Stories about crops and statistics (plus coding)
In this session, I will introduce the method of calculating the Best Linear Unbiased Estimator (BLUE). Instead of simply listing formulas as many websites do to explain BLUE, this post aims to help readers understand the process of calculating BLUE with an actual dataset using R. I have the following data. The dataset comprises three … Read more
Time is not a flowing river, but a massive, frozen block of ice where the past, present, and future coexist simultaneously within a four-dimensional spacetime continuum. As Albert Einstein famously noted: “The distinction between past, present, and future is only a stubbornly persistent illusion.” 1. The Geometric Completion of Spacetime As three-dimensional beings, we only … Read more
Today, I developed my own Twitter-style news feed, which you can see now. I added a DNS record to my website, agronomy4future.com, and the current address is today.agronomy4future.com. Do I know how to code? No. Did I major in programming? No. But I developed my own platform by collaborating with Claude. I simply shared my … Read more
In my previous post, I demonstrated how to add distinct text to panels created with facet_wrap() or facet_grid(), and I proposed the following simple method. I first created a data frame containing the labels, which I then used to map the text to the corresponding panels. Let’s practice using this method This data is from … Read more
Recently, I set up my database workflow using a Virtual Private Server (VPS) and developed R code to easily access and analyze this database. I’ll introduce them one by one. 1) Data in local PC to MySQL Server I want to upload my data in my PC to a MySQL server hosted on a Virtual … Read more
In my previous post, I explained What logistic regression is and also explained odds, odds ratio and model equation. Today, I’ll introduce Firth’s Logistic Regression. Common logistic regression is mostly used when the sample size is sufficiently large, and the outcome variable (0 and 1) is well-balanced. Also, it is used when there is no … Read more
In a modern workflow, we constantly bounce between various web-based note-taking tools. For a developer or researcher, the act of opening a browser, logging in, and navigating to a page is a significant context switch. When you are deep in a coding session or analyzing data in the terminal, grabbing the mouse to record a … Read more
On Linux, OneDrive cannot be downloaded and synchronized as seamlessly as it is in a Windows environment. Today, I will provide a step-by-step guide on how to install and sync OneDrive on your Linux PC. 1) Set up a new remote connection. First, let’s open the terminal using the shortcut Ctrl + Alt + T … Read more
When analyzing grain size, we’ve used high-throughput image scanning machines. However, if we can detect grains using R code, estimating grain size becomes possible. In my previous R function, colorcapture(), we were able to detect fruit size and estimate its surface area in 2D. Recently, I developed a new R function called phenokio() specifically designed … Read more
1) Nitrogen Immobilization Nitrogen immobilization is the process by which soil microorganisms take up inorganic nitrogen (mainly NH₄⁺ and NO₃⁻) from the soil solution and convert it into organic forms inside their own cells. In other words, the N is temporarily “locked up” in microbial cells and is not available for plants. Microbes need nitrogen … Read more
Meta-analysis is a quantitative method that synthesizes results from multiple independent studies to identify overall patterns, effect sizes, and sources of variability for specific treatments or research questions. It is particularly powerful for summarizing existing evidence and placing new findings within the context of current scientific trends through transparent and reproducible statistical integration of prior … Read more
When data is arranged, it can be structured either vertically (row-based) or horizontally (column-based). The choice depends on your preference for organizing data. However, when running statistics, data should be arranged row-based, as variables need to be in the same column. On the other hand, when calculating per variable, it is much easier to organize … Read more
When conducting a meta-analysis, results from multiple studies must be synthesized despite differences in measurement scales, experimental designs, and reported units. To enable meaningful comparisons across studies, effect sizes are commonly used. One of the most widely applied effect size metrics in ecological and agricultural research is the Log Response Ratio (LRR). The Log Response … Read more
When performing a t-test, a confidence interval can be obtained. Below, I describe how to calculate the confidence interval manually, step by step. 1) Difference in means 2) Pooled variance 3) Standard error 4) Degrees of freedom 5) Confidence interval and let’s calculate the confidence interval We aim to develop open-source code for agronomy ([email protected]) … Read more
Recently, I’ve been focusing on Bayesian statistics. To organize the concepts for myself as well, I’m going to explain Bayes’ theorem as simply as possible. Let’s import a dataset from Kaggle. https://www.kaggle.com/datasets/cameronseamons/electronic-sales-sep2023-sep2024 This dataset contains information used to analyze customer purchasing behavior at an electronics store. You can download it from Kaggle after creating an … Read more
I don’t manage my data with Excel, but primarily with SQL. I also don’t store any data on my local PC—not even SQL files. Instead, I keep everything on the server and access it whenever I need it. Previously, I shared how to import data to a cloud MySQL server and how to import data … Read more
In my previous post, I explained how to calculate Cook’s Distance step by step, and noted that in R you can simply use the function cooks.distance(). However, this simple function only provides the Cook’s Distance values. In my previous post, I explained the formula for Cook’s Distance step by step, including how to compute residuals, … Read more
When analyzing yield, we usually use bar or box plots based on the mean. However, sometimes we need to visualize the spatial variation of yield. In those cases, GIS maps are commonly used, often created with powerful software such as ArcGIS, which I have used and found to be excellent. The drawback is that ArcGIS … Read more
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Previous post□ How to analyze linear plateau model in R Studio? In my previous post, I explained how to analyze the linear plateau model. I simulated yield data for five different crop varieties with varying sulphur applications and suggested that the optimum sulphur application would be 23.3 kg/ha based on the linear plateau model. In … Read more
The Gamma distribution is a flexible family of continuous probability distributions defined only for non-negative values (x>0). It’s commonly used to model quantities that represent time, size, or waiting periods—anything that can’t go below zero and often shows right-skewed behavior (a long tail toward larger values). In essence, the Gamma distribution describes how likely different … Read more
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A Virtual Private Server (VPS) is a virtualized computer within a larger physical server. It acts like an independent server, offering dedicated resources and control at a lower cost than a full physical machine. VPS hosting uses this setup to give users private, customizable environments for web hosting or applications. Some reputable VPS providers include … Read more
In my previous post, I introduced how to import data into a Cloud MySQL database using Python from the Command Prompt. By typing the code below in your Command Prompt, you can automatically import data into your MySQL server. This is the next step. After importing data into the MySQL server, what if I want … Read more
This colorcapture() R function provides easy image analysis to estimate fruit surface area. 1. Install the pacakge Before installing colorcapture(), please download Rtools (https://cran.r-project.org/bin/windows/Rtools), and install the following package. □ colorcapture() 2. Basic code If you want to change other criteria, type ?colorcapture to see detailed information about the colorcapture() function. The default code is set to capture the … Read more
In my previous post, I introduced how to import data into SQL. That process was done manually to import data into a local SQL server. I use MySQL. A local SQL server means you can only access the data from your own computer. If you use another computer elsewhere, you won’t be able to access … Read more
When measuring leaf area or fruit surface area, these have usually been measured manually, which is time-consuming and often inaccurate, especially when the shape is not perpendicular. For more reliable measurement, image analysis provides a good alternative. To facilitate this process, I developed an R function, greencapture() that captures the green area of leaves or … Read more
When analyzing data, we sometimes need to analyze cumulative data. When calculating cumulative data, grouping is important, and it takes time to perform the grouping and calculations. To simplify this process, I developed an R package called datacume(). Let’s upload the dataset. This dataset contains biomass measurements across different treatments over time, recorded for various … Read more