DOI: 10.13012/b2idb-7536377_v1
title: Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

description: This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. 
The data support the analyses presented in the article:
“Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.”
We collected 105 ground-truth biomass samples from four mature commercial fields (&gt;4 years old) covering 92.81 ha. 
Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. 
Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS.
Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). 
Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. 
Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated.
This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here.

The dataset consists of three comma-separated value (CSV) files:

1. Combine_Groundtruth_Yield_VI_22_23.csv
This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons.
Rows: 105 observations
Columns:
Year — Year of observation (2022 or 2023)
Field — Field location identifier
Sample_number — Unique sample identifier
GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July
GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August
NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August
Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare)

2. trainData_GNDVI.csv
This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield.
Rows: 76 observations
Columns:
Unnamed: 0 — Row index retained from the original data processing workflow
GNDVI_End_Jul — GNDVI at end of July
Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹)

3. testData_GNDVI.csv
This file contains the test dataset used to evaluate model performance.
Rows: 29 observations
Columns:
Unnamed: 0 — Row index retained from the original data processing workflow
GNDVI_End_Jul — GNDVI at end of July
Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹)
Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)