Agronomy4future

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 to estimate the grain area of cereals. 1. Install the function Before installing, please download Rtools (https://cran.r-project.org/bin/windows/Rtools) 2. Default Values Summary Table If a parameter…

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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, leverage, and internal studentized residuals. To make it easier to calculate these values, I recently developed an R package called datacooks(). □ datacooks() Before installing…

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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 is not free. If you want to create a simple yield map using R, it is possible, although the map quality may be slightly lower….

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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 yellow color. If you run the code, it will detect the yellow surface area. The frame size was 24 cm × 24 cm. and the…

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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 fruits in the lab using a fixed frame. 1. Install the greencapture() package 2. Set up folders for input and output images I will save…

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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 plants and their branches. I want to calculate the cumulative biomass over time. To do this accurately, I’ll first calculate the average biomass of the…

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https://github.com/agronomy4future/r_code/blob/main/geom_mark_ellipse.ipynb We aim to develop open-source code for agronomy ([email protected]) © 2022 – 2025 https://agronomy4future.com – All Rights Reserved. Last Updated: 19/07/2025

This post is part of a series introducing R packages that present methods for calculating phenotypic plasticity. □ [R package] Finlay-Wilkinson Regression model (feat. fwrmodel)□ [R package] Calculate the responsiveness of each treatment relative to a control (Feat. deltactrl)□ [R package] Quantifying Reaction Norm Plasticity from Slopes to Individual Responses (Feat. nrmodel) In my previous post, I explained how to quantify phenotypic plasticity in crops and described three different approaches: Responsiveness, Reaction Norm, and the Finlay-Wilkinson Regression Model. □ Quantifying…

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■ [R package] Embedding Key Descriptive Statistics within Original Data (Feat. descriptivestat) ■ [R package] Calculate the responsiveness of each treatment relative to a control (Feat. deltactrl) In my previous posts, I introduced two R packages. The first package, descriptivestat(), displays raw data along with mean values and additional descriptive statistics. The second package, deltactrl(), calculates the responsiveness of dependent variables in response to the control. Today, in this article, I will demonstrate how combining these two R packages allows…

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■ Quantifying Phenotypic Plasticity of Crops In my previous posts, I explained how to quantify phenotypic plasticity of crops in response to environmental factors, and introduced the concept of responsiveness, calculated using the formula: (Treatment – Control) / Control, as shown in the table below. Genotype Control Treatment Responsiveness A 100 90 -10.0% = (90-100)/100 B 120 70 -41.7% C 115 90 -21.7% D 95 85 -10.5% E 110 105 -4.5% While calculating responsiveness for a single variable is relatively…

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