10 t/ha), higher values of GM were obtained by increased efficiency of inputs, but not by increasing their amount to maximize the yields. This indicates the multifunctional and synergic effects of production factors, which can be used at the so-called ecological intensification. Optimizations of inputs can be obtained rather by crop protection than by crop nutrition, which means rather in protection of high yields than in their maximization. Under field conditions, soil and plant processes affected by weather cannot be controlled. Therefore, optimisation of production factors is based both on scientific findings and practical agronomic experience. That is why a universal crop management practice with increased economic and ecological effects cannot be practically proposed.

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10

Hu, Naiyue, Chenghang Du, Wanqing Zhang, Ying Liu, Yinghua Zhang, Zhigan Zhao, and Zhimin Wang. "Did Wheat Breeding Simultaneously Improve Grain Yield and Quality of Wheat Cultivars Releasing over the Past 20 Years in China?" Agronomy 12, no. 9 (September 5, 2022): 2109. http://dx.doi.org/10.3390/agronomy12092109.

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Grain yield and quality of wheat are both important components for food security. Great effort has been made in the genetic improvement of wheat grain yield in China. However, wheat grain quality (i.e., protein concentration and protein quality) has received much less attention and is often overlooked in efforts to improve grain yield. A timely summary of the recent process of wheat breeding for increasing yield and quality (which can be used to guide future breeding strategies) is essential but still lacking. This study evaluated the breeding efforts on grain yield and grain quality of 1908 wheat varieties in China over the past two decades, from 2001 to 2020. We found wheat yields show a 0.64–1.03% annual growth in the three-dominant wheat-growing regions in China. At the same time, there was no significant decrease in wheat protein concentration. Genetic yield potential was increased, and the genetic yield gap was closed. High grain yields and better quality can likely be achieved simultaneously by genomic selection in future wheat breeding.

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Tesis sobre el tema "Wheat Yield"

1

Dick, G., J. Harper, L. Moore, and M. Ottman. "Effect of Russian Wheat Aphid on Durum Wheat Yield." College of Agriculture, University of Arizona (Tucson, AZ), 1988. http://hdl.handle.net/10150/200817.

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2

Zubaidi, Akhmad. "Growth and yield of durum and bread wheat." Title page, contents and summary only, 1996. http://web4.library.adelaide.edu.au/theses/09A/09az93.pdf.

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Bibliography: leaves 148-160. A series of experiments was conducted to examine the growth and nutrient uptake of durum and bread wheat at a number of sites in South Australia. The experiments examined response to water stress, the pattern of root and shoot growth, soil water extraction and nutrient uptake among a range of adapted bread wheat and durum wheat cultivars.

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3

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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4

Torofder, Golam. "Manipulating wheat yield in semi-arid environments." Thesis, University of Aberdeen, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394451.

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Findings from a number of recent glasshouse studies are reported and their relevance to wheat production practices in Bangladesh is discussed. It was found that application of large amounts of urea gave highest grain yield when the total amount of urea was added immediately after irrigation following germination. The same amount of urea applied before irrigation or in smaller doses throughout the growing season gave lower yield and resulted in higher post-harvest concentrations of soil nitrate. Reducing the total urea application to one quarter of the typical maximum reported value, did not cause a reduction in yield and this could be achieved with only one occasion of irrigation (as opposed to two) following germination. The findings confirm the recommended dosage of urea (typically 250 kg urea ha<sup>-1</sup>) and indicate the importance of applying urea after irrigation to maximise yield and minimise post-harvest soil nitrate concentrations. Adding a nitrate fertiliser as opposed to the same amount of urea-N did not result in a significant yield increase. The results indicate that application of urea-N following irrigation results in a rapid availability of soil N for plant uptake. Where severe soil drying occurs in the upper rooting zone, grain field was drastically reduced. This occurred even where longer roots had access to non-limiting amounts of water and nutrients. It was found that roots in the drying soil produced the plant hormone abscisic acid (ABA) and that this had a likely causal significance in decreasing yield. ABA was also produced in plants with ammonium- as opposed to nitrate nutrition and this was also associated with reduced yield. It was concluded that breeding for deep rooting alone would be insufficient to attain high yield if the upper part of root system was exposed to severe soil water deficit. Breeding of deep rooting in combination with a decreased sensitivity of stomatal closure to ABA, is an attractive possibility for plant and yield improvement for semi-arid zones. In the interim, current measures of tillage and mulching that enhance the water content of the upper rooting zone should be encouraged. Such measures are likely to counter the potential ABA-induced inhibition of yield associated with partial root dehydration and incomplete nitrification of soil ammonium.

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5

Misailidis, Nikiforos. "Understanding and predicting alcohol yield from wheat." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/understanding-and-predicting-alcohol-yield-from-wheat(845cbadd-5825-488e-94e7-160c60b2ef0d).html.

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Bioethanol is a promising renewable biofuel and wheat is currently the main candidate asthe feedstock for its production in the UK context. The quality of the numerous varieties ofwheat developed in the past by plant breeders has been well examined in terms of bread, biscuitand pasta producing industries. In general, the end-use quality determination of wheat in termsof alcohol yield is less investigated. This work focused on understanding and predicting thealcohol yield from wheat according to its physical, physicochemical and chemicalcharacteristics. The research ran alongside the GREEN Grain project and utilised its wheatsamples, which consist of a range of wheat varieties, agronomic regimes and growing sitesfrom four harvests years 2005-2008. The combined dataset consists of a diverse range ofchemical, physicochemical and physical characteristics of the GREEN Grain wheats. An initial multivariate analysis (PCA) indicated that the first principal component, whichexplains most of the variability of the wheat characteristics, is related with the classification ofwheat as hard or soft. High alcohol yielding wheats typically have high starch, mealiness andalbumin+globulin fraction, and also low protein, gliadin fraction and hardness. They also havelarger and more spherical kernels. Analysis of Variance (ANOVA) was applied in order to identify differences between thevarieties, the sites and the application or not of N fertiliser. The ANOVA showed that theapplication of N fertiliser increases all the protein components, although it increases the Gliadinand the LMW glutenins more. N fertiliser also yields smaller (TGW, width, depth) and moreelongated kernels. High alcohol yielding varieties tend to be softer with lower protein andlarger and more spherical kernels. This consistent variability allowed prediction of the alcoholyield based on easily measured parameters. The following model, based on the SKCS reportedvalues plus protein, could predict the alcohol yield with an R2 of about 78%:Alcohol yield = 466.62 - 5.07 × Protein - 0.21 × hardness + 11.6 × diameter ±6.94 l/dry tonIt is frequently hypothesised that larger and more rounded kernels produce more alcoholbecause they have a smaller relative amount of the unfermentable outer layers. In an effort totest this hypothesis, the pericarp thicknesses and the crease characteristics of the wheat sampleswere measured. It was found that pericarp thickness and crease dimensions vary with kernelsize, with significant differences between varieties. A physical model was developed thatconsiders these differences and calculates the endosperm to non-endosperm ratio. None of thevariables obtained by the physical model could be related to alcohol yield. The SKCS fundamental data were further analysed in an effort to improve the alcoholyield predictability. It was found that the averaged Crush Response Profiles are morereproducible than the hardness index itself. It was shown that the initial peak does not occurbecause of the "shell" (i.e. the bran layers) as suggested in the literature, but because of thecrease. Examination of the effects of moisture content on the aCRPs showed that their 1stquarter is equivalent to the stress-strain plots of dedicated rheological tests. The remaining partsof the curve relate to the post-failure behaviour of the kernels and with hardness as used incereal science. The aCRP parameters could improve the alcohol yield predictability of theGREEN Grain wheats to an R2 of about 82.3% and a standard error of the regression of6.3 l/dry ton. Further standardisation and calibration with respect to the moisture content and tothe size of the kernels could improve the predictions even further. Textural testing of cereals is constrained by the complexity of the wheat kernel structureand exacerbated by the between-kernel variation. The current work has demonstrated howSKCS data can be interpreted more insightfully in order to improve end-use quality predictions. The aCRP parameters clearly contain rheological information about wheats. Further research toestablish their examination by more standardised methodologies will allow effectiveinvestigation of connections between the rheological properties, chemical characteristics,processing behaviour and end-use quality prediction of wheat.

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6

Farr, Chuck. "Yield Requirements of Non-Premium Durum Wheat." College of Agriculture, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/200542.

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Grotenhuis, Timothy P. "Superoptimal CO2 Reduces Seed Yield in Wheat." DigitalCommons@USU, 1996. https://digitalcommons.usu.edu/etd/6747.

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Although projected terrestrial CO2 levels will not reach 1000 μmol moI-1 (0.1%) for many decades, CO2 levels in growth chambers and greenhouses routinely exceed that concentration. CO2 levels in life support systems in space can exceed 10,000 μmol moI-1 (1%) CO2. Numerous studies have examined CO2 effects up to 1000 μmol mol-1, but theoretical and some experimental evidence indicates that the beneficial effects of CO2 continue past 1000 μmol mol-1 and are near-optimal for wheat at about 1200 μmol mol-1. We studied the effects of near-optimal and superoptimal CO2 levels (>1200 μmol mol-1) on yield of two cultivars of hydroponically grown wheat in 12 trials. Increasing CO2 from suboptimal to near-optimal (350 to 1200 μmol mol-1) increased vegetative growth by 25% and seed yield by 15% in both cultivars. Yield increases were primarily the result of an increased number of heads m-2. Further elevation of CO2 to 2500 μmol mol-1reduced seed yield by 22% in cv. 'Veery-10' and by 15% in cv. 'USU-Apogee'. Superoptimal CO2 did not decrease the number of heads m-2, but reduced seeds per head by 10% and mass per seed by 11%. CO2 toxicity occurred over a wide range of light levels. Subsequent trials revealed that superoptimal CO2 in the 2 weeks before and after anthesis mimicked the effect of constant superoptimal CO2. Furthermore, near-optimal CO2 in the 2 weeks before and after anthesis mimicked the effect of constant near-optimal CO2. Nutrient concentration of leaves and heads was not affected by CO2. The yield decreases may be a response mediated by ethylene.

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Ottman, Michael J. "Wheat and barley varieties for Arizona, 2017." College of Agriculture, University of Arizona (Tucson, AZ), 2017. http://hdl.handle.net/10150/625860.

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Ottman, Michael J. "Wheat and barley varieties for Arizona, 2016." College of Agriculture, University of Arizona (Tucson, AZ), 2016. http://hdl.handle.net/10150/625421.

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Sloane, David. "Early vigour : its role in enhancing the productivity of wheat grown in South Australia /." Title page, contents and abstract only, 1999. http://web4.library.adelaide.edu.au/theses/09AFP/09afps634.pdf.

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Libros sobre el tema "Wheat Yield"

1

United States. Agricultural Research Service., ed. ARS wheat yield project. [Beltsville, Md.]: The Service, 1985.

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2

AGRICULTURE, US DEPARTMENT OF. 2004 wheat objective yield survey interviewer's manual. Washington, D.C: U.S. Dept. of Agriculture, National Agricultural Statistics Service, Agricultural Statistics Board, 2004.

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AGRICULTURE, US DEPARTMENT OF. 2001 wheat objective yield survey interviewer's manual. [Washington, D.C.?: U.S. Dept. of Agriculture, 2001.

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4

Davies, Samuel. Soybean and wheat crops: Growth, fertilization, and yield. Hauppauge, NY: Nova Science Publishers, 2009.

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5

Smith, Edward L., ed. Genetic Improvement in Yield of Wheat. Madison, WI, USA: Crop Science Society of America and American Society of Agronomy, 1986. http://dx.doi.org/10.2135/cssaspecpub13.

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Braun, H. J., M. P. Reynolds, and J. Pietragalla. International symposium on wheat yield potential: Challenges to international wheat breeding. Edited by International Maize and Wheat Improvement Center. Mexico: CIMMYT, 2008.

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7

Dumanski, J. Identification of crop production risk areas in Manitoba based on agroecological resources. [Ottawa]: Research Branch, Agriculture Canada, 1992.

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Smiley, Richard W. Plant-parasitic nematodes affecting wheat yield in the Pacific Northwest. [Corvallis, Or.]: Oregon State University Extension Service, 2005.

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Smiley, Richard W. Plant-parasitic nematodes affecting wheat yield in the Pacific Northwest. [Corvallis, Or.]: Oregon State University Extension Service, 2005.

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H, Satorre Emilio, and Slafer Gustavo A. 1960-, eds. Wheat: Ecology and physiology of yield determination. New York: Food Products Press, 1999.

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Capítulos de libros sobre el tema "Wheat Yield"

1

Westcott, B. "Yield assessment." In Wheat Breeding, 339–68. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3131-2_12.

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Foulkes, M. John, Gemma Molero, Simon Griffiths, Gustavo A. Slafer, and Matthew P. Reynolds. "Yield Potential." In Wheat Improvement, 379–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_21.

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AbstractThis chapter provides an analysis of the processes determining the yield potential of wheat crops. The structure and function of the wheat crop will be presented and the influence of the environment and genetics on crop growth and development will be examined. Plant breeding strategies for raising yield potential will be described, with particular emphasis on factors controlling photosynthetic capacity and grain sink strength.

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Reis, Erlei Melo, Carlos A. Medeiros, and Marta M. Casa Blum. "Wheat Yield As Affected by Diseases." In Wheat, 229–38. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-12.

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Froud-Williams, Robert J. "Wheat Yield As Affected by Weeds." In Wheat, 161–82. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-10.

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Frederick, James R., and Philip J. Bauer. "Physiological and Numerical Components of Wheat Yield." In Wheat, 45–65. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-4.

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Borghi, Basilio. "Nitrogen As Determinant of Wheat Growth and Yield." In Wheat, 67–84. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-5.

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Richards, Richard A. "Drought." In Wheat Improvement, 417–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_23.

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AbstractEstablished breeding methods for wheat in dry environments continue to make gains. It will remain the cornerstone for wheat improvement. This Chapter discusses proven methods to make additional gains. It discusses a way to benchmark yield potential in dry environments and how this can be used to determine whether unexpected agronomic or genetic factors are limiting yields. It examines opportunities, advantages and disadvantages of trait-based selection methods for dry environments, and it presents a framework by which important traits can be selected. Both high throughput and marker-based methods of selection are examined for their success and feasibility of use in breeding. It also highlights the importance of agronomic approaches in combination with breeding to continue to improve yield potential in water limited environments. Finally, the elements of success of translation from research to the delivery of new varieties is examined.

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Slafer, Gustavo A., Jose L. Araus, and Richard A. Richards. "Physiological Traits That Increase the Yield Potential of Wheat." In Wheat, 379–415. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-21.

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Graybosch, Robert, Harold E. Bockelman, Kimberly A. Garland-Campbell, David F. Garvin, and Teshome Regassa. "Wheat." In Yield Gains in Major U.S. Field Crops, 459–87. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub33.c16.

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Satorre, Emilio H. "Plant Density and Distribution As Modifiers of Growth and Yield." In Wheat, 141–59. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003578444-9.

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Actas de conferencias sobre el tema "Wheat Yield"

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Babbar, Nandini, Ashish Kumar, and Vivek Kumar Verma. "Predicting Wheat Yield Using Sequential and Deep Convolutional Neural Networks." In 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC), 1104–8. IEEE, 2024. http://dx.doi.org/10.1109/icesc60852.2024.10689887.

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Ma, Lawrence, and Lin Zou. "A Creative Computing Approach to Forecasting Yield Shock of Winter Wheat." In 2024 IEEE 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C), 1203–12. IEEE, 2024. http://dx.doi.org/10.1109/qrs-c63300.2024.00158.

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Bozorgi, Mahsa, and Jordi Cristóbal. "Time Series Analysis of Evapotranspiration for Assessing Drough Impact on Wheat Yield." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2094–99. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642928.

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Khechba, Keltoum, Mariana Belgiu, Ahmed Laamrani, Qi Dong, Alfred Stein, and Abdelghani Chehbouni. "Stratified Machine Learning Models for Wheat Yield Estimation Using Remote Sensing Data." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 1946–49. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641044.

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Vikram, Aadi Krishna, Ashish Agrawal, Ankit Ranjan, Shubham Shinde, Swapnil Jalihale, Anurag Singh, Shrivishal Tripathi, Smitha Kurup, and Bharat Char. "Optimizing Wheat Ear Head Detection and Yield Estimation Through UAV Based Imagery." In TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), 1381–84. IEEE, 2024. https://doi.org/10.1109/tencon61640.2024.10902737.

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Madić, Milomirka, Dragan Đurović, Vladeta Stevović, Dalibor Tomić, Milan Biberdžić, Nenad Pavlović, and Miloš Marjanović. "GRAIN YIELD AND YIELD COMPONENTS OF PROSPECTIVE HOMOZYGOUS WINTER WHEAT GENOTYPES." In 2nd International Symposium on Biotechnology. Faculty of Agronomy in Čačak, University of Kragujevac, 2024. http://dx.doi.org/10.46793/sbt29.03mm.

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During the two-year research on the experimental field of the Grain Center in Kragujevac, the 1,000-grain weight, hectoliter mass and grain yield of ten prospective homozygous genotypes of wheat were analyzed. During the growing season, the average annual temperature and precipitation were favorable for growing wheat. In both growing seasons, precipitation was 120 mm more than the annual average, and 220 mm more in the second year. Genotype L- 1/59 had the highest grain yield and the highest 1,000-grain weight, while the hectoliter mass was more or less equal to other genotypes. All genotypes had a satisfactory 1,000-grain weight ranging from 43 to 50 g. On average, all analyzed lines had a hectoliter mass greater than 80 for both years, which ranks them as high quality.

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Fajardo, M., B. Whelan, P. Filippi, and T. Bishop. "Wheat yield forecast using contextual spatial information." In 12th European Conference on Precision Agriculture. The Netherlands: Wageningen Academic Publishers, 2019. http://dx.doi.org/10.3920/978-90-8686-888-9_88.

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Junankar, Tejas, Jasleen Kaur Sondhi, and Akhil M. Nair. "Wheat Yield Prediction using Temporal Fusion Transformers." In 2023 2nd International Conference for Innovation in Technology (INOCON). IEEE, 2023. http://dx.doi.org/10.1109/inocon57975.2023.10101144.

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Lamba, Vikas, Susheela Hooda, Rakesh Ahuja, and Amandeep Kaur. "Wheat Yield Prediction Using Feedforward Neural Networks." In 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2021. http://dx.doi.org/10.1109/icrito51393.2021.9596464.

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Kumar, Deepak, Yash Kumar, Akhilesh Gulati, and Vinay Kukreja. "Wheat Crop Yield Prediction Using Machine Learning." In 2022 International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, 2022. http://dx.doi.org/10.1109/icdabi56818.2022.10041621.

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Informes sobre el tema "Wheat Yield"

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Raitzer, David, and Joeffrey Drouard. Empirically Estimated Impacts of Climate Change on Global Crop Production via Increasing Precipitation–Evapotranspiration Extremes. Asian Development Bank, December 2024. https://doi.org/10.22617/wps240589-2.

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To assess climate change effects on crop yields, remote sensing-derived yield and agrometeorological reanalysis data are used to construct a panel at 0.1-degree resolution for 2003–2015. Regressions controlling for grid cell-specific intercepts and time trends, temperature, rainfall, and cloudiness estimate the subregional relationships between yields and precipitation-evapotranspiration extremes for rice, wheat, and maize. Results imply that climate change will cause global yield reductions for all crops, with losses highest for wheat and maize, especially in South Asia and Southern Africa.

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Blum, Abraham, and Henry T. Nguyen. Molecular Tagging of Drought Resistance in Wheat: Osmotic Adjustment and Plant Productivity. United States Department of Agriculture, November 2002. http://dx.doi.org/10.32747/2002.7580672.bard.

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Drought stress is a major limitation to bread wheat (Triticumaestivum L.) productivity and its yield stability in arid and semi-arid regions of world including parts of Israel and the U.S. Currently, breeding for sustained yields under drought stress is totally dependent on the use of yield and several key physiological attributes as selection indices. The attempt to identify the optimal genotype by evaluating the phenotype is undermining progress in such breeding programs. Osmotic adjustment (OA) is an effective drought resistance mechanism in many crop plants. Evidence exists that there is a genetic variation for OA in wheat and that high OA capacity supports wheat yields under drought stress. The major objective of this research was to identify molecular markers (RFLPs, restriction fragment length polymorphisms; and AFLPs, amplified fragment length polymorph isms) linked to OA as a major attribute of drought resistance in wheat and thus to facilitate marker-assisted selection for drought resistance. We identified high and low OA lines of wheat and from their cross developed recombinant inbred lines (RILs) used in the molecular tagging of OA in relation to drought resistance in terms of plant production under stress. The significant positive co-segregation of OA, plant water status and yield under stress in this RIL population provided strong support for the important role of OA as a drought resistance mechanism sustaining wheat production under drought stress. This evidence was obtained in addition to the initial study of parental materials for constructing this RIL population, which also gave evidence for a strong correlation between OA and grain yield under stress. This research therefore provides conclusive evidence on the important role of OA in sustaining wheat yield under drought stress. The measurement of OA is difficult and the selection for drought resistance by the phenotypic expression of OA is practically impossible. This research provided information on the genetic basis of OA in wheat in relations to yield under stress. It provided the basic information to indicate that molecular marker assisted selection for OA in wheat is possible. The RIL population has been created by a cross between two agronomic spring wheat lines and the high OA recombinants in this population presented very high OA values, not commonly observed in wheat. These recombinants are therefore an immediate valuable genetic recourse for breeding well-adapted drought resistant wheat in Texas and Israel. We feel that this work taken as a whole eliminate the few previous speculated . doubts about the practical role of OA as an important mechanism of drought resistance in economic crop plants. As such it should open the way, in terms of both concept and the use of marker assisted selection, for improving drought resistance in wheat by deploying high osmotic adjustment.

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Petzold, Christopher, Ai Oikawa, and Yang Tian. Fast growing high-yield wheat and canola for efficient nutrient recycling systems. Office of Scientific and Technical Information (OSTI), January 2020. http://dx.doi.org/10.2172/1593301.

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Beckman, Jayson, Fengxia Dong, Maros Ivanic, Jonas Jägermeyr, and Nelson Villoria. Climate-induced yield changes and TFP. [Washington, D.C.]: Economic Research Service, U.S. Department of Agriculture, 2024. http://dx.doi.org/10.32747/2024.8534117.ers.

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Increasing agricultural productivity is vital to ensure that global food demand can be met. However, the impact of a changing climate on temperatures and precipitation could potentially influence agricultural productivity by affecting crop yields. This report combines the latest estimates of yield changes from the Agricultural Model Intercomparison and Improvement Project with projections of future productivity changes in the form of total factor productivity (TFP) to gain a better understanding of the future of agricultural production (and thus of food supply). Yield estimates are used from a high greenhouse gas emissions scenario (to show an upper bound, as the impact of climate on yields is the strongest) for corn, rice, soybeans, and wheat. Yield changes are then combined with TFP estimates across four scenarios where research and development (R&D) assumptions determine the rate of TFP growth. Finally, the changes in yields and TFP, in conjunction with changes in populations and incomes, are assessed to shape the projected state of food supply in 2050. The results suggest that with no additional R&D expenditures, climate change would result in a production-consumption gap. When R&D investments are increased by amounts corresponding to the remaining three scenarios, TFP growth is sufficient to mitigate the impacts of climate change and projected population/income growth to maintain production at a level to meet global demand for food

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Blum, Abraham, Henry T. Nguyen, and N. Y. Klueva. The Genetics of Heat Shock Proteins in Wheat in Relation to Heat Tolerance and Yield. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568105.bard.

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Fifty six diverse spring wheat cultivars were evaluated for genetic variation and heritability for thermotolerance in terms of cell-membrane stability (CMS) and triphenyl tetrazolium chloride (TTC) reduction. The most divergent cultivars for thermotolerance (Danbata-tolerant and Nacozari-susceptible) were crossed to develop an F8 random onbred line (RIL) population. This population was evaluated for co-segragation in CMS, yield under heat stress and HSP accumulation. Further studies of thermotolerance in relations to HSP and the expression of heterosis for growth under heat stress were performed with F1 hybrids of wheat and their parental cultivars. CMS in 95 RILs ranged from 76.5% to 22.4% with 71.5% and 31.3% in Danbata and Nacozari, respectively. The population segregated with a normal distribution across the full range of the parental values. Yield and biomass under non-stress conditions during the normal winter season at Bet Dagan dit not differ between the two parental cultivar, but the range of segregation for these traits in 138 RILs was very high and distinctly transgressive with a CV of 35.3% and 42.4% among lines for biomass and yield, respectively. Mean biomass and yield of the population was reduced about twofold when grown under the hot summer conditions (irrigated) at Bet Dagan. Segregation for biomass and yield was decreased relative to the normal winter conditions with CV of 20.2% and 23.3% among lines for biomass and yield, respectively. However, contrary to non-stress conditions, the parental cultivars differed about twofold in biomass and yield under heat stress and the population segregated with normal distribution across the full range of this difference. CMS was highly and positively correlated across 79 RILs with biomass (r=0.62**) and yield (r=0.58**) under heat stress. No such correlation was obtained under the normal winter conditions. All RILs expressed a set of HSPs under heat shock (37oC for 2 h). No variation was detected among RILs in high molecular weight HSP isoforms and they were similar to the patterns of the parental cultivars. There was a surprisingly low variability in low molecular weight HSP isoforms. Only one low molecular weight and Nacozari-specific HSP isoform (belonging to HSP 16.9 family) appeared to segregate among all RILs, but it was not quantitatively correlated with any parameter of plant production under heat stress or with CMS in this population. It is concluded that this Danbata/Nacozari F8 RIL population co-segregated well for thermotolerance and yield under heat stress and that CMS could predict the relative productivity of lines under chronic heat stress. Regretfully this population did not express meaningful variability for HSP accumulation under heat shock and therefore no role could be seen for HSP in the heat tolerance of this population. In the study of seven F1 hybrids and their parent cultivars it was found that heterosis (superiority of the F1 over the best parent) for CMs was generally lower than that for growth under heat stress. Hybrids varied in the rate of heterosis for growth at normal (15o/25o) and at high (25o/35o) temperatures. In certain hybrids heterosis for growth significantly increased at high temperature as compared with normal temperature, suggesting temperature-dependent heterosis. Generally, under normal temperature, only limited qualitative variation was detected in the patterns of protein synthesis in four wheat hybrids and their parents. However, a singular protein (C47/5.88) was specifically expressed only in the most heterotic hybrid at normal temperature but not in its parent cultivars. Parental cultivars were significantly different in the sets of synthesized HSP at 37o. No qualitative changes in the patterns of protein expression under heat stress were correlated with heterosis. However, a quantitative increase in certain low molecular weight HSP (mainly H14/5.5 and H14.5.6, belonging to the HSP16.9 family) was positively associated with greater heterosis for growth at high temperature. None of these proteins were correlated with CMS across hybrids. These results support the concept of temperature-dependent heterosis for growth and a possible role for HSP 16.9 family in this respect. Finally, when all experiments are viewed together, it is encouraging to find that genetic variation in wheat yield under chronic heat stress is associated with and well predicted by CMS as an assay of thermotolerance. On the other hand the results for HSP are elusive. While very low genetic variation was expressed for HSP in the RIL population, a unique low molecular weight HSP (of the HSP 16.9 family) could be associated with temperature dependant heterosis for growth.

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Minz-Dub, A., G. J. Muehlbauer, E. Millet, and A. Sharon. ing and characterization of a novel leaf rust and stripe rust resistance gene from Sharon goatgrass. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2021. http://dx.doi.org/10.32747/2021.8134171.bard.

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Each year, significant global wheat yield loss occurs due to diseases that affect yield quantity or quality. Breeding for resistance has been the best economic and environmentally safe approach to control wheat diseases, however many disease resistance (R) genes succumbed to the pathogens and are no longer effective. Hence, new sources of resistance are necessary to boost the wheat gene pool. The main source for such genes are species of wheat wild relatives in the secondary gene pool that contain an unexploited reservoir of novel R genes. Sharon goatgrass (Aegilops sharonensis Eig) is a wild diploid relative of wheat (genome SshS sh). It is native to the coastal plain of Israel, growing mostly on stabilized dunes, and is highly resistant to rust pathogens. Previously, we introgressed a leaf and stripe rust resistance locus from Ae. sharonensis into bread wheat using chromosome engineering (Millet et al., 2014). We mapped the alien region to the short arm of chromosome six using genotyping by sequencing, identified SNPs, and used them to generate diagnostic markers (Khazan et al., 2020).

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Feldman, Moshe, Eitan Millet, Calvin O. Qualset, and Patrick E. McGuire. Mapping and Tagging by DNA Markers of Wild Emmer Alleles that Improve Quantitative Traits in Common Wheat. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573081.bard.

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The general goal was to identify, map, and tag, with DNA markers, segments of chromosomes of a wild species (wild emmer wheat, the progenitor of cultivated wheat) determining the number, chromosomal locations, interactions, and effects of genes that control quantitative traits when transferred to a cultivated plant (bread wheat). Slight modifications were introduced and not all objectives could be completed within the human and financial resources available, as noted with the specific objectives listed below: 1. To identify the genetic contribution of each of the available wild emmer chromosome-arm substitution lines (CASLs) in the bread wheat cultivar Bethlehem for quantitative traits, including grain yield and its components and grain protein concentration and yield, and the effect of major loci affecting the quality of end-use products. [The quality of end-use products was not analyzed.] 2. To determine the extent and nature of genetic interactions (epistatic effects) between and within homoeologous groups 1 and 7 for the chromosome arms carrying "wild" and "cultivated" alleles as expressed in grain and protein yields and other quantitative traits. [Two experiments were successful, grain protein concentration could not be measured; data are partially analyzed.] 3. To derive recombinant substitution lines (RSLs) for the chromosome arms of homoeologous groups 1 and 7 that were found previously to promote grain and protein yields of cultivated wheat. [The selection of groups 1 and 7 tons based on grain yield in pot experiments. After project began, it was decided also to derive RSLs for the available arms of homoeologous group 4 (4AS and 4BL), based on the apparent importance of chromosome group 4, based on early field trials of the CASLs.] 4. To characterize the RSLs for quantitative traits as in objective 1 and map and tag chromosome segments producing significant effects (quantitative trait loci, QTLs by RFLP markers. [Producing a large population of RSLs for each chromosome arm and mapping them proved more difficult than anticipated, low numbers of RSLs were obtained for two of the chromosome arms.] 5. To construct recombination genetic maps of chromosomes of homoeologous groups 1 and 7 and to compare them to existing maps of wheat and other cereals [Genetic maps are not complete for homoeologous groups 4 and 7.] The rationale for this project is that wild species have characteristics that would be valuable if transferred to a crop plant. We demonstrated the sequence of chromosome manipulations and genetic tests needed to confirm this potential value and enhance transfer. This research has shown that a wild tetraploid species harbors genetic variability for quantitative traits that is interactive and not simply additive when introduced into a common genetic background. Chromosomal segments from several chromosome arms improve yield and protein in wheat but their effect is presumably enhanced when combination of genes from several segments are integrated into a single genotype in order to achieve the benefits of genes from the wild species. The interaction between these genes and those in the recipient species must be accounted for. The results of this study provide a scientific basis for some of the disappointing results that have historically obtained when using wild species as donors for crop improvement and provide a strategy for further successes.

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Tzin, V., B. Dilkes, and H. Sela. Identifying molecular markers for defense metabolites against aphid feeding in wild emmer wheat. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2021. http://dx.doi.org/10.32747/2021.8134174.bard.

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Bread wheat is the second most important food crop, providing calories to half of the world population and roughly one-fifth of the calories and protein consumed by people worldwide. Crop losses to insect pests depress yields and climate change is expected to significantly increase this problem. To combat global food insecurity, the protection of crops from insect pests must be prioritized. The Bird cherry-oat aphid, Rhopalosiphum padi, is the most abundant and economically important cereal pest, causes up to 40-60 % yield loss through direct feeding and vectoring plant diseases. The main goal of this project was to identify molecular markers associated with aphid resistance and defense metabolite levels in wild emmer wheat (WEW). During the three years of this project, we screened a large number of WEW accessions and conducted a genome-wide association study (GWAS) analysis. We experimented with data processing and explored different GWAS models, which revealed a massive number of determinants of aphid resistance and highlighted hundreds of single nucleotide polymorphisms (SNPs). Thus, we focused on a small subset of genes that linked to the most significant SNPs. By the end of this collaboration, we have a list of important SNPs, and three major genes that we believe have a strong effect on wheat resistance to aphids. Work on these genes is continuing and will soon publish our exciting new results.

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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.

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Pullammanappallil, Pratap, Haim Kalman, and Jennifer Curtis. Investigation of particulate flow behavior in a continuous, high solids, leach-bed biogasification system. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600038.bard.

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Recent concerns regarding global warming and energy security have accelerated research and developmental efforts to produce biofuels from agricultural and forestry residues, and energy crops. Anaerobic digestion is a promising process for producing biogas-biofuel from biomass feedstocks. However, there is a need for new reactor designs and operating considerations to process fibrous biomass feedstocks. In this research project, the multiphase flow behavior of biomass particles was investigated. The objective was accomplished through both simulation and experimentation. The simulations included both particle-level and bulk flow simulations. Successful computational fluid dynamics (CFD) simulation of multiphase flow in the digester is dependent on the accuracy of constitutive models which describe (1) the particle phase stress due to particle interactions, (2) the particle phase dissipation due to inelastic interactions between particles and (3) the drag force between the fibres and the digester fluid. Discrete Element Method (DEM) simulations of Homogeneous Cooling Systems (HCS) were used to develop a particle phase dissipation rate model for non-spherical particle systems that was incorporated in a two-fluid CFDmultiphase flow model framework. Two types of frictionless, elongated particle models were compared in the HCS simulations: glued-sphere and true cylinder. A new model for drag for elongated fibres was developed which depends on Reynolds number, solids fraction, and fibre aspect ratio. Schulze shear test results could be used to calibrate particle-particle friction for DEM simulations. Several experimental measurements were taken for biomass particles like olive pulp, orange peels, wheat straw, semolina, and wheat grains. Using a compression tester, the breakage force, breakage energy, yield force, elastic stiffness and Young’s modulus were measured. Measurements were made in a shear tester to determine unconfined yield stress, major principal stress, effective angle of internal friction and internal friction angle. A liquid fludized bed system was used to determine critical velocity of fluidization for these materials. Transport measurements for pneumatic conveying were also assessed. Anaerobic digestion experiments were conducted using orange peel waste, olive pulp and wheat straw. Orange peel waste and olive pulp could be anaerobically digested to produce high methane yields. Wheat straw was not digestible. In a packed bed reactor, anaerobic digestion was not initiated above bulk densities of 100 kg/m³ for peel waste and 75 kg/m³ for olive pulp. Interestingly, after the digestion has been initiated and balanced methanogenesis established, the decomposing biomass could be packed to higher densities and successfully digested. These observations provided useful insights for high throughput reactor designs. Another outcome from this project was the development of low cost devices to measure methane content of biogas for off-line (US$37), field (US$50), and online (US$107) applications.

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