Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots
The current study investigates the performance of various sampling designs in providing accurate estimates for crucial maize yield traits (intended for silage) including plant height, fresh/dry/ear weight, number of maize ears per plant, and total ear weight per plant, using spatial maize data. The...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/14/2/280 |
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| author | Thomas M. Koutsos Georgios C. Menexes |
| author_facet | Thomas M. Koutsos Georgios C. Menexes |
| author_sort | Thomas M. Koutsos |
| collection | DOAJ |
| description | The current study investigates the performance of various sampling designs in providing accurate estimates for crucial maize yield traits (intended for silage) including plant height, fresh/dry/ear weight, number of maize ears per plant, and total ear weight per plant, using spatial maize data. The experiment took place in an experimental field area at Aristotle University (AUTH) farm during the 2016 growing season. Nine sampling designs were statistically analyzed and compared with spatial data from an Italian maize hybrid (AGN720) to identify the most suitable and effective sampling design for dependable maize yield estimates. The study’s results indicate that, among the different sampling techniques, Stratified Random Sampling is the most effective and reliable method for obtaining accurate maize yield estimates. This new approach not only provides precise estimates but also requires fewer measurements, making it suitable for experiments where not all plants have emerged. These findings suggest that Stratified Random Sampling can be employed effectively as an alternative to harvesting the entire plot for effectively estimating maize crop traits in experimental plots. |
| first_indexed | 2024-03-07T22:47:05Z |
| format | Article |
| id | doaj.art-ec773034cca34d0cb464ab7d742b3bc7 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-07T22:47:05Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-ec773034cca34d0cb464ab7d742b3bc72024-02-23T15:04:03ZengMDPI AGAgronomy2073-43952024-01-0114228010.3390/agronomy14020280Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental PlotsThomas M. Koutsos0Georgios C. Menexes1School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceSchool of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceThe current study investigates the performance of various sampling designs in providing accurate estimates for crucial maize yield traits (intended for silage) including plant height, fresh/dry/ear weight, number of maize ears per plant, and total ear weight per plant, using spatial maize data. The experiment took place in an experimental field area at Aristotle University (AUTH) farm during the 2016 growing season. Nine sampling designs were statistically analyzed and compared with spatial data from an Italian maize hybrid (AGN720) to identify the most suitable and effective sampling design for dependable maize yield estimates. The study’s results indicate that, among the different sampling techniques, Stratified Random Sampling is the most effective and reliable method for obtaining accurate maize yield estimates. This new approach not only provides precise estimates but also requires fewer measurements, making it suitable for experiments where not all plants have emerged. These findings suggest that Stratified Random Sampling can be employed effectively as an alternative to harvesting the entire plot for effectively estimating maize crop traits in experimental plots.https://www.mdpi.com/2073-4395/14/2/280crop estimatescrop productionagricultural systemsspatial sampling methods |
| spellingShingle | Thomas M. Koutsos Georgios C. Menexes Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots Agronomy crop estimates crop production agricultural systems spatial sampling methods |
| title | Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots |
| title_full | Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots |
| title_fullStr | Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots |
| title_full_unstemmed | Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots |
| title_short | Comparing Spatial Sampling Designs for Estimating Effectively Maize Crop Traits in Experimental Plots |
| title_sort | comparing spatial sampling designs for estimating effectively maize crop traits in experimental plots |
| topic | crop estimates crop production agricultural systems spatial sampling methods |
| url | https://www.mdpi.com/2073-4395/14/2/280 |
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