Paper · 1997 · jpa

Spatial and Temporal Stability of Corn Grain Yields

J. A. Lamb; R. H. Dowdy; J. L. Anderson; et al.

8
claims
16
verbatim quotes
81
citations
1
research areas
—
Not open access

Abstract

Year‐to‐year consistency of crop yields within a farm field is needed to use grain yield monitor data for site‐specific management decisions such as yield goals for fertilizer recommendations. A 5‐yr study was conducted from 1991 to 1995 to determine whether patterns of corn ( Zea mays L.) grain yields are similar over a number of years and whether grain yields from one or more years can be used to predict grain yields for subsequent years. The experimental site was located at the Northern Cornbelt Sand Plain Management Systems Evaluation Area near Princeton, MN. The research area was 4.4 acres with soils mapped as three variants of the Zimmerman fine sand (mixed, frigid, argic, Udipsamment) and a Cantlin loamy fine sand (sandy, mixed, frigid, typic, Udipsamment). Continuous corn was grown from 1990 through 1995 after alfalfa ( Medicago saliva L.) from 1981 through 1989. Cultural practices were applied uniformly to the 4.4 acre site each year. The 4.4 acres were divided into 60 grid cells (50 ft. by 60 ft.) and grain yields, corrected to 15.5% moisture, were determined by hand harvesting an area (two rows 20 ft. long) within each of the 60 grid cells. Differences between highest and lowest continuous corn grain yields in the research area were 72 bu/acre in 1991, 44 bu/acre in 1992, 45 bu/acre in 1993, 51 bu/acre in 1994, and 57 bu/acre in 1995. Grain yields were not spatially consistent from year to year. Areas with better grain yields were not consistent from year to year, and conversely, poor production areas were not found in similar locations each year. Only 4 to 42% of the grain yield variability for a given year is accounted for by a knowledge of the grain yields from a previous year. The lack of grain yield stability as measured by ranked correlations on a sandy soil raises serious questions for the potential for use of this information. The data indicate that the use of grain yield maps for fertilizer recommendations on a site specific basis may not be possible or may require a much longer term database than the normally recommended 5 yr, unless there is a construct of inputs that explains the grain yield patterns each year. Research Question With variable rate technology it is possible to make changes in the application of crop production inputs on the go. Fertilizer recommendations are often adjusted for yield goal. Therefore, it is important to have some measure of consistent yield patterns across a landscape. Are differences in yields across a field consistent over time? Can measured differences in yield be used to established more realistic yield goals? Literature Summary Growers usually know that certain areas of their production fields produce more yield than others. Until recently, the technology to measure and locate the variability of yields has not been available. Yield goals have been used to develop fertilizer recommendations in the Upper Midwest. Before the development of yield monitoring technology, yield goals were usually based on production information from entire fields. Now yield goals can be adjusted for differences in production potential that occur across the field. In some fields, these differences can be considerable, and can affect grain yields and, thus, fertilizer recommendations. To date, differences in yield potential have been related to chemical and physical properties of soils, which are documented in modern soil surveys. Research to document stability of grain yield over years is limited. Some knowledge of spatial and temporal stability of yields should help producers establish more realistic yield goals and manage production inputs more effectively. Study Description A study was conducted from 1991 to 1995 to determine whether spatial patterns of corn yield are similar over a number of years and whether grain yield from one or more years can be used to predict grain yields for subsequent years. The experimental site was located at the Northern Cornbelt Sand Plain Management Systems Evaluation Area near Princeton, MN. The research area was 4.4 acres, containing four major soil types. The cropping system was continuous corn since 1990, preceded by alfalfa from 1981 to 1989. Cultural practices were applied uniformly to the 4.4 acre site. Grain yields corrected to 15.5% moisture were determined by hand harvesting an area (two rows 20 ft long) within each of 60 grid cells (50 ft. by 60 ft.) located in the research area. The data were analyzed by statistical procedures similar to those used by plant breeders to determine the stability of a variety over several environments. Applied Questions What is the variability in corn yields across a field? In the 4.4 acre field used in this study, differences between the least and greatest corn grain yields among grid cells in any given year ranged from 44 bu/acre to 72 bu/acre. This field was managed as uniformly as possible in terms of water, pesticide, and fertilizer applications. Do areas of similar relative grain yield occur in the same location in a production field over time? The relationship between relative yield and location in the field during the 5 yr study was not strong (Fig. .). Visual and statistical analyses confirm the poor relationship. During the 5 yr of the study, only 3.3% of the grid cells were in the same relative yield category (10% intervals < 61, 61 to 70, 71 to 80, 81 to 90, and 91 to 100% of maximum yield for each year). Thirty‐eight percent had relative yields within two relative yield categories. The remainder of the grid cells (58.7%) varied more. Can a grain yield map from previous production years be useful in establishing yield goals for the next year's fertilization program? Relative grain yields for each grid cell location from 1991 to 1995 at Princeton, MN. image Grain yield maps for four previous years could only account for 46% of the 1995 grain yield variability. Using the strategy to discard the lowest yielding year (1993) and the highest yielding year (1991), 32% of the 1995 yield variability could be predicted from yields in previous years. Recommendations The information from this study suggests that grain yield variability can be substantial even in intensively managed fields believed to be uniform. The lack of grain yield stability on a sandy soil causes some concern for many practical applications of this information that might be used on fields that are much more variable. Using grain yield maps for fertilizer recommendations on a site specific basis may not be possible without identifying agents causing the grain yield variability.

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Claims 8

Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Grain yields were not spatially consistent from year to year.

Outcome
spatially consistente3
Qualifier
from year to yeare3

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e3

“Grain yields were not spatially consistent from year to year”

✓ located verbatim in the source · abstract, characters 1368–1428 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Poor production areas of corn were not found in similar locations each year.

Outcome
poor production arease4
Qualifier
not found in similar locations each yeare4

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e4

“Areas with better grain yields were not consistent from year to year, and conversely, poor production areas were not found in similar locations each year”

✓ located verbatim in the source · abstract, characters 1430–1583 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Areas with better corn grain yields were not consistent from year to year.

Outcome
Areas with better grain yieldse4
Qualifier
were not consistent from year to yeare4

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e4

“Areas with better grain yields were not consistent from year to year, and conversely, poor production areas were not found in similar locations each year”

✓ located verbatim in the source · abstract, characters 1430–1583 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Previous-year grain yields accounted for only 4 to 42% of the grain yield variability in a given year.

Outcome
grain yield variabilitye5
Value
4 to 42%e5
Qualifier
accounted for by a knowledge of the grain yields from a previous yeare5

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e5

“Only 4 to 42% of the grain yield variability for a given year is accounted for by a knowledge of the grain yields from a previous year”

✓ located verbatim in the source · abstract, characters 1585–1719 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Grain yield maps from four previous years could only account for 46% of the 1995 grain yield variability.

Outcome
1995 grain yield variabilitye6
Value
46%e6
Qualifier
Grain yield maps for four previous years could only account fore6

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e6

“Grain yield maps for four previous years could only account for 46% of the 1995 grain yield variability”

✓ located verbatim in the source · abstract, characters 5786–5889 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Discarding the lowest and highest yielding years, 32% of the 1995 yield variability could be predicted from previous yields.

Outcome
1995 yield variabilitye7
Value
32%e7
Qualifier
discard the lowest yielding year (1993) and the highest yielding year (1991)e7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e7

“Using the strategy to discard the lowest yielding year (1993) and the highest yielding year (1991), 32% of the 1995 yield variability could be predicted from yields in previous years”

✓ located verbatim in the source · abstract, characters 5891–6073 · show in text ↑
Observationauthor interpretationoriginal resultmeasured

Claim · model-written summary

Grain yield variability can be substantial even in intensively managed fields believed to be uniform.

Outcome
grain yield variabilitye7
Qualifier
can be substantial even in intensively managed fields believed to be uniforme7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e7

“The information from this study suggests that grain yield variability can be substantial even in intensively managed fields believed to be uniform”

✓ located verbatim in the source · abstract, characters 6091–6237 · show in text ↑
Recommendationauthor interpretationoriginal resultbasis n/a

Claim · model-written summary

The authors conclude that site-specific yield-map fertilizer recommendations may not be possible without identifying causes of yield variability.

Outcome
fertilizer recommendations on a site specific basise7
Qualifier
without identifying agents causing the grain yield variabilitye7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays subsp. mays
Zea mays subsp. mays · TaxonDominicus Johannes Bergsma · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51 · show in text ↑
e7

“Using grain yield maps for fertilizer recommendations on a site specific basis may not be possible without identifying agents causing the grain yield variability”

✓ located verbatim in the source · abstract, characters 6419–6580 · show in text ↑