Code from: Canopy closure, yield, and quality under heterogeneous plant spacing in sunflower

<p dir="ltr"><b>Abstract</b></p><p dir="ltr">Deviation from uniform target plant population density in sunflower (Helianthus annuus L.) production may negatively affect canopy closure, yield, and grain quality. The objective of this study was to evaluate the effects of plant density heterogeneity on yield, quality, and canopy closure in confectionery and oilseed sunflowers. Field experiments consisted of fixed differences in the number of skips/doubles per plot while maintaining equal total number of plants, and stand gaps with proportional decreasing plant counts.These were conducted in Minnesota, Texas, and Colorado, USA. Experiments revealed that yield was occasionally influenced by heterogeneity, with more uniform stand density yielding higher; however, substantial changes in uniformity of plant density often resulted in no differences in yield. Confectionery sunflowers compensated for yield losses in thinner stands mainly by producing larger seeds (observed range of 0.1 to 46.2 % of seeds over a 9.53 mm sieve), while oilseed sunflowers increased seed production per head (as shown by invariable test weight across treatments within environments). Plants that were unharvestable for any cause (most often due to head rot disease or lodging) were more prevalent in less uniform stands, and faster canopy closure was achieved in uniformly spaced plants. Although sunflower is very resilient to stand uniformity issues, these findings underscore the importance of uniform sunflower plant spacing for effective weed suppression and crop performance, and highlights the need for further research into sunflower yield compensation mechanisms.</p><p dir="ltr"><b>Contents</b></p><ol><li>Neil figures.R: An R script that reads canopy cover data from the "can1920.xls" file for oil and confectionery sunflowers in 2019 and 2020. It creates ggplot visualizations of canopy cover by treatment, with facets for different days after planting (DAP) and color-coding for statistical significance.</li><li>canopy.sas: A SAS script that imports canopy data, performs data transformations (including arcsine transformation), and conducts mixed model analyses. It includes repeated measures analysis, least squares means comparisons with Tukey's adjustment, and residual diagnostics. The script analyzes canopy cover data by sunflower type, year, and time point.</li></ol><p dir="ltr">These scripts are used for statistical analysis and visualization of the canopy cover data collected in the sunflower plant density heterogeneity study.</p>