Agronomy4future

CURRICULUM VITAE
BASIC STAT
STATISTICAL MODEL
- ANOVA
- REGRESSION
- SPLIT-PLOT
- GLM
- Mixed Model
- REML
- NONLINEAR
CODING
- R coding
- SAS
- PYTHON
- Machine Learning
DATABASE
JK column

Agronomy4future

Stories about cereals and statistics (plus coding). We aim to develop open-source code for agronomy.

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Agronomy4future Logo

April 30, 2023 JK

© 2022 - 2025 https://agronomy4future.com - All Rights Reserved.
Last Updated : 06/18/2025 09:45:20

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JK Kim 
(kimjk@agronomy4future.com) 
"We aim to develop open-source code for agronomy"

• GitHub: github.com/agronomy4future
• YouTube: @agronomy4future

annotate() aov () arrange() c(rep() case_when() colnames() data.frame() ddply () dplyr facet_grid() facet_wrap() filter() fwrmodel() gdds() geom_abline () geom_bar () geom_vline() github HSD.test() if() ifelse() intercept0() kimindex() mutate() nls() nlsLM() normtools() pivot_longer() poly() predict() probdistz() rbind() reshape2::melt() residuals() sapply() scale_fill_manual () spread() str_replace_all () subset() table() tdist() theme_grey() windows () write_xlsx() xtabs()

Previously, I developed two R packages, descriptivestat() and deltactrl(). By combining these packages, it becomes easy to create a responsiveness graph.

[Data article] Visualizing Responsiveness: Integrating Raw Data for a Holistic Dataset View (https://t.co/Yz3I6bbMsF) pic.twitter.com/eBesZBJUY9
— J.K Kim (@agronomy4future) June 9, 2025

□ New R package: #deltactrl(); delta control

This package is designed to easily calculate the responsiveness of each treatment relative to a control.

□ Github: https://t.co/BYCSf7KU9v
□ Code explained: https://t.co/GlXvnhh4mV pic.twitter.com/iIhWHLDAAH
— J.K Kim (@agronomy4future) June 9, 2025

We’re working on measuring crop canopy with image analysis and comparing it to actual leaf area. If the model fits well, this could be a fast way to estimate canopy size. Currently setting up the frame and code. pic.twitter.com/GE33yujdKi
— J.K Kim (@agronomy4future) May 21, 2025

New R package: #descriptivestat()
This package automatically embeds descriptive statistics into the dataset, allowing for clear visualization alongside the raw data.

□ Github: https://t.co/tYJPmzvCzJ
□ Code explained: https://t.co/sPOqQwIDgu pic.twitter.com/EL330dIH21
— J.K Kim (@agronomy4future) May 18, 2025

When the intercept is forced to 0 in a simple linear regression, most software programs report an incorrect R². Therefore, I developed a new R package, #intercept0(), which provides the correct R².

□ Github: https://t.co/In3GS6szFI
□ Code explained: https://t.co/EAL3Rbeo6U pic.twitter.com/LJ2eoUlLeT
— J.K Kim (@agronomy4future) May 11, 2025

https://twitter.com/agronomy4future/status/1903192051631481171

https://twitter.com/agronomy4future/status/1898040162229403743

I developed an R package, #interpolate() to facilitate data interpolation, particularly by grouping. With this R package, you can easily predict intermediate data points based on actual data points.
□ Github: https://t.co/ClJuZPAMfH
□ Code explained: https://t.co/RRoaphRSi8 pic.twitter.com/u6SVdY1tBO
— J.K Kim (@agronomy4future) March 3, 2025

I became curious about mapping U.S. agriculture universities, so I used the #Folium package in #Python to create an easy-to-use #GIS map. Here’s the code to visualize their locations across the U.S. (https://t.co/mupLakgyms) pic.twitter.com/LB5u4lb2gy
— J.K Kim (@agronomy4future) February 12, 2025

I will continue my #Agrivoltaics study at Cornell University. Over the past 1.5 years, I have conducted research on the source-sink strength of crops in response to shading at the University of Illinois Urbana-Champaign, and I look forward to gaining further insights at Cornell. pic.twitter.com/o1kxJLR32e
— J.K Kim (@agronomy4future) January 13, 2025

At the 2024 ASA meeting in San Antonio, I presented my current #agrivoltaics study and proposed distinct farming strategies for sorghum and soybean at pre- and post-anthesis, respectively, focusing on yield components (grain number and weight) in terms of source-sink strength. pic.twitter.com/QdV2kEP9zQ
— J.K Kim (@agronomy4future) November 19, 2024

The Log-Likelihood is a crucial component in statistical modeling, as it helps evaluate how well a model fits the data. In this article, I will explain how to calculate the Log-Likelihood by hand. There is an exercise you can try with an actual dataset (https://t.co/Q1b7693UUB) pic.twitter.com/YrV2SxnzzE
— J.K Kim (@agronomy4future) November 8, 2024

[STAT Article] Step-by-Step Guide to Calculating and Analyzing Principal Component Analysis (PCA) by Hand (https://t.co/IB1kXGYGiJ)

In this article, I introduce how to calculate and analyze Principal Component Analysis (PCA) by hand step by step. pic.twitter.com/HmjHOvOtaB
— J.K Kim (@agronomy4future) November 1, 2024

□ R package: normtools() for Normalization Methods for Data Scaling.

Recently, I developed an R package to normalize data using various methods (Z-test, Robust Scaling, Min-Max Scaling, and Log Transformation) for data scaling.

□ Code explained: https://t.co/EE8fatSqks pic.twitter.com/0u99SrvPLn
— J.K Kim (@agronomy4future) October 8, 2024

I share a simple R code to create a GIS map like the one below.

□ Code explained: https://t.co/IdIlabCRns pic.twitter.com/5WOXubwxrm
— J.K Kim (@agronomy4future) September 22, 2024

I've developed an R package, #gdds(), to easily calculate Growing Degree Days (#GDDs) with a base temperature (BT).

□ Cumulative temp when BT is 0
GDDs = gdds(df, "date", "temp", "group", date= c("0000-00-00", "0000-00-00"), BT= 0)

□ Github: https://t.co/p4oUI3XEnM pic.twitter.com/psKtHWZNiR
— J.K Kim (@agronomy4future) September 15, 2024

#kimindex() is a simple R package I developed to predict grain weight from area based on ŷ=x^1.32

# basis code
□ predicted_gw=kimindex(df, "grain_area", remove_na= TRUE)
□ predicted_area=kimindex1(df, "grain_weight", remove_na= TRUE)

□ Code explained: https://t.co/ISaQIGuQTr pic.twitter.com/ERguU3fee7
— J.K Kim (@agronomy4future) September 10, 2024

probdistz() R package
When creating a probability curve, the process can be a bit tricky. Recently, I developed an R package called #probdistz() to simplify this.

# basic code
probdistz(data, env_cols, yield_cols, smooth= TRUE)
#

□ Github: https://t.co/rKw7FkyHPq pic.twitter.com/bv2VjZ6vdx
— J.K Kim (@agronomy4future) September 2, 2024

Using a simple Python code, a GIS map can be created if we have coordinates (latitude and longitude) along with yield data. I will share the Python code. "Python GIS: Interpolating and Plotting Corn Grain Yield Data." https://t.co/RMS9MoWEZl pic.twitter.com/RUCP7O1SCX
— J.K Kim (@agronomy4future) August 18, 2024

https://twitter.com/agronomy4future/status/1816248306777088298

https://twitter.com/agronomy4future/status/1788229741624840668

https://twitter.com/agronomy4future/status/1784735707057303677

https://twitter.com/agronomy4future/status/1780672363446542654

https://twitter.com/agronomy4future/status/1777825479187145064

https://twitter.com/agronomy4future/status/1718349430653440207

https://twitter.com/agronomy4future/status/1701697459141984518

https://twitter.com/agronomy4future/status/1689110911028473856

[Data article] Visualizing Responsiveness: Integrating Raw Data for a Holistic Dataset View
[R package] Calculate the responsiveness of each treatment relative to a control (Feat. deltactrl)
Amblyseius swirskii – Predatory Mite
The New York Night scene from the Airplane
pepper flowering initiated
[R package] Embedding Key Descriptive Statistics within Original Data (Feat. descriptivestat)
How to upload data from Google Drive to Google Colab in an R environment?
[R package] R-Squared Calculation in Simple Linear Regression with Zero Intercept (Feat. Intercept0)
A Step-by-Step Guide to Creating an R Package and Uploading to GitHub
How to download data from R environment in Google Colab?
Urea (46-0-0) application at the agrivoltaics field in 2024 and 2025
How to Upload Data from GitHub Using R and Python?
[Data article] Simulating Crop Growth Over Time Using a Sigmoid Growth Model
[STAT Article] RMSE Calculation with Excel and R: A Comprehensive Guide
What is split-plot design in agronomy research?
[R Package] Convert Data into Code Instantly – Save as a Script with One Line
[R package] An easy way to use interpolation code to predict in-between data points
[Data article] Predicting Intermediate Data Points with Linear Interpolation in Excel and R
How to Combine Files and Create a New Data Table in MySQL
How to Rename Variables within Columns in R (feat. case_when() code)?
How to convert to a .json file using Python?
How to Use Temporary Tables for Quick Calculations in MySQL?
Visualizing Geospatial Data with Folium in Python
How to automatically insert linear regression equation in graph in RSTUDIO?
[Article] Tiny Plants Reveal Big Potential for Boosting Crop Efficiency – Boyce Thompson Institute – Boyce Thompson Institute
[슬기로운 코넬 생활 101] 한국에서 이타카 (Ithaca) 가는 방법
[STAT Article] Steps to Calculate Log-Likelihood Prior to AIC and BIC: [Part 2] ANOVA model
2024 ASA, CSSA, SSSA International Annual Meeting in San Antonio, TX
[STAT Article] Steps to Calculate Log-Likelihood Prior to AIC and BIC: [Part 1] regression model
[STAT Article] Step-by-Step Guide to Calculating and Analyzing Principal Component Analysis (PCA) by Hand

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