Soil sensing and machine learning reveal factors affecting maize yield in the mid-Atlantic United States (Record no. 66002)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02874nab|a22003737a|4500 |
| 001 - CONTROL NUMBER | |
| control field | 66002 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251210153752.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 20231s2023||||mx |||p|op||||00||0|eng|d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER | |
| International Standard Serial Number | 0002-1962 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER | |
| International Standard Serial Number | 1435-0645 (Online) |
| 024 8# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | https://doi.org/10.1016/j.compag.2022.106965 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | MX-TxCIM |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Kinoshita, R. |
| 9 (RLIN) | 2600 |
| 245 10 - TITLE STATEMENT | |
| Title | Soil sensing and machine learning reveal factors affecting maize yield in the mid-Atlantic United States |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | American Society of Agronomy : |
| -- | Wiley, |
| Date of publication, distribution, etc. | 2022. |
| Place of publication, distribution, etc. | Madison, WI (USA) : |
| 500 ## - GENERAL NOTE | |
| General note | Peer review |
| 500 ## - GENERAL NOTE | |
| General note | Early View |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | In large-scale arable cropping systems, understanding within-field yield variations and yield-limiting factors are crucial for optimizing resource investments and financial returns, while avoiding adverse environmental effects. Sensing technologies can collect various crop and soil information, but there is a need to assess whether they reveal within-field yield constraints. Spatial data regarding grain yields, proximal soil sensing data, and topographical and soil properties were collected from 26 maize (Zea mays L.) growing fields in the U.S. Mid-Atlantic. Apparent soil electrical conductivity (ECa) collected by an on-the-go sensor (Veris) was an effective method for estimating subsoil textural variation and water holding capacity in the Coastal Plain region, which was also the best predictor of spatial yield pattern when combined with surface pH and topographic wetness index in a Random Forest (RF) model. In the Piedmont Plateau region, proximal soil sensors showed a lower correlation to measured soil properties, while topographical properties (aspect and slope) were important estimators of spatial yield patterns in an RF model. In locations where the RF model failed to predict yield variation, soil compaction appeared to be limiting crop yields. In conclusion, the application of RF models using ECa sensors and topographical properties was effective in revealing within-field yield constraints, especially in the Coastal Plain region. On the Piedmont Plateau, the calibration of proximal sensor information needs to be improved with a particular focus on soil compaction. |
| 546 ## - LANGUAGE NOTE | |
| Language note | Text in English |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Soil |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 4828 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 11127 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Maize |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 1173 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Yields |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 1313 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Sensors |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 2530 |
| 651 #7 - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Source of heading or term | AGROVOC |
| 9 (RLIN) | 29087 |
| Geographic name | United States of America |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Tani, M. |
| 9 (RLIN) | 29876 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Sherpa, S.R. |
| Field link and sequence number | 001712516 |
| Miscellaneous information | Sustainable Agrifood Systems |
| 9 (RLIN) | 28790 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ghahramani, A. |
| 9 (RLIN) | 29877 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | van Es, H.M. |
| 9 (RLIN) | 2607 |
| 773 0# - HOST ITEM ENTRY | |
| Title | Agronomy Journal |
| Related parts | In press |
| Place, publisher, and date of publication | Madison, WI (USA) : American Society of Agronomy : Wiley, 2022. |
| International Standard Serial Number | 0002-1962 |
| Record control number | 444482 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Article |
| Suppress in OPAC | No |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Date last seen | Total Checkouts | Price effective from | Koha item type | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Withdrawn status | Home library | Current library | Date acquired |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01/31/2023 | 01/31/2023 | Article | Not Lost | Dewey Decimal Classification | CIMMYT Staff Publications Collection | CIMMYT Knowledge Center: John Woolston Library | CIMMYT Knowledge Center: John Woolston Library | 01/31/2023 |