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Precision management of corn for opt...

Miao, Yuxin.

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Precision management of corn for optimum yield and grain quality.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Precision management of corn for optimum yield and grain quality./
Author:	Miao, Yuxin.
Description:	263 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6118.
Contained By:	Dissertation Abstracts International65-12B.
Subject:	Agriculture, Soil Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3156783
ISBN:	9780496174775

Precision management of corn for optimum yield and grain quality.
Miao, Yuxin.

Precision management of corn for optimum yield and grain quality. - 263 p.

Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6118.

Thesis (Ph.D.)--University of Minnesota, 2005.

Precision crop management needs to be site-, weather-, variety-, and end use-specific, in order to realize the management objectives of maximized profitability, sustainability and protection of the environment. This study was conducted to determine the magnitude of spatial variability in corn quality, characterizing their spatial structures, identifying important influencing factors, and evaluating the potential of precision N management to optimize both grain yield and quality.

ISBN: 9780496174775Subjects--Topical Terms:

1017824
Agriculture, Soil Science.

Precision management of corn for optimum yield and grain quality.
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100 1 $a Miao, Yuxin. $3 1912487
245 1 0 $a Precision management of corn for optimum yield and grain quality.
300 $a 263 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6118.
500 $a Advisers: David J. Mulla; Pierre C. Robert.
502 $a Thesis (Ph.D.)--University of Minnesota, 2005.
520 $a Precision crop management needs to be site-, weather-, variety-, and end use-specific, in order to realize the management objectives of maximized profitability, sustainability and protection of the environment. This study was conducted to determine the magnitude of spatial variability in corn quality, characterizing their spatial structures, identifying important influencing factors, and evaluating the potential of precision N management to optimize both grain yield and quality.
520 $a This study was conducted on two commercial farms in Paris, Illinois involving six corn hybrids, five N application rates (0, 112, 168, 224, and 336 kg ha -1), three no-till fields, three reduced-tillage fields and four years (2000--2003). In each field, two corn hybrids were planted side-by-side to facilitate the comparison of hybrid differences in yield, quality, and their responses to environmental conditions and/or N management.
520 $a The results indicate that spatial variability in corn yield and grain quality is smaller than soil variability. Hybrid is the most important factor influencing corn quality, and it is possible to select hybrids with both optimum yield and quality. Both corn yield and quality responses to N vary spatially, temporally and with hybrids. Compared with uniform N application at 168 kg ha-1, precision N application at year-, hybrid- and site-specific economically optimum N recommendations (EONRs) for yield has the potential to increase N use efficiency (NUE) and economic returns, but does not significantly increase corn quality or reduce its variability. Combining soil-landscape and yield spatial-temporal variability information is a very robust approach for delineating site-specific management zones.
520 $a We conclude that the most practical approach to optimize both corn yield and quality is to select suitable hybrids with high quality and yield, and then apply hybrid- and management zone-specific EONRs that can maximize long-term average (15--30 years) yield (or economic returns), as determined by simulating corn N responses across different weather conditions using a crop growth model. More studies are needed to develop in-season N management strategies that are responsive to weather.
590 $a School code: 0130.
650 4 $a Agriculture, Soil Science. $3 1017824
650 4 $a Agriculture, Agronomy. $3 1018679
650 4 $a Engineering, Agricultural. $3 1019504
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710 2 0 $a University of Minnesota. $3 676231
773 0 $t Dissertation Abstracts International $g 65-12B.
790 1 0 $a Mulla, David J., $e advisor
790 1 0 $a Robert, Pierre C., $e advisor
790 $a 0130
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3156783