Relevant bibliographies by topics / Grain yield

Academic literature on the topic 'Grain yield'

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Published: 4 June 2021
Last updated: 10 March 2023

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Journal articles on the topic "Grain yield"

1

Ionuṭ RACZ, Rozalia KADAR, Sorin VȂTCĂ, Florin Dumitru BORA, Diana HIRIṢCĂU, Adina VARADI, and Ioana BERINDEAN. "RELATIONSHIP BETWEEN LEAF AREA SURFACE, CHLOROPHYLL CONCENTRATION AND YIELD COMPONENTS IN SPRING WHEAT." LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT 2, no. 2 (December 26, 2021): 1–5. http://dx.doi.org/10.58509/lssd.v2i2.122.

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The present paper presents the variability of some yields and non-yields components of a group of ten varieties of spring wheat. Flag leaf area, chlorophyll concentration, spike length, number of grains/spike, weight of grains/spike and estimated grain yield were analyzed as yield components or morpho-physiological traits with a high impact on final grain yield. Flag leaf area surface has a direct an important contribution to determine increased number and weight of grains per spike. Chlorophyll concentration determined from flag leaf at early milky stage is significant correlated with weight of grains per spike (0.64*) which means that maintaining of a high level of chlorophyll pigments in leaf contributes decisively to high grain yield. Grain yield performance of genotypes can be appreciated based on the preliminary information given by chlorophyll concentration measured in advanced generative stage. Obtaining information previous final grain yield creates the possibility of pursuing more closely of a valuable breeding material while eliminating non-conforming genotypes.
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Ramadhani, Siti Hasdiyanti, Ni Luh Sri Suryaningsih, and Yosefina Mangera. "Analysis of Grain Yield and Quality of Rice Aromatic Inpago Unsoed 1." AGRICOLA 8, no. 1 (September 24, 2019): 1–6. http://dx.doi.org/10.35724/ag.v8i1.2098.

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The purpose of the study was to determine the quality of the grainand rice are planted, the ricevarieties Inpago Unsoed 1. The research method use dis data collection, namely primary data andsecondary data. Primary data is used for observed in this research about grain moisturecontent,density of grain, foreign bodies, empty grains, grain crackedor broken, after the percentage ofgrain milled head of rice, broken rice, graing roats, grain limestone, yolk broken and milled rice yield.The results showed that during the observation the quality of grain varieties Inpago Unsoed 1 hasmilled at about 13,33% moisture content, grain density of 0,57g/ml, and grain weight is 27,60g/1000grain. The percentage point for the determination quality of head point is 73,49%, broken grainsabout 13,92%, and 12,34% graing roats. The quality of rice milled varieties inpago Unsoed 1 includelow. The lower of rice quality is due to the low of head rice percentage, while the percentage ofbroken grain sand high graing roats. Rice milled yield about 51,23%
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Feng, Fan, Pengfei Dang, Xuan Pu, Xiaoxia Wen, Xiaoliang Qin, Yinglong Chen, and Kadambot H. M. Siddique. "Contribution of Proximal and Distal Grains Within Spikelets in Relation to Yield and Yield Components in the Winter Wheat Production Region of China From 1948 to 2012." Agronomy 9, no. 12 (December 5, 2019): 850. http://dx.doi.org/10.3390/agronomy9120850.

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Grain number and weight within a spikelet are major yield components which determine the grain yield in wheat. The objective of this study was to explore genetic gains in grain performance within wheat spikelets at the individual grain level and its effect on grain yield and evaluate genetic progress in stem internode length and other yield-related traits. We conducted field experiments across three growing seasons in the western Yellow and Huai Valley of China; incorporating 17 bread wheat cultivars released from 1948 to 2012. Yields were significantly correlated with year of release. Yield gains equated to 3.95 g m−2 yr−1 in response to increases in total grain weight per m2 (GW) in proximal (G1 and G2) and distal (G3 and G4) grains, despite a decline in the proportional contribution of proximal grains to yield and increase in the proportional contribution of distal grains to yield with year of release. Grain number per m2 (GN), thousand-grain weight (TGW), and harvest index (HI) increased with year of release, but plant height decreased. Both grain number per spikelet of proximal and distal grain contributed to the increase in total GN. However, the contribution ratio of GN in proximal grains to total GN declined, and the proportion in distal grains increased. Average single grain weight (SGW) increased linearly at G1, G2, G3, and G4 with year of release and contributed to the increase in TGW. The G3 and G4 grain positions had much lower individual grain weights but increased at a faster rate than G1 and G2. At G1, G2, and G3 grain positions, from bottom to top spikelets, the newly released cultivars had the heaviest grains and the old cultivars had the lightest grains. New cultivars had more spikelets than old cultivars and the number of grains (proximal and distal grains) in the apical spike increased with year of release. The length of five internodes decreased significantly with year of release, more so in the upper than lower internodes, all of which contributed to the decline in plant height. In summary, increasing the number and weight of distal grains could increase grain yield, TGW, and GN.
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Dorval, Isabelle, Anne Vanasse, Denis Pageau, and Yves Dion. "Seeding rate and cultivar effects on yield, yield components and grain quality of spring spelt in eastern Canada." Canadian Journal of Plant Science 95, no. 5 (September 2015): 841–49. http://dx.doi.org/10.4141/cjps-2014-439.

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Dorval, I., Vanasse, A., Pageau, D. and Dion, Y. 2015. Seeding rate and cultivar effects on yield, yield components and grain quality of spring spelt in eastern Canada. Can. J. Plant. Sci. 95: 841–849. There is currently an increasing demand from master millers for spelt (Triticum aestivum ssp. spelta), but little is known about crop management of spring spelt under the eastern Canadian climate in organic or low-input systems. Field experiments were carried out at three sites in Quebec from 2011 to 2013 to assess the effect of cultivar (CDC Origin, CDC Zorba, CDC Nexon, CDC Silex) and seeding rate (250, 300, 350, 400 and 450 grains m−2) on grain and straw yields, yield components and some grain quality characteristics of spelt. CDC Origin produced higher hulled grain yields at all sites, while CDC Silex produced similar hulled grain yields and achieved the highest naked grain yields at two of the three test sites. The hull content varied from 24.0 to 37.6% among cultivars. CDC Origin had the highest hull content at each site. The seeding rate generally had no effect on yields, but had an effect on yield components; increasing seeding rates slightly increased the number of spikes per square metre and decreased the number of grains per spike, while the 1000-grain weight remained unaffected. Protein content of all cultivars was high (14.2 to 15.4%), while falling number varied from 219 to 385 s.
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Brdar, Milka, Borislav Kobiljski, and Marija Balalic-Kraljevic. "Grain filling parameters and yield components in wheat." Genetika 38, no. 3 (2006): 175–81. http://dx.doi.org/10.2298/gensr0603175b.

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Grain yield of wheat (Triticum aestivum L.) is influenced by number of grains per unit area and grain weight, which is result of grain filling duration and rate. The aim of the study was to investigate the relationships between grain filling parameters in 4 wheat genotypes of different earliness and yield components. Nonlinear regression estimated and observed parameters were analyzed. Rang of estimated parameters corresponds to rang of observed parameters. Stepwise MANOVA indicated that the final grain dry weight, rate and duration of grain filling were important parameters in differentiating among cultivars grain filling curves. The yield was positively correlated with number of grains/m2, grain weight and grain filling rate, and negatively correlated with grain filling duration. Correlation between grain weight and rate of grain filling was positive. Grain filling duration was negatively correlated with grain filling rate and number of grains/m2. The highest yield on three year average had medium late Mironovska 808, by the highest grain weight and grain filling rate and optimal number of grains/2 and grain filling duration.
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Gudepu, Sandhya, Damodar Raju Chennamadhavuni, and Sumalini Katragadda. "Variability and association studies for yield and yield contributing traits in long grain rice (Oryza sativa L.)." Oryza-An International Journal on Rice 59, no. 4 (December 31, 2022): 409–17. http://dx.doi.org/10.35709/ory.2022.59.4.3.

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Thirty accessions of long grain rice with grain length > 6.2mm including two checks viz., KNM 118 and IR 64 were evaluated to study variability, correlation and path analysis for yield and yield attributing traits. High range of variation, PCV and GCV were observed for number of effective tillers per plant, panicle weight, number of grains per panicle, 1000-grain weight and grain yield per plant and high heritability coupled with high genetic advance was observed for number of effective tillers per plant, plant height, panicle length, panicle weight, number of grains per panicle, 1000-grain weight, kernel length, kernel L/B ratio, grain length, grain L/B ratio and grain yield per plant. Among all the entries tested KPS 6363 and KPS 3272 were found promising with higher grain yield per plant. Correlation analysis revealed that plant height, panicle weight, grain breadth exhibited a significant and positive association with grain yield per plant. Path analysis revealed that among quantitative traits number of effective tillers per plant, plant height, panicle weight and number of grains per panicle and quality traits kernel breadth, kernel L/B ratio, grain length and kernel L/B ratio had shown positive direct effect on grain yield per plant followed by kernel breadth, plant height, panicle weight, grain length and number of grains per panicle and these traits can be used as selection indices for development of high yielding rice varieties coupled with quality.
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El-Shatnawi, M. K. J., and N. I. Haddad. "Assessing barley (Hordeum vulgare) response to clipping in the semi-arid Mediterranean climate." Australian Journal of Experimental Agriculture 44, no. 1 (2004): 37. http://dx.doi.org/10.1071/ea02103.

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Greenhouse pot trials and field experiments were carried out under rain-fed condition in north-eastern Jordan during 1997–98 and 1998–99 growing seasons, to test 3 barley genotypes for their suitability for both forage and grain production. The varieties Rehani and ACSAD176 produced higher forage yields than Rum. In the field, clipping reduced subsequent grain yield per plant by about 18%, lowering grain weight of the main spike from 2.3�g in the control to 1.8 g in the clipped plants. Clipping increased tiller density of barley plants in the field. Decreases in grain yield following clipping could also be attributed to reductions in the number of grains per spike. Clipping decreased the number of grains per spike by about 9% by reducing the number of spikelets per spike. Cutting reduced 1000-grain weight by about 9%. Clipping induced changes in the relative importance of yield components influencing subsequent grain yield. The yield components reduced by clipping were the most important contributors to loss of grain yield.
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Rahman, MM, SK Paul, and MM Rahman. "Effects of spacing and nitrogen levels on yield and yield contributing characters of maize." Journal of the Bangladesh Agricultural University 14, no. 1 (December 10, 2016): 43–48. http://dx.doi.org/10.3329/jbau.v14i1.30595.

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An experiment was conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during November 2014 to April 2015 to investigate the effect of planting spacing and nitrogen levels on yield attributes and yield of maize cv. Khaibhutta. The experiment comprised three nitrogen levels viz. 50, 100 and 150 kg N ha-1 and five plant spacings viz. 75 cm × 25 cm, 75 cm × 20 cm, 50 cm × 25 cm, 50 cm × 20 cm and 100 cm × 20 cm. The experiment was laid out in a randomized complete block design with three replications. Results revealed that nitrogen levels and plant spacing had significant effect on yield attributes and yield of Khaibhutta. The highest number of cobs plant-1, grains row-1, grain yield and stover yield were recorded with 150 kg N ha-1 followed by 100 kg N ha- 1and the lowest values were observed in 50 kg N ha-1. The highest number of cobs plant-1, grain rows cob-1, grains row-1, grains cob-1, 1000-grain weight, grain yield and harvest index were recorded at 75 cm × 25 cm spacing. In contrast, the closest spacing of 50 cm x 20 cm produced the lowest values of grain rows cob-1, grains row-1, grains cob-1, 1000-grain weight and grain yield. In case of interaction, the highest grain yield and harvest index were obtained at 75 cm × 25 cm spacing fertilized with 150 kg N ha-1. The lowest values of the above parameters were recorded in the closest spacing 50 cm × 20 cm with 50 kg N ha-1. From this study it may be concluded that maize (cv. Khaibhutta) can be cultivated at the spacing of 75 cm × 25 cm with 150 kg N ha-1 for appreciable grain yield.J. Bangladesh Agril. Univ. 14(1): 43-48, June 2016
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Balyan, H. S., and Tejbir Singh. "Character association analysis in common wheat (Triticum aestivum L.)." Genome 29, no. 2 (April 1, 1987): 392–94. http://dx.doi.org/10.1139/g87-068.

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Grain yield of wheat as a component characteristic of total dry matter (biological) yield is governed by harvest index (V. P. Kulshrestha and H. K. Jain. 1982. Z. Pflanzenzuecht. 89: 19–30). At the phenotypic level, both the grain and biological yields are dependent upon a number of measurable agronomic characteristics such as plant height, tiller number, spike length, and grains per spike, etc. From a breeder's point of view, it is of great value to know the relative significance of these characteristics in determining grain yield to design appropriate selection strategies. The present study evaluated the covariability of yield in relation to various agronomic traits and ascertained their direct and indirect contributions towards grain yield. Key words: wheat, grain yield.
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Perry, MW, and MF D'Antuono. "Yield improvement and associated characteristics of some Australian spring wheat cultivars introduced between 1860 and 1982." Australian Journal of Agricultural Research 40, no. 3 (1989): 457. http://dx.doi.org/10.1071/ar9890457.

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Twenty-eight Australian wheat (Triticum aestivum L. em. Thell.) cultivars representing a series from the 1860s to 1982, were grown in 20 field trials over four years in the wheatbelt of Western Australia. The cultivars included introductions and selections made before 1900, plus important cultivars bred or grown in Western Australia up to 1982. Five of the latter group were from crosses including semidwarf cultivars as parents. Grain yields were measured on all trials, and six trials were also sampled for biomass and yield components.Based on the regression of mean grain yield versus the number of years elapsed since 1884, yields have increased from 1022 kg ha-1 in 1884 to 1588 kg ha-1 in 1982. This represents a rate of increase of 5.8 kg ha-1 year-1 or 0.57% per year. Regression of cultivar yield on site mean yield gave values of b, the slope of the regression, from 0.66 to 1.24, and these were higher for modern than for old cultivars.In six trials sampled for yield components, above-ground biomass appeared to have increased slightly when comparing early selections and their derivatives with later cultivars, but over 80% of the overall increase in grain yield was due to increase in harvest index. Grains per car and grains m-2 were strongly and positively correlated with grain yield, but there were weak negative correlations between 1000-grain weight and yield, and between 1000 grain weight and years since 1884. Cultivars with a semi-dwarf background had equal biomass, but higher yield, harvest index, ear number m-2 and grains ear-2 than modern tall cultivars. The results show that genetic improvement has substantially increased yield potential in this environment and that this has been achieved through substantial increases in grain number m-2 associated with an improvement in harvest index.
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Dissertations / Theses on the topic "Grain yield"

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Ottman, Michael J., Michael D. Sheedy, and Richard W. Ward. "Clipping small grains to increase subsequent grain yield." College of Agriculture, University of Arizona (Tucson, AZ), 2016. http://hdl.handle.net/10150/625423.

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Wheat is commonly grown as a dual purpose crop especially in the Southern Great Plains where the forage is grazed then allowed to mature into a grain crop. In Arizona, clipping a crop planted in October may increase tillering and grain yield. A trial was conducted at the Maricopa Ag Center where various small grain varieties were planted on October 12, 2015, cut for forage on January 10, 2016, and allowed to go to grain and compared with the same varieties planted on December 3, 2016 and not cut for forage. No differences in grain yield due to planting date and clipping were detected. However, the October 12 planting with clipping had larger kernels, greater grain protein, and higher stem density. The income from the sale of the forage was $99/acre based a yield of 2639 lb/acre and a forage value of $75/ton. The added cost per acre to produce this forage included $29 for water (6.27 inches of water at $55/acre-ft) plus $34 for fertilizer (50 lb N/acre of urea at $433/ton). Therefore, even though grain yield was not increased by planting early and clipping, a net increase in revenue of $36/acre was realized from the sale of the forage.
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Norng, Sorn. "Statistical decisions in optimising grain yield." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15806/1/Sorn_Norng_Thesis.pdf.

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This thesis concerns Precision Agriculture (PA) technology which involves methods developed to optimise grain yield by examining data quality and modelling protein/yield relationship of wheat and sorghum fields in central and southern Queensland. An important part of developing strategies to optimisise grain yield is the understanding of PA technology. This covers major aspects of PA which includes all the components of Site- Specific Crop Management System (SSCM). These components are 1. Spatial referencing, 2. Crop, soil and climate monitoring, 3. Attribute mapping, 4. Decision suppport systems and 5. Differential action. Understanding how all five components fit into PA significantly aids the development of data analysis methods. The development of PA is dependent on the collection, analysis and interpretation of information. A preliminary data analysis step is described which covers both non-spatial and spatial data analysis methods. The non-spatial analysis involves plotting methods (maps, histograms), standard distribution and statistical summary (mean, standard deviation). The spatial analysis covers both undirected and directional variogram analyses. In addition to the data analysis, a theoretical investigation into GPS error is given. GPS plays a major role in the development of PA. A number of sources of errors affect the GPS and therefore effect the positioning measurements. Therefore, an understanding of the distribution of the errors and how they are related to each other over time is needed to complement the understanding of the nature of the data. Understanding the error distribution and the data give useful insights for model assumptions in regard to position measurement errors. A review of filtering methods is given and new methods are developed, namely, strip analysis and a double harvesting algoritm. These methods are designed specifically for controlled traffic and normal traffic respectively but can be applied to all kinds of yield monitoring data. The data resulting from the strip analysis and double harvesting algorithm are used in investigating the relationship between on-the-go yield and protein. The strategy is to use protein and yield in determining decisions with respect to nitrogen managements. The agronomic assumption is that protein and yield have a significant relationship based on plot trials. We investigate whether there is any significant relationship between protein and yield at the local level to warrent this kind of assumption. Understanding PA technology and being aware of the sources of errors that exist in data collection and data analysis are all very important in the steps of developing management decision strategies.
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Norng, Sorn. "Statistical decisions in optimising grain yield." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15806/.

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This thesis concerns Precision Agriculture (PA) technology which involves methods developed to optimise grain yield by examining data quality and modelling protein/yield relationship of wheat and sorghum fields in central and southern Queensland. An important part of developing strategies to optimisise grain yield is the understanding of PA technology. This covers major aspects of PA which includes all the components of Site- Specific Crop Management System (SSCM). These components are 1. Spatial referencing, 2. Crop, soil and climate monitoring, 3. Attribute mapping, 4. Decision suppport systems and 5. Differential action. Understanding how all five components fit into PA significantly aids the development of data analysis methods. The development of PA is dependent on the collection, analysis and interpretation of information. A preliminary data analysis step is described which covers both non-spatial and spatial data analysis methods. The non-spatial analysis involves plotting methods (maps, histograms), standard distribution and statistical summary (mean, standard deviation). The spatial analysis covers both undirected and directional variogram analyses. In addition to the data analysis, a theoretical investigation into GPS error is given. GPS plays a major role in the development of PA. A number of sources of errors affect the GPS and therefore effect the positioning measurements. Therefore, an understanding of the distribution of the errors and how they are related to each other over time is needed to complement the understanding of the nature of the data. Understanding the error distribution and the data give useful insights for model assumptions in regard to position measurement errors. A review of filtering methods is given and new methods are developed, namely, strip analysis and a double harvesting algoritm. These methods are designed specifically for controlled traffic and normal traffic respectively but can be applied to all kinds of yield monitoring data. The data resulting from the strip analysis and double harvesting algorithm are used in investigating the relationship between on-the-go yield and protein. The strategy is to use protein and yield in determining decisions with respect to nitrogen managements. The agronomic assumption is that protein and yield have a significant relationship based on plot trials. We investigate whether there is any significant relationship between protein and yield at the local level to warrent this kind of assumption. Understanding PA technology and being aware of the sources of errors that exist in data collection and data analysis are all very important in the steps of developing management decision strategies.
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4

Clover, Matthew William. "Soil and fertilizer potassium impacts on corn and soybean grain yield, potassium uptake, and within-field grain yield variation." [Ames, Iowa : Iowa State University], 2008.

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Sukumaran, Sivakumar. "Genomic mapping for grain yield, stay green, and grain quality traits in sorghum." Diss., Kansas State University, 2012. http://hdl.handle.net/2097/15084.

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Doctor of Philosophy
Department of Agronomy
Jianming Yu
Knowledge of the genetic bases of grain quality traits will complement plant breeding efforts to improve the end use value of sorghum (Sorghum bicolor (L.) Moench). The objective of the first experiment was to assess marker-trait associations for 10 grain quality traits through candidate gene association mapping on a diverse panel of 300 sorghum accessions. The 10 grain quality traits were measured using the single kernel characterization system (SKCS) and near-infrared reflectance spectroscopy (NIRS). The analysis of the accessions through 1,290 genome-wide single nucleotide polymorphisms (SNPs) separated the panel into five subpopulations that corresponded to three major sorghum races (durra, kafir, and caudatum), one intermediate race (guinea-caudatum), and one working group (zerazera/caudatum). Association analysis between 333 SNPs in candidate genes/loci and grain quality traits resulted in eight significant marker-trait associations. A SNP in starch synthase IIa (SSIIa) gene was associated with kernel hardness (KH) with a likelihood ratio–based R[superscript]2 (R[subscript]L[subscript]R[superscript]2) value of 0.08. SNPs in starch synthase (SSIIb) gene (R[subscript]L[subscript]R[superscript]2 = 0.10) and loci pSB1120 (R[subscript]L[subscript]R[superscript]2 = 0.09) was associated with starch content. Sorghum is a crop well adapted to the semi arid regions of the world and my harbor genes for drought tolerance. The objective of second experiment was to identify quantitative trait loci (QTLs) for yield potential and drought tolerance. From a cross between Tx436 (food grain type) and 00MN7645 (drought tolerant) 248 recombinant inbred lines (RILs) was developed. Multi-location trials were conducted in 8 environments to evaluate agronomic performance of the RILs under favorable and drought stress conditions. The 248 RILs and their parents were genotyped by genotyping-by-sequencing (GBS). A subset of 800 SNPs was used for linkage map construction and QTL detection. Composite interval mapping identified a major QTLs for grain yield in chromosome 8 and QTL for flowering time in chromosome 9 under favorable conditions. Three major QTLs were detected for grain yield in chromosomes 1, 6, and 8 and two flowering time QTLs on chromosome 1 under drought conditions. Six QTLs were identified for stay green: two on chromosome 4; one each on chromosome 5, 6, 7, and 10 under drought conditions.
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Harper, John, and David K. Parsons. "Small Grain Variety Yield Comparisons, Maricopa Agricultural Center." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/200517.

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Cluff, Ronald E., David K. Parsons, and Lee J. Clark. "Small Grain Variety Yield Comparison, Maricopa Agricultural Center." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/200518.

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Ekanayake, Lukshman Jayampathi. "Selenium on Increasing Lentil (Lens Culinaris Medikus.) Grain Yield." Thesis, North Dakota State University, 2014. https://hdl.handle.net/10365/27405.

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Selenium is an essential element for mammals but it has not been considered as essential for higher plants. The effect of Se application on lentil grain yield, antioxidant activity, nitrogen fixation, and seed Se concentration studied. Experiments were conducted at Carrington Research and Extension Center in 2012 and 2013. Selenium fertilization increased the lentil grain yield by 5 % in 2012 and by 9 % in 2013. Selenium application increased the antioxidant activity (70 % inhibition) of lentils compared to the untreated control (61% inhibition). Percentage nitrogen derived from air was increased with Se fertilization by 17 % and 12 % in 2012 and 2013, respectively, with Se fertilization. Seed Se concentration was significantly higher in selenate treated lentils (1.4 mg/kg) compared to selenite (0.9 mg/kg) and the control (0.6 mg/kg). Overall, application of Se increased lentil grain yield, nitrogen fixation, antioxidant protection, and seed Se concentration.
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9

Sheedy, M., M. Ottman, and T. Ramage. "Oat Variety Grain and Forage Yield Trials at the Maricopa Agricultural Center 1989." College of Agriculture, University of Arizona (Tucson, AZ), 1989. http://hdl.handle.net/10150/201031.

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Sheedy, M., M. Ottman, and T. Ramage. "Oat Variety Grain and Forage Yield Trials at the Maricopa Agricultural Center, 1990." College of Agriculture, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/201345.

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Twelve oat varieties (9 hulled and 3 hull-less) were yield tested for both forage and grain production at the Maricopa Agricultural Center during the '89-90 growing season. Highest forage producing varieties were generally later maturing - Cayuse and Stampede; while lower yields were produced by early maturing varieties - Montezuma and Palestine. Highest grain yields were produced by Swan and FMC400.
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Books on the topic "Grain yield"

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Egli, D. B., ed. Seed biology and yield of grain crops. Wallingford: CABI, 2017. http://dx.doi.org/10.1079/9781780647708.0000.

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Seed biology and the yield of grain crops. Wallingford, Oxon: CAB International, 1998.

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Crook, Frederick W. China's coarse grains, production, area and yield estimates, 1949-85. [Washington, D.C.]: U.S. Dept. of Agriculture, Economic Research Service, International Economics Division, 1986.

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Ntamatungiro, S. Influence of uneven emergence of rice on grain yield, yield components and milling quality. Fayetteville, Ark: Arkansas Agricultural Experiment Station, 1993.

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Jamie, Goode, Chadwick Derek, and Symposium on Rice Biotechnology: Improving Yield, Stress Tolerance, and Grain Quality (2000 : Laguna, Philippines), eds. Rice biotechnology: Improving yield, stress tolerance and grain quality. Chichester: Wiley, 2001.

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Ash, Mark S. Regional crop yield response for U.S. grains. Washington, D.C. (1301 New York Ave., NW., Washington 20005-4788): U.S. Dept. of Agriculture, Economic Research Service, 1987.

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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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Wibberley, E. John. Fertilising small-grain cereals for sustainable yield and high quality. Horgen: International Potash Institute, 2006.

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Bradbury, Derek. Cereals in Europe: Statistical systems for measuring area, production, and yield. Luxembourg: Office for Official Publications of the European Communities, 1995.

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Counce, Paul A. Post-heading irrigation management effects on rice grain yield and milling quality. Fayetteville, Ark: Arkansas Agricultural Experiment Station, 1993.

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Book chapters on the topic "Grain yield"

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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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Vandemark, George J., Mark A. Brick, Juan M. Osorno, James D. Kelly, and Carlos A. Urrea. "Edible Grain Legumes." In Yield Gains in Major U.S. Field Crops, 87–123. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub33.c5.

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Sears, R. G. "Strategies for improving wheat grain yield." In Developments in Plant Breeding, 17–21. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-4896-2_3.

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Tollenaar, M., and E. A. Lee. "Strategies for Enhancing Grain Yield in Maize." In Plant Breeding Reviews, 37–82. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470880579.ch2.

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Strashnaya, Anna, Tamara Maksimenkova, and Olga Chub. "Grain Yield Prediction in the Russian Federation." In Use of Satellite and In-Situ Data to Improve Sustainability, 93–97. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9618-0_10.

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Schrock, M. D., D. K. Kuhlman, R. T. Hinnen, D. L. Oard, J. L. Pringle, and K. D. Howard. "Sensing Grain Yield With a Triangular Elevator." In Site-Specific Management for Agricultural Systems, 637–50. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1995.site-specificmanagement.c47.

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Missotten, B., G. Strubbe, and J. De Baerdemaeker. "Accuracy of grain and straw yield mapping." In Proceedings of the Third International Conference on Precision Agriculture, 713–22. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1996.precisionagproc3.c85.

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Bhatia, C. R., and R. Rabson. "Relationship of Grain Yield and Nutritional Quality." In Agronomy Monographs, 11–43. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/agronmonogr28.c2.

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Islam, Mirza Mofazzal, Shamsun Nahar Begum, and Rigyan Gupta. "High-yielding NERICA mutant rice for upland areas and hope for Bangladeshi farmers." In Mutation breeding, genetic diversity and crop adaptation to climate change, 53–64. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249095.0006.

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Abstract Drought is an important stress phenomenon in Bangladesh that greatly hampers crop production. So, it is imperative to develop drought-tolerant rice varieties. Low-yielding, non-uniform flowering and late-maturing Africa rice - New Rice for Africa (NERICA), viz. NERICA-1, NERICA-4 and NERICA-10 varieties - were irradiated with different doses of gamma-rays (250, 300 and 350 Gy) in 2010. M1 plants were grown and M2 plants were selected based on earliness and higher grain yield. The desired mutants along with other mutants were grown as the M3 generation during 2011. A total of 37 mutants from NERICA-1, NERICA-4 and NERICA-10 were selected on the basis of plant height, short duration, drought tolerance and high yield in the M4 generation. In the M5 generation, six mutants were selected for drought tolerance, earliness, grain quality and higher yield. With respect to days to maturity and grain yield (t/ha), the mutant N1/250/P-2-6-1 of NERICA-1 matured earlier (108 days) and had higher grain yield (5.1 t/ha) than the parent. The mutant N4/350/P-4(5) of NERICA-4 also showed a higher grain yield (6.2 t/ha) than its parent and other mutants. On the other hand, NERICA-10 mutant N10/350/P-5-4 matured earlier and had a higher yield (4.5 t/ha) than its parent. Finally, based on agronomic performance and drought tolerance, the two mutants N4/350/P-4(5) and N10/350/P-5-4 were selected and were evaluated in drought-prone and upland areas during 2016 and 2017. These two mutants performed well with higher grain yield than the released upland rice varieties. They will be released soon for commercial cultivation and are anticipated to play a vital role in food security in Bangladesh.
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Lamb, J. A., J. L. Anderson, G. L. Malzer, J. A. Vetch, R. H. Dowdy, D. S. Onken, and K. I. Ault. "Perils of Monitoring Grain Yield On-The-Go." In Site-Specific Management for Agricultural Systems, 87–90. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1995.site-specificmanagement.c7.

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Conference papers on the topic "Grain yield"

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Chenghai Yang, James H. Everitt, and Joe M. Bradford. "Airborne Hyperspectral Imaging and Yield Monitoring of Grain Sorghum Yield Variability." In 2002 Chicago, IL July 28-31, 2002. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2002. http://dx.doi.org/10.13031/2013.9318.

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Nathan Hemming and Jonathan Chaplin. "Precision of Real Time Grain Yield Data." In 2004, Ottawa, Canada August 1 - 4, 2004. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2004. http://dx.doi.org/10.13031/2013.17880.

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KALAShNIKOV, Maksim, and Nadezhda KOCAREVA. "Yield of sugar corn depending on sowing time." In Multifunctional adaptive fodder production 29 (77). ru: Federal Williams Research Center of Forage Production and Agroecology, 2022. http://dx.doi.org/10.33814/mak-2022-29-77-76-80.

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The results of cultivation of sugar corn in the agricultural enterprise CJSC Pobeda of the Belgorod district of the Belgorod region are presented. As a result of the work, it was found that the yield of sweet corn depends on the timing of sowing. The yield of cobs and grains of corn of the main hybrid Royalty F1, cultivated on the farm, increased at the time of sowing, starting from the second decade of May, from 16.26 t/ha to 23.38 t/ha. The replacement of the main hybrid Royalty F1 with new hybrids led to a loss in yield of both cobs and grain yield of sugar corn for all sowing dates. According to the yield of grain from one cob, no definite dependence on the timing of sowing was noted.
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Xu Xingmei, Cao Liying, Zhou Jing, and Su Fengyan. "Study and application of grain yield forecasting model." In 2015 4th International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2015. http://dx.doi.org/10.1109/iccsnt.2015.7490829.

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Xincheng Li, Minzan Li, Lihua Zheng, Hong Sun, and Wei Yang. "A Remote Operating System of Grain Yield Monitor." In 2013 Kansas City, Missouri, July 21 - July 24, 2013. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2013. http://dx.doi.org/10.13031/aim.20131620122.

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Luo, Yifan, Kunio Tei, Ken Suzuki, and Hideo Miura. "Crystallinity-Induced Variation of the Yield Strength of Electroplated Copper Thin Films." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70302.

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The quality of grains and grain boundaries of polycrystalline copper thin films was analyzed by using image quality (IQ) value obtained from the observed Kikuchi pattern by applying electron back-scatter diffraction (EBSD) analysis. It is considered that the IQ value strongly correlates with the order of atomic configuration in the observed area, in other words, density of various defects, and thus, the area with high IQ value was defined as the area with high crystallinity. The yield strength of a grain was measured by using micro tensile test system in a scanning electron microscope. A bicrystal structure which had two grains with different IQ values was cut from a copper thin film by using focus ion beam (FIB) and the sample was fixed to a single-crystalline silicon beam and a micro probe, respectively, by tungsten deposition. Finally it was thinned to 1μm and stretched to fracture at room temperature. In this micro tensile test, however, the tungsten deposition on the side surface of the test samples caused serious error on the measured strength. Therefore, in this study, the experimental method was improved by the development of an effective method for elimination the excess tungsten deposition. During the tensile test, a mass of plastic deformation and necking phenomenon were obviously observed. Ductile fracture always occurred in the grain with higher Schmidt factor. It was found that the yield strength of a copper grain decreased monotonically with the increase in the IQ value when the IQ value at the grain boundary was larger than 3500.
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Lian, Jie, Javier Garay, and Junlan Wang. "Effect of Grain Size and Grain Boundary on Mechanical Yielding Behavior of Fully Stabilized Zirconia." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15418.

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Mechanical properties of fully yttria stabilized zirconia (F-YSZ) with different grain sizes were investigated using instrumented indentation. While the grain size effect on the yield strength was performed on both the coarse-grained and fine-grained F-YSZ, the grain boundary effect was studied on the coarse-grained F-YSZ by performing nanoindentation within the grains and on/near the grain boundaries. Little variations were observed on mechanical properties such as hardness and reduced modulus, interesting results were obtained on the grain boundary effect on the yielding load for the course-grained F-YSZ.
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Mikos-Szymańska, Marzena, Mieczysław Borowik, Marta Wyzińska, and Piotr Rusek. "Effects of different fertilizer treatments on grain yield and yield components of spring wheat." In Research for Rural Development, 2018. Latvia University of Life Sciences and Technologies, 2018. http://dx.doi.org/10.22616/rrd.24.2018.058.

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Michihisa Iida, Yong Yao, Atsushi Kimura, and Mikio Umeda. "Development of Grain Yield Monitor for Head-feeding Combines." In 2005 Tampa, FL July 17-20, 2005. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2005. http://dx.doi.org/10.13031/2013.18872.

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Farouk, Issame, Fatima Gaboun, Zakaria Kehel, Ahmad Alsaleh, Bouchra Belkadi, Ismahane Elouafi, Jihan Motowaj, Abdelkarim Filali maltouf, and M. Miloudi Nachit. "Dissection of QTL linked to grain yield and identification of candidate genes involved in grain yield formation using comparative SNP sequences analysis." In 2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2020. http://dx.doi.org/10.1109/iraset48871.2020.9091989.

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Reports on the topic "Grain yield"

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Bracke, Marianne. Agronomy / Grain Yield - Purdue University. Purdue University Libraries, November 2011. http://dx.doi.org/10.5703/1288284314992.

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Gibson, Lance R., Aaron J. Schwarte, David N. Sundberg, and Douglas L. Karlen. Planting Date Effects on Winter Triticale Grain Yield. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-2748.

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Gibson, Lance R., Aaron J. Schwarte, David N. Sundberg, and Douglas L. Karlen. Planting Date Effects on WinterTriticale Grain and Forage Yield. Ames: Iowa State University, Digital Repository, 2005. http://dx.doi.org/10.31274/farmprogressreports-180814-902.

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Akkol, Suna, Diğdem Arpalı, and Mehmet Yağmur. Adaptive Lasso Analysis for Grain Yield and Yield Components in Two-rowed Barley under Rainfed Conditions. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, September 2018. http://dx.doi.org/10.7546/crabs.2018.09.17.

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Al-Kaisi, Mahdi. Corn Residue Removal Effects on Grain Yield and Soil Quality. Ames: Iowa State University, Digital Repository, 2009. http://dx.doi.org/10.31274/farmprogressreports-180814-1001.

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Licht, Mark A. Corn Residue Removal Effects on Grain Yield and Soil Quality. Ames: Iowa State University, Digital Repository, 2010. http://dx.doi.org/10.31274/farmprogressreports-180814-2701.

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Killorn, Randy, Marianela Gonzalez, Jeffrey Moore, and David Haden. Effect of Controlled-Release N Fertilizer on Corn Grain Yield. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-621.

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Archontoulis, Sotirios, Mark Licht, and Ranae Dietzel. In-Season Forecasting of Plant Growth, Soil Water-Nitrogen, and Grain Yield. Ames: Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/farmprogressreports-180814-1412.

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Archontoulis, Sotirios, Mark Licht, Raziel Antonio Ordonez, and Emily Wright. In-Season Forecasting of Plant Growth, Soil Water-Nitrogen, and Grain Yield. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-2048.

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McClure, Joseph, Dale E. Farnham, and Bernard J. Havlovic. Planting Date Effects on Yield and Grain Composition of High Oil Corn. Ames: Iowa State University, Digital Repository, 2001. http://dx.doi.org/10.31274/farmprogressreports-180814-2118.

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