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Morphometric characterization and stepwise regression-based live body weight prediction in Kadaknath chicken: A biometric framework for indigenous breed management

This study establishes a reliable, low-cost method for estimating the live body weight of Kadaknath chickens using a stepwise regression equation based on closed wing length and chest circumference, providing a practical tool for managing this indigenous breed in settings lacking weighing facilities.

Original authors: Utkarsh Kumar Tripathi, Satish Kumar Pathak, Anuradha Kumar Kumari, Anshuman Kumar, Manish Kumar, Santosh Marandi

Published 2026-08-06

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Utkarsh Kumar Tripathi, Satish Kumar Pathak, Anuradha Kumar Kumari, Anshuman Kumar, Manish Kumar, Santosh Marandi

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine trying to guess how heavy a friend is just by looking at them. You might glance at their shoulders, measure their waist, or see how long their arms are. In the world of farming, this "guessing game" is a real problem. Farmers often need to know exactly how much their chickens weigh to check if they are healthy or growing well. But in many small villages, there are no fancy digital scales. The chickens are too fast to catch and put on a scale, or the scale is too expensive to buy. So, scientists have been trying to solve a puzzle: Can we figure out a chicken's weight just by measuring its body parts, like a detective solving a case with clues? This field of study is called morphometry, which is just a fancy word for measuring the shape and size of living things. If scientists can find the right "clues" (like wing length or chest size), they can build a simple math formula to predict the weight without ever needing a scale. This is a big deal for farmers who want to take better care of their flocks without needing expensive equipment.

Now, let's zoom in on a very special chicken called the Kadaknath. This isn't your average backyard bird; it's a famous Indian breed known for having black skin, black meat, and even black bones. It's like the "goth rockstar" of the chicken world, prized for its unique look and supposed health benefits. But here's the mystery: nobody really knew exactly how to measure these birds to predict their weight because they are so unique. A team of researchers from Banaras Hindu University decided to crack this code. They didn't just guess; they went out and measured 50 of these black chickens (both young and old, boys and girls) with extreme precision. They took 23 different measurements, from the length of their beaks to the circumference of their legs, and recorded their actual weight using a scale to see which body parts were the best clues.

The scientists treated the chickens like a giant jigsaw puzzle. They wanted to see which pieces of the body fit together to tell the story of the bird's total weight. First, they looked at the data and found that 19 out of the 23 measurements were linked to the weight. But the real superstar clue turned out to be the closed wing length. When the researchers measured the length of the wing while it was folded against the bird's body, it was the strongest predictor of how heavy the chicken was. It's as if the wing length is the "master key" that unlocks the secret of the bird's size. The second best clue was the chest circumference, or how wide the bird's chest is.

Using a clever mathematical trick called "stepwise regression" (which is like a smart filter that keeps only the best clues and throws away the rest), the team built a simple recipe to predict the weight. They found that if you know the closed wing length and the chest circumference, you can calculate the weight with surprising accuracy. The formula they came up with is: Body Weight = -1.133 + 0.067(Closed Wing Length) + 0.023(Chest Circumference).

To make sure this recipe actually worked, they tested it. They used the formula to guess the weight of the chickens and compared it to the real weight they had measured on the scale. The results were impressive: the guesses were very close to the reality. The math showed that this simple two-measurement method could explain about 76% of the differences in weight among the birds. Even when they tested the formula on "new" data (using a method called cross-validation where they pretended they hadn't seen the data before), it still held up well.

The researchers also used a tool called Principal Component Analysis (PCA), which is like a way to squish a big, messy pile of data into a few neat categories. They discovered that all the different body measurements could be boiled down to just two main ideas: the overall "body frame" (how big and sturdy the bird is) and the "appendage dimensions" (how long the wings and legs are). The "body frame" was the most important factor, and the closed wing length was the biggest part of that frame.

So, what's the takeaway? The paper suggests that farmers and conservationists don't need a heavy, expensive scale to manage Kadaknath chickens. Instead, they can use a simple tape measure to check the wing and chest. This low-cost tool helps ensure the birds are healthy and growing correctly, which is crucial for keeping this special breed safe and thriving. While the study was done on a specific group of 50 birds, the results strongly suggest that this method is a reliable, easy, and non-invasive way to keep track of these unique black chickens in the real world.

Technical Summary: Morphometric Characterization and Live Body Weight Prediction in Kadaknath Chicken

Problem Statement
Accurate live body weight (BW) estimation is critical for flock management, health monitoring, and breeding decisions in poultry. However, in smallholder indigenous poultry systems, particularly in remote rural settings, mechanical and electronic weighing facilities are often unavailable, unreliable, or economically inaccessible. While morphometric approaches (using external body measurements) have been proposed as alternatives, comprehensive biometric data and validated prediction models for the Kadaknath chicken—a distinctive fibro-melanotic indigenous breed of India with significant commercial and conservation value—remain limited. Existing literature lacks a detailed characterization of the breed's morphometric architecture and a field-applicable equation for weight prediction specific to this population.

Methodology
The study utilized a sample of 50 Kadaknath chickens (18 males, 32 females) representing young (4–6 weeks) and adult (24–28 weeks) age groups, selected via simple random sampling from a semi-intensively managed flock at Banaras Hindu University, India.

Data Collection: Researchers recorded body weight and 23 external morphometric traits, including linear dimensions (e.g., body length, wing length) and circumferential measurements (e.g., chest circumference, tarsus circumference). Measurements were taken using calibrated digital scales, flexible tapes, and rigid rulers by a single trained investigator to minimize observer bias.
Statistical Analysis:
- Descriptive Statistics: Means, standard errors, and ranges were calculated for all variables.
- Correlation Analysis: Pearson's product-moment correlation coefficients were computed to identify relationships between body weight and morphometric traits.
- Principal Component Analysis (PCA): Performed on 13 structural body-size traits (excluding secondary sexual adornments and craniofacial measurements) to reduce dimensionality and identify major axes of morphological variation.
- Stepwise Multiple Linear Regression (MLR): Conducted with body weight as the dependent variable and all 23 morphometric traits as candidate predictors to derive a parsimonious prediction equation.
- Model Validation: The model's robustness was assessed using leave-one-out cross-validation (LOOCV), evaluating metrics such as cross-validated $R^2$ , root mean square error (RMSE), and mean absolute error (MAE).

Key Results

Descriptive Profile: The mean body weight was $1.00 \pm 0.04$ kg (range: 0.44–1.75 kg). Wingspan was the largest linear trait ( $65.57 \pm 0.83$ cm), while craniofacial measurements showed lower variation compared to skeletal and adornment traits.
Correlations: Nineteen of the 23 morphometric traits were significantly positively associated with body weight ( $P < 0.05$ ). The strongest correlations were observed with closed wing length ( $r = 0.83$ ), back length ( $r = 0.80$ ), and tarsus circumference ( $r = 0.77$ ). Traits such as skull width, ocular length, and neck length showed no significant association with body weight.
Principal Component Analysis: PCA reduced the dataset into two orthogonal components explaining 64.97% of the total variance:
- PC1 (40.85% variance): Represented a general "body-frame" dimension, heavily loaded with closed wing length, tarsus circumference, back length, and body length.
- PC2 (24.12% variance): Represented "appendage dimensions," characterized by central toe length, wing length, tarsus length, and wingspan.
Prediction Model: Stepwise regression identified closed wing length (CWL) and chest circumference (CC) as the most informative independent predictors. The final predictive equation is:
$BW = -1.133 + 0.067(CWL) + 0.023(CC)$
- Model Performance: The model achieved an Adjusted $R^2$ of 0.757 ( $P < 0.001$ ).
- Validation: The correlation between observed and predicted weights was strong ( $r = 0.876$ ). Cross-validation yielded an $R^2_{CV}$ of 0.660, an RMSE of 0.180 kg, and an MAE of 0.134 kg, indicating satisfactory stability and predictive accuracy. Multicollinearity was negligible (VIF = 1.244).

Key Contributions

First Morphometric Profile: This study provides the first comprehensive morphometric characterization profile of the Kadaknath indigenous chicken, documenting 23 external traits and their statistical relationships.
Identification of Key Predictors: It establishes that closed wing length is the single strongest correlate of body weight in this breed, surpassing chest circumference in correlation strength, though both are required for the optimal model.
Practical Prediction Tool: The study develops a scale-free, low-cost equation enabling the estimation of live body weight using only two easily measurable traits (closed wing length and chest circumference).
Structural Insight: PCA analysis reveals that the morphological variation in Kadaknath chickens is primarily driven by body-frame size and secondarily by appendage dimensions, offering a biometric framework for understanding the breed's phenotypic architecture.

Significance and Claims
The authors claim that the proposed regression equation offers a simple, low-cost, and non-invasive tool for estimating live body weight in Kadaknath chickens. This is particularly significant for flock management, breeding programs, and conservation efforts in settings where access to weighing equipment is limited. The study emphasizes that the model's satisfactory performance under cross-validation supports its potential application in field conditions.

The paper modestly notes that the model was derived from a population comprising both sexes and multiple age classes, which enhances field applicability but suggests that sex- or age-specific allometric relationships may require further evaluation in larger, independent populations. The authors conclude that these findings establish a valuable biometric baseline for the breed and provide a practical tool for indigenous breed management, while recommending further validation in geographically diverse populations to confirm broader applicability.

Technical Summary: Morphometric Characterization and Live Body Weight Prediction in Kadaknath Chicken

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