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1

Tsuji, Shojiro. "Analysis on pasting properties of corn and waxy corn starches." NIPPON SHOKUHIN KOGYO GAKKAISHI 35, no. 11 (1988): 748–54. http://dx.doi.org/10.3136/nskkk1962.35.11_748.

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2

Bucchini, Luca, and Lynn R. Goldman. "Starlink corn: a risk analysis." Environmental Health Perspectives 110, no. 1 (January 2002): 5–13. http://dx.doi.org/10.1289/ehp.021105.

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3

Tong, Jin, Bai Gong Zeng, Dong Hui Chen, Long Zhe Quan, and Shu Jun Zhang. "Finite Element Modal Analysis of the Frame of Corn Stubble-Collector." Advanced Materials Research 430-432 (January 2012): 1072–75. http://dx.doi.org/10.4028/www.scientific.net/amr.430-432.1072.

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In this paper, one kind of agriculture machines with picking and separating soil was designed to collect corn stubble. The core component of the machine is the frame of corn stubble-collector. The 3-D solid model of the frame of corn stubble-collector was designed using Pro/Engineer software. The first 10 natural frequencies and vibration modes of the frame were obtained by means of the finite element modal analysis in the ANSYS-Workbench software, and analyze the dynamic characteristics of the frame, which can be used to provide some theory basis for design and optimization of the frame.
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4

Drennan, N., and J. Munroe. "Corn Syrup Analysis Check Service (CSACS)." Journal of the American Society of Brewing Chemists 44, no. 3 (June 1986): 145–46. http://dx.doi.org/10.1094/asbcj-44-0145b.

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5

Hodgson, John. "Doubts linger over Mexican corn analysis." Nature Biotechnology 20, no. 1 (January 2002): 3–4. http://dx.doi.org/10.1038/nbt0102-3.

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6

Pengelly, Jasper J. L., Scott Kwasny, Soumi Bala, John R. Evans, Elena V. Voznesenskaya, Nuria K. Koteyeva, Gerald E. Edwards, Robert T. Furbank, and Susanne von Caemmerer. "Functional Analysis of Corn Husk Photosynthesis." Plant Physiology 156, no. 2 (April 21, 2011): 503–13. http://dx.doi.org/10.1104/pp.111.176495.

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7

Johri, M. M., and E. H. Coe. "Clonal analysis of corn plant development." Genetica 97, no. 3 (May 1996): 291–303. http://dx.doi.org/10.1007/bf00055315.

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8

Zhang, Beili. "Corn Products International (CPI) Financial analysis." E3S Web of Conferences 275 (2021): 01021. http://dx.doi.org/10.1051/e3sconf/202127501021.

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Corporation financial analysis is crucial for accounting research, including background and environment, revenue and profit, different kinds of financial ratios. This paper will analyze Corn Products International, a corn refining and ingredient companies.
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9

Ma, Chengye, Yuyan Fan, Shuhua Wu, Zhehao Zhang, and Dongliang Zhang. "Analysis of the Complex Index of Extruded Corn Starch and Degermed Corn." Journal of Food Research 6, no. 6 (October 29, 2017): 56. http://dx.doi.org/10.5539/jfr.v6n6p56.

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Commercial corn starch or degermed corn contains lipids and protein, and starch-lipid (or protein) complexes were formed during extrusion. The formation of starch and lipid (or protein) complexes was investigated using the complex index (CI) and differential scanning calorimetry (DSC) analysis. The CI of extrudates of a commercial corn starch/germ mixture (or gluten meal) showed that starch was complexed with lipid or protein, thus decreasing the iodine-binding capacity of amylose. The CI increased as the content of germ or gluten meal blending starch increased. Blends containing degermed corn and thermostable or mesophilic α-amylase were extruded. The CI of extrudates was higher than 55%; however, the starch-lipid complex was not stable and could be separated. The DSC analysis of the blending starch extrudate and palmitic acid showed that the enthalpy of the starch-palmitic acid complex was increased with increasing fatty acid content. Increased complex formation required more DSC heating, resulting in an enthalpy change of the endothermic peak rise, with the peak temperature higher than 100℃.
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10

Ou, Longwen, Tristan R. Brown, Rajeeva Thilakaratne, Guiping Hu, and Robert C. Brown. "Techno-economic analysis of co-located corn grain and corn stover ethanol plants." Biofuels, Bioproducts and Biorefining 8, no. 3 (February 24, 2014): 412–22. http://dx.doi.org/10.1002/bbb.1475.

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11

Hu, Dong Fang, and Yan Ping Du. "Strength Analysis of Corn Combine Harvester Chassis." Applied Mechanics and Materials 644-650 (September 2014): 489–92. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.489.

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As the installed base of all other assemblies, the corn combine harvester chassis supports a variety of loads from the harvester and ground, so its reliability directly affects the quality and safety of the corn combine harvester. The analysis of corn combine harvester chassis was carried out with finite element analysis software. First, the 3D part of the chassis was established and simplified in accordance with the relevant principles. Second, the stress distribution and displacement of the chassis in the no-loaded and full-loaded conditions were calculated by meshing,applying loads and constraining boundary conditions. The analysis result is of great significance to enhance the quality and reliability of the chassis.
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12

Sikora, Marek, Magdalena Krystyjan, Anna Dobosz, Piotr Tomasik, Katarzyna Walkowiak, Łukasz Masewicz, Przemysław Łukasz Kowalczewski, and Hanna Maria Baranowska. "Molecular Analysis of Retrogradation of Corn Starches." Polymers 11, no. 11 (October 27, 2019): 1764. http://dx.doi.org/10.3390/polym11111764.

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Changes of the molecular dynamics of water in 5% corn starch pastes and 5% systems composed of starch and non-starchy hydrocolloid were studied during short and long term retrogradation. Low Field NMR was used to record mean correlation times (τc) of water molecules. This molecular parameter reflects the rotation of water molecules within the network of paste. Starches of different amylose and amylopectin content were selected for this study. Comparison of the changes of τc shows how particular polymers bind water molecules. During 90 days of storage, over 50% increase in mean correlation time was recorded in pastes of starches with high amylose content. This suggests that the formation of polymeric network is controlled by amylose to which water is binding. Amylopectin was found to influence the mobility of water in the pastes to a lesser extent with changes in mean correlation times of approximately 10–15% over 90 days. On retrogradation, amylopectin, Arabic and xanthan gums hindered the formation of solid phase structures. Guar gum evoked an increase in mean correlation times of approximately 40–50% during the prolonged process of changes of the molecular dynamics of water. This indicates continued expansion of the polymeric network. Mean correlation time available from spin–lattice and spin–spin relaxation times can be useful in the analysis of the rotational vibrations of the water molecules in biopolymeric structures.
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13

Sigulas, Kristen M. "Genetic Analysis ofExserohilum turcicumLesion Expansion on Corn." Phytopathology 78, no. 2 (1988): 149. http://dx.doi.org/10.1094/phyto-78-149.

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14

Moros, E. E., D. Darnoko, M. Cheryan, E. G. Perkins, and J. Jerrell. "Analysis of Xanthophylls in Corn by HPLC." Journal of Agricultural and Food Chemistry 50, no. 21 (October 2002): 5787–90. http://dx.doi.org/10.1021/jf020109l.

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15

Suddin, Andi Faisal, Muslimin, and Sarintang. "Corn margin analysis in Takalar, South Sulawesi." IOP Conference Series: Earth and Environmental Science 484 (June 20, 2020): 012139. http://dx.doi.org/10.1088/1755-1315/484/1/012139.

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16

Partridge, Bruce, Vitaly L. Spitsberg, Nancy E. Pfeiffer, and Sheldon M. Schuster. "Kinetic Analysis of Corn Mitochondrial F1-ATPase." Plant Physiology 77, no. 2 (February 1, 1985): 346–51. http://dx.doi.org/10.1104/pp.77.2.346.

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17

Overman, A. R., and R. V. Scholtz. "Model Analysis for Growth Response of Corn." Journal of Plant Nutrition 27, no. 5 (December 27, 2004): 885–906. http://dx.doi.org/10.1081/pln-120030677.

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18

Usubharatana, Phairat, and Harnpon Phungrassami. "ECOLOGICAL FOOTPRINT ANALYSIS OF CANNED SWEET CORN." Journal of Ecological Engineering 17, no. 3 (2016): 22–29. http://dx.doi.org/10.12911/22998993/63320.

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19

Miranda, M. T., F. J. Sepúlveda, J. I. Arranz, I. Montero, and C. V. Rojas. "Analysis of pelletizing from corn cob waste." Journal of Environmental Management 228 (December 2018): 303–11. http://dx.doi.org/10.1016/j.jenvman.2018.08.105.

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20

Limmatvapirat, Chutima, Chutipa Nateesathittarn, Kamol Dechasathian, Tharit Moohummad, Pana Chinajitphan, and Sontaya Limmatvapirat. "Phytochemical analysis of baby corn silk extracts." Journal of Ayurveda and Integrative Medicine 11, no. 3 (July 2020): 344–51. http://dx.doi.org/10.1016/j.jaim.2019.10.005.

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21

Xu, Xiaojie, and Yun Zhang. "Network analysis of corn cash price comovements." Machine Learning with Applications 6 (December 2021): 100140. http://dx.doi.org/10.1016/j.mlwa.2021.100140.

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22

Kadir, Laksmyn, Syam S. Kumaji, and Wirnangsi D. Uno. "Nutrition Analysis of “Sujakaju” as a Functional Drink of Health." Journal of Food Studies 7, no. 1 (September 2, 2018): 97. http://dx.doi.org/10.5296/jfs.v7i1.13369.

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Malnutrition, poverty and abundant corn crops are the factors that provide the potential for innovation to create “Sujakaju” (corn-soy mil). The innovation aims to tackle the issues in children health and welfare in Gorontalo. The purpose of this study is to generate the proper formulation of a combination of well-nutrition corn-soy milk. The study employed experimental method with four treatments; each treatment group consumes different kind of corn-soy milk, i.e. milk of pulo (waxy) corn and soybean, Kiki corn and soybeans, hybrid corn and soybean, and from sweet corn and soybean with ratio of 50:50, 100:50 and 150:50 respectively. The results show that milk from mixture pulo corn and soybean suits the most for well-nutrition corn-soy milk by the composition ratio of 150:50, in which it contains the highest carbohydrate and protein nutrition and the lowest fat, compared to the treatment of 50:50 and 100:50 ratios.
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23

Conrado, T. V., C. A. Scapim, L. S. Bignotto, R. J. B. Pinto, I. L. J. Freitas, A. T. Amaral Jr., and A. C. Pinheiro. "Diallel analysis of corn for special use as corn grits: determining the main genetic effects for corn gritting ability." Genetics and Molecular Research 13, no. 3 (2014): 6548–56. http://dx.doi.org/10.4238/2014.august.26.5.

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24

Coimbra, Ronaldo Rodrigues, Glauco Vieira Miranda, Newton Portilho Carneiro, Cláudia Teixeira Guimarães, Derly José Henriques da Silva, and Elainy Cristina Alves Martins Oliveira. "Molecular caracterization of a corn core collection–landraces subgroup." REVISTA AGRO@MBIENTE ON-LINE 12, no. 1 (December 23, 2017): 11. http://dx.doi.org/10.18227/1982-8470ragro.v12i1.4641.

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The efficient use of genetic resources- stored in germplasm collections can be maximized if morphoagronomic and molecular information on the accessions is made available. To achieve this, a collection that is well-structured, well-curated and easily accessible (the core collection) is required. Consequently, the objective of the current study was to characterize 80 landrace accessions from the maize core collection of the Federal University of Viçosa (UFV), and assay thenngenetic diversity of the various landraces, considering grain type and ecogeographic origin. For this, AFLP analysis was performed using 12 primer combinations. Genetic diversity of the collection was quantified with the UPGMA method, using the Jaccard Index to quantify dissimilarity. The core collection was divided into four sub-populations by grain type, and into six sub-populations based on ecogeographic origin. Genetic diversity analysis was performed both within and between sub-populations. A high level of genetic variability was found among the landrace accessions of UFV Core Collection, principally among those accessions with dentate type grains.Classification by grain type and ecogeographic origin allowed genetically divergent groups to be distinguished.
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25

Chen, Dong Hui, Heng Xie, Shao Bo Ye, Ting Wu, Xin Lu, and Zhi Yong Chang. "Bionic Jump Mechanism Analysis Based on Locust Hind." Applied Mechanics and Materials 461 (November 2013): 184–90. http://dx.doi.org/10.4028/www.scientific.net/amm.461.184.

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The structure of corn stubble was complex and closely combined with the soil, so dig location and root-soil separation are the urgent problem of the manufacturing of corn stubble harvesting machinery. This paper mainly focuses on investigating the interaction principles of corn stubble and soil which by the UU triaxial compression tests. Compared the shear strength of three different types of corn root-soil complexes (vertical root, horizontal root, complex root) and pure soil, and analyzed three important factors affecting the root-soil complex shear strength, it was shown that the presence of corn fibrous root can enhance the soil shear strength and different with their layout types. It will provide a theoretical basis for the design of bionic agricultural tillage components for root- soil separation.
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26

Liu, Sijun, Thomas W. Sappington, Brad S. Coates, and Bryony C. Bonning. "Nudivirus Sequences Identified from the Southern and Western Corn Rootworms (Coleoptera: Chrysomelidae)." Viruses 13, no. 2 (February 9, 2021): 269. http://dx.doi.org/10.3390/v13020269.

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Analysis of pooled genomic short read sequence data revealed the presence of nudivirus-derived sequences from U.S. populations of both southern corn rootworm (SCR, Diabrotica undecimpunctata howardi Barber) and western corn rootworm (WCR, Diabrotica virgifera virgifera LeConte). A near complete nudivirus genome sequence was assembled from sequence data for an SCR population with relatively high viral titers. A total of 147,179 bp was assembled from five contigs that collectively encode 109 putative open reading frames (ORFs) including 20 nudivirus core genes. In contrast, genome sequence recovery was incomplete for a second nudivirus from WCR, although sequences derived from this virus were present in three geographically dispersed populations. Only 48,989 bp were assembled with 48 putative ORFs including 13 core genes, representing about 20% of a typical nudivirus genome. Phylogenetic analysis indicated that both corn rootworm nudiviruses grouped with the third known nudivirus of beetles, Oryctes rhinoceros nudivirus in the genus Alphanudivirus. On the basis of phylogenetic and additional analyses, we propose further taxonomic separation of nudiviruses within Alphanudivirus and Betanudivirus into two subfamilies and five genera. Identification of nudivirus-derived sequences from two species of corn rootworm highlights the diversity of viruses associated with these agricultural insect pests.
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27

Wei, Huan Huan, Yun Long Liu, and Dong Yu Chen. "Analysis of Corn Straw Pyrolysis Bio-Oil Composition." Applied Mechanics and Materials 737 (March 2015): 14–19. http://dx.doi.org/10.4028/www.scientific.net/amm.737.14.

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The fast pyrolysis of corn straw in the fluidized bed reactor to produce bio-oil, the preliminary qualitative research on the composition of the bio-oil was analyzed by GC-MS to provide the basis for their purification, refining and long-term stability studies. The result shows that: the bio-oil producted by corn straw pyrolysis contains 66 components, mainly containing phenol, furan, acetic acid, propanoic acid, ethanone, vanillin, aldehyde, bio-oil water content is 33% and pH is 3.1, which has a great significance to improve the quality of bio-oil.
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28

Ruan, R. Roger, Paul L. Chen, and Simon Almaer. "Nondestructive Analysis of Sweet Corn Maturity Using NMR." HortScience 34, no. 2 (April 1999): 319–21. http://dx.doi.org/10.21273/hortsci.34.2.319.

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This paper describes the relationship between the maturity stages and nuclear magnetic resonance (NMR) characteristics of sweet corn (Zea mays L.). The NMR parameter T2, which is the spin–spin relaxation time constant, and two conventional maturity parameters, moisture content and alcohol insoluble solids (AIS), of sweet corn samples during maturation, were determined and correlated with reference maturity indices, namely, heat units and sensory maturity scores. The relationships between T2 and the heat unit and sensory maturity score of the samples were linear, suggesting that T2 can be used to establish mathematical models for the prediction of sweet corn maturity to determine harvest time. The major advantages of using NMR are the nondestructive nature, the speed, and the simplicity of the method.
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29

Szareski, Vinícius Jardel, Ivan Ricardo Carvalho, Kassiana Kehl, Alan Junior de Pelegrin, Maicon Nardino, Gustavo Henrique Demari, Mauricio Horbach Barbosa, et al. "Interrelations of Characters and Multivariate Analysis in Corn." Journal of Agricultural Science 10, no. 2 (January 12, 2018): 187. http://dx.doi.org/10.5539/jas.v10n2p187.

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The objective of this work was to evaluate the agronomic performance of corn hybrids, the interrelations of the characters with the grain yield, and to genetically discriminate the corn hybrids by means of the dispersion analysis of the canonical variables. The experiment was conducted in the agricultural crop of 2013/2014, in an area belonging to the Federal University of Santa Maria, Campus of Frederico Westphalen, RS. The experimental design was a randomized block design, with four replications. The treatments were composed of seven maize hybrids with different genetic bases and maturation cycles. The LG 6304 modified simple hybrid has higher grain yield than the others. The characters plant height, spike insertion height and number of grains per row of spike have positive interrelations with grain yield of corn hybrids. Hybrids are not grouped according to the genetic basis and maturation cycle. The canonical variables explain 94.62% of the existing genetic variation, and allows the formation of five groups of maize hybrids.
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30

Hyde, Jeffrey, Marshall A. Martin, Paul V. Preckel, Craig L. Dobbins, and C. Richard Edwards. "An economic analysis of non-Bt corn refuges." Crop Protection 20, no. 2 (March 2001): 167–71. http://dx.doi.org/10.1016/s0261-2194(00)00121-6.

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31

Hatima, H., A. R. Siregar, and Jusni. "Analysis of corn agribusiness revenue in Bulukumba Regency." IOP Conference Series: Earth and Environmental Science 492 (June 24, 2020): 012118. http://dx.doi.org/10.1088/1755-1315/492/1/012118.

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32

Jim G. Field, L. G. James, D. L. Bassett, and Keith E. Saxton. "An Analysis of Irrigation Scheduling Methods for Corn." Transactions of the ASAE 31, no. 2 (1988): 0508–12. http://dx.doi.org/10.13031/2013.30739.

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33

C. J. Bern, C. R. Hurburgh, and Jr. "Characteristics of Fines in Corn: Review and Analysis." Transactions of the ASAE 35, no. 6 (1992): 1859–67. http://dx.doi.org/10.13031/2013.28807.

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34

Romagnolo, D., C. E. Polan, and W. E. Barbeau. "Electrophoretic Analysis of Ruminal Degradability of Corn Proteins." Journal of Dairy Science 77, no. 4 (April 1994): 1093–99. http://dx.doi.org/10.3168/jds.s0022-0302(94)77044-2.

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35

Petter, Ryan, and Wallace E. Tyner. "Technoeconomic and Policy Analysis for Corn Stover Biofuels." ISRN Economics 2014 (February 4, 2014): 1–13. http://dx.doi.org/10.1155/2014/515898.

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Conventional fossil fuels dominate the marketplace, and their prices are a direct competitor for drop-in biofuels. This paper examines the impact of fuel selling price uncertainty on investment risk in a fast pyrolysis derived biofuel production facility. Production cost specifications are gathered from previous research. Monte Carlo analysis is employed with uncertainty in fuel selling price, biomass cost, bio-oil yield, and hydrogen price parameters. Experiments reveal that fuel price has a large impact on investment risk. A reverse auction would shift risk from the private sector to the public sector and is shown to be more effective at encouraging private investment than capital subsidies for the same expected public cost.
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36

Parris, Nicholas, Leland Dickey, and James Craig. "Quantitative Analysis of Corn Zeins by Capillary Electrophoresis." Cereal Chemistry Journal 74, no. 6 (November 1997): 766–70. http://dx.doi.org/10.1094/cchem.1997.74.6.766.

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37

Wu, Y. V., K. L. Payne-Wahl, and S. F. Vaughn. "Analysis of Headspace Volatiles of Corn Gluten Meal." Cereal Chemistry Journal 80, no. 5 (September 2003): 567–69. http://dx.doi.org/10.1094/cchem.2003.80.5.567.

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38

Tolaba, M. P., R. J. Aquerre, and C. Suarez. "SHAPE -ZATION FOR DIFFUSIOhW, ANALYSIS OF CORN DRYING." Drying Technology 7, no. 2 (June 1989): 205–17. http://dx.doi.org/10.1080/07373938908916587.

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39

Kidd, George, and James Dvorak. "A Porter analysis of the corn-genetics industry." Nature Biotechnology 13, no. 3 (March 1995): 211–12. http://dx.doi.org/10.1038/nbt0395-211.

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40

Hess, J. Richard, Kevin L. Kenney, Christopher T. Wright, Robert Perlack, and Anthony Turhollow. "Corn stover availability for biomass conversion: situation analysis." Cellulose 16, no. 4 (June 30, 2009): 599–619. http://dx.doi.org/10.1007/s10570-009-9323-z.

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41

Mehta, H., K. R. Sarkar, and S. K. Sharma. "Genetic analysis of photosynthesis and productivity in corn." Theoretical and Applied Genetics 84, no. 1-2 (June 1992): 242–55. http://dx.doi.org/10.1007/bf00224006.

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42

ORLANDI, PALMER A., KEITH A. LAMPEL, PAUL K. SOUTH, SAMIR K. ASSAR, LAURENDA CARTER, and DAN D. LEVY. "Analysis of Flour and Food Samples for cry9C from Bioengineered Corn." Journal of Food Protection 65, no. 2 (February 1, 2002): 426–31. http://dx.doi.org/10.4315/0362-028x-65.2.426.

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StarLink corn is a variety of yellow corn that has been genetically modified by the insertion of an altered cry9C gene into the plant genome, resulting in expression of the insecticidal Cry9C protein. The U.S. Environmental Protection Agency has approved StarLink corn for use in animal feed but not in food intended for human consumption. Therefore, under the U.S. Food, Drug, and Cosmetic Act, any food intended for human consumption in which the presence of StarLink corn is indicated by the presence of either the Cry9C protein or the cry9C gene would be considered adulterated. Extraction and PCR-based methods were used to detect the presence of the cry9C DNA initially in corn flour and corn meal, and then these methods were extended to the analysis of processed corn products, including taco shells, cereals, baby foods, party snacks, and chips, for the presence of this modified genetic material. In a survey of 63 products, the cry9C transgene was detected in 4 taco shells.
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43

Anindita, Ratya, Agnes Quartina Pudjiastuti, and Nur Baladina. "Food Self-Sufficiency Through Land Area Expansion (CGE Analysis in Indonesia)." KnE Life Sciences 2, no. 6 (November 26, 2017): 362. http://dx.doi.org/10.18502/kls.v2i6.1058.

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This study aimed to analyze the impact of land area expansion policy of paddy and corn crops towards food self-sufficiency in Indonesia. Analyses were performed by using CGE models based on the SAM data and Input Output Table of Indonesia in 2008. The result showed that the increase of land area of paddy and corn by 4-10%, the paddy production will rise 36,21-87,93%, while the corn production is relatively constant even going down to 0,55%. If the land of paddy and corn increased by 4-10%, it will decrease the export of almost all sectors in Indonesia, except the food and beverage industry whose increased 52-118,12%, as well as fertilizer and pesticide industries whose are relatively constant. On the other hand, the land area expansion of paddy and corn 4-10% will not affect the import of this commodity. Thus, it can be concluded that the land area expansion of paddy and corn crops have a positive impact on food self-sufficiency (rice and corn) in Indonesia. Keywords: land area expansion; paddy and corn crops; food self-sufficiency; CGE models
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44

Pilcher, Clinton D., and Marlin E. Rice. "Economic Analysis of Planting Dates to Manage European Corn Borer (Lepidoptera: Crambidae) with Bt Corn." Journal of Economic Entomology 96, no. 3 (June 1, 2003): 941–49. http://dx.doi.org/10.1093/jee/96.3.941.

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45

López, R., C. Fernández, J. Cara, O. Martínez, and M. E. Sánchez. "Differences between combustion and oxy-combustion of corn and corn–rape blend using thermogravimetric analysis." Fuel Processing Technology 128 (December 2014): 376–87. http://dx.doi.org/10.1016/j.fuproc.2014.07.036.

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46

Gardner, Jeffrey, Michael P. Hoffmann, Sylvie A. Pitcher, and Jayson K. Harper. "Integrating insecticides and Trichogramma ostriniae to control European corn borer in sweet corn: Economic analysis." Biological Control 56, no. 1 (January 2011): 9–16. http://dx.doi.org/10.1016/j.biocontrol.2010.08.010.

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47

Zhao, Ben, Xiaolong Wang, Syed Tahir Ata-Ul-Karim, Zhandong Liu, and Aiwang Duan. "Effect of Straw Incorporation on Corn Yield in North China: A Meta-Analysis." Journal of Biobased Materials and Bioenergy 13, no. 4 (August 1, 2019): 532–36. http://dx.doi.org/10.1166/jbmb.2019.1872.

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Crop straw incorporation (SI) is as an effective method of soil improvement, which is playing an increasingly important role in improving corn productivity, soil fertility and reducing nitrogen leaching and ammonia volatilization in North China. We conducted a meta-analysis to examine the effect of crop SI on corn yield in North China, and to investigate how the effect varies with region, climate, soil, duration of crop SI, cropping system, and application of inorganic fertilizer (nitrogen, phosphorus, potassium). Results indicated that crop SI significantly increased corn yield by 12.3% in North China. Crop SI had the most significant effect on improving corn yield under the annual precipitation ≤ 400 mm (18.6%) and mean temperature > 12 °C (15.4%) environment. The change rate of corn yield was higher with the experimental duration of 2–3 years (13.3%) than that of ≥4 years (8.52%). Corn yield responses to crop SI in the corn–corn cropping system (10.42%) were not as obvious as that in the corn–wheat cropping system (14.73%). Therefore, we conclude that crop SI could significantly increase corn yield, which can reduce environmental pollution and add farmer income.
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48

Siagian, Viktor, Resmayeti, Silvia Yuniarti, and Ismatul Hidayah. "Analysis of factors that influence production and cost of corn in Banten province." E3S Web of Conferences 232 (2021): 01007. http://dx.doi.org/10.1051/e3sconf/202123201007.

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Banten Province on the 2019 year has to harvest area of corn was 66,356 ha with 331,865.38 tons production and the highest production in Pandeglang Regency. The purpose of this study was: 1) Knowing the pattern of corn farming in Banten Province, 2) Knowing the factors of production that affect corn production. 3) Knowing the cost factors that affect the cost of corn production. The analytical method used multiple linear analysis of the Cobb Douglas production and cost function. The results of the study were: 1) The planting pattern of corn was corn-corn - fallow. Dominant varieties were NK-212 (75.8%), Bima (12.1%) and BISI-18 (12.1%). Average productivity in RS 2018/2019 was 3.44 tons of dry shelled ha-1. The B/C ratio is 0.7, it’s mean financially not profitable.2) Factors that significantly affect corn production were: number of seeds, amount of manure, and number of tractors rent, and variety dummy. A cumulative elasticity value of 1.0 means corn farming was efficient. 3) Factors that significantly influence the cost of production were liquid herbicide prices and human labor costs. Increasing corn productivity still needs to be done with the use of proportional farming inputs.
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49

Yu, Ya Jun, Ji Yang Yu, Qing Long Li, Jian Qun Yu, and Hong Fu. "Analysis on the Contact Interaction between Thresher and Corn Ears Based on the DEM." Applied Mechanics and Materials 246-247 (December 2012): 71–77. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.71.

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The corn threshing process is a complex process of contact interaction between thresher mechanical parts and corn ears. The paper analyzed this process with the discrete element method (DEM). A method was set up to calculate the contact forces between thresher mechanical parts (boundary) and corn ears. The conditions for corn kernels threshing were established as well. On this basis, we developed the corn threshing simulation software, and simulated the corn threshing process using the software. The simulation results are close to the actual situation, and the results verify the feasibility and effectiveness of the new method. Thus we have laid the foundation for using the DEM to analyze the corn threshing process and putting forward a novel method for the optimal design of the corn thresher.
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50

Hu, Hong Sheng, Qun Feng Niu, and Bo Yuan Cui. "Research on Ultra-Weak Bioluminescence Detection and Features for Freshness of Corn." Applied Mechanics and Materials 727-728 (January 2015): 239–43. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.239.

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Detection of ultra-weak bioluminescence for freshness of corn is not only a problem of corn safe storage but also related to corn quality. The paper built a Virtual Instrument platform based on LabVIEW and PXI4220 modularized hardware of NI. Then, a testing and analysis system for corn ultra-weak bioluminescence features was designed. Different freshness corns were tested and analyzed about the relation of freshness and ultra-weak bioluminescence features. The experimental results shows that the ultra-weak bioluminescence voltage peak values of different freshness corns all maximize about 1 hour, and voltage peak values between different freshness corns have no evident relationship. However, the ultra-weak bioluminescence voltage energy sum of different freshness corns increase progressively with the freshness degree. So, detection of voltage energy sum of different freshness corns can reflect wheat freshness effectively. Comparing with traditional method, the freshness detection method based on wheat ultra-weak bioluminescence features can realize precise, rapid and nondestructive examination.
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