Mass Modelling of Eggs Based on Shape Index Using Regression Analysis

Manoj Mahawar; Ebubekir Altuntaş; Esra Nur Gül

doi:10.18016/ksutarimdoga.vi.992588

TR EN

Yumurtaların Şekil İndeksine Göre Regresyon Analiziyle Kütle Modellemesi

Öz

Bu çalışma, uzunluk (L), genişlik (W), geometrik ortalama çap (GMD) gibi geometrik özellikleri; birinci ve ikinci projeksiyon alanları (PA1, PA2), kriter alanı (CAE) ile basık küre hacmi (Vosp) ve ölçülen hacim (Vm) ve şekil indeksi (SI) ile yumurta kütlesi arasındaki ilişkiyi belirlemek amacıyla yapılmıştır. Şekil indeksine göre yumurtalar sırasıyla sivri (<72), normal (72-76) ve yuvarlak (>76) olarak karakterize edildi. Kütle tahmini için farklı sınıflandırmalar yani boyut 1. sınıflandırma, projeksiyon alanı 2. sınıflandırma ve hacim 3. sınıflandırma olarak gözönüne alındı. Analiz 33 lineer regresyon modeli kullanılarak uygulandı ve modeller maksimum belirtme katsayısı (R2) ve minimum regresyon standart hatası (RSE) dikkate alınarak önerildi. Modelleme analizine göre, kütle tahmini için seçilen sınıflandırmalara dayalı 10 model denklem önerilmiştir. Bu araştırmanın bulguları, yumurta üretimi ve işlenmesinde proseslerdeki ekipmanların tasarımı ve geliştirilmesinde araştırmacılara yardımcı olabilecektir.

Anahtar Kelimeler

Mass Modelling of Eggs Based on Shape Index Using Regression Analysis

Abstract

This study was conducted to determine the correlation between the mass of eggs based on its geometrical dimensions characteristics such as length (L), width (W), geometric mean diameter (GMD), the first and second projection areas (PA1, PA2), criteria area (CAE), oblate spheroid volume (Vosp), measured volume (Vm) and shape index (SI). Based upon the SI, eggs were characterized as sharp (<72), normal (72 -76) and round (>76), respectively. For mass prediction, different classifications viz. dimension as 1st classification, projection area as 2nd classification, and volume as 3rd classification were considered. 1st classification (dimension), 2nd classification (projection area), and 3rd classification (volume) were considered. The analysis was executed using 33 linear regression models and the models were recommended by considering maximum coefficient of determination (R2) and minimum regression standard error (RSE). Based on the modelling analysis, 10 model equations based on the selected classifications were recommended for mass estimation. The findings of this investigation will be helpful for the researchers involved in the design and development of process equipments in the production and processing of eggs.

Keywords

References

Altuntas E, & Mahawar MK 2021. Mass prediction of cherry laurel genotypes based on physical attributes using linear regression models. Journal of Agricultural Faculty of Gaziosmanpasa University, 38 (2), 87-94.
Altuntas E, & Sekeroglu A 2008. Effect of shape index on mechanical properties of chicken eggs. Journal of Food Enginering, 85, 606-612.
Altuntas E, & Sekeroglu A 2010. Mechanical behavior and physical properties of chicken egg as affected by different egg weights. Journal of Food Process Enginering, 33(1), 115-127.
Anderson KE, Tharrıngton JB, Curtıs PA, & Jones FT 2004. Shell characteristics of eggs from historic strains of single combwhite leghorn chickens and relationship of egg shape to shell strength. International Journal of Poultry Science, 3, 17–19.
Duman M, Şekeroğlu A, Yıldırım A, Eleroğlu H, & Camcı Ö 2016. Relation between egg shape index and egg quality characteristics. European Poultry Science, 80, 1-9.
Hasan ZU, Sultan JI, & Akram A 2000. Nutritional manipulation during induced moult in white leghorn layers I. Effects on carcass characteristics and visceral organs. International Journal of Agriculture and Biology, 2, 318-321.
Keranova N, Hristakieva P, & Oblakova M 2017. Mathematical approach for studying the influence of the shape index of turkey eggs and their mass on some incubation indicators. Agricultural Science, 9(22), 75-82.
Mahawar MK, Bibwe B, Jalgaonkar K, & Ghodki BM 2019. Mass modeling of kinnow mandarin based on some physical attributes. Journal of Food Process Enginering, 42, 10.1111/jfpe.13079. 10.1111/jfpe.13079.

Meena VS, Bibwe B, Bhushan B, Jalgaonkar K, & Mahawar MK 2021. Physicochemical characterization of selected pomegranate (Punica granatum L.) cultivars. Turkish Journal of Agricultural Engineering Research (TURKAGER), 2(2), 425-433. https://doi.org/10.46592/ turkager. 2021.v02i02.015
Rashidi M, & Gholami M 2011. Prediction of egg mass based on geometrical attributes. Agriculture and Biology Journal of North America, 2(4), 638-644.
Rashidi M, Malekiyan M, & Gholami M 2008. Egg volume determination by spheroid approximation and image processing. World Applied Science Journal, 3, 590-596.
Rashidi M, & Gholami M 2008. Classification of fruit shape in kiwifruit using the analysis of geometrical attributes. American-Eurasian Journal of Agricultre and Environmental Science, 3, 258-263.
Rath PK, Mishra PK, Mallick BK, & Behura NC 2015. Evaluation of different egg quality traits and interpretation of their mode of inheritance in White Leghorns. Veterinary World, 8(4), 449-452.
Réhault-Godbert S, Guyot N, & Nys Y 2019. The golden egg: nutritional value, bioactivities, and emerging benefits for human health. Nutrients, 11(3), 684.
Sarica M, & Erensayin C 2004. Poultry products. Bey-Ofset, Ankara-Turkey (in Turkish).
USDA National Nutrient Database for Standard Reference, Release 1; U.S. Department of Agriculture. Food Group: Dairy and Egg Products: Beltsville, MD, USA. 2018.
Yang HM, Yang Z, Wang W, Wang ZY, Sun HN, Ju XJ, & Qi XM 2014. Effects of different housing systems on visceral organs, serum biochemical proportions, immune performance and egg quality of laying hens. European Poultry Science, 78, 1-9.

Details

Primary Language

English

Subjects

Agricultural, Veterinary and Food Sciences

Journal Section

Research Article

Authors

Manoj Mahawar ^*
0000-0001-6802-252X
India

Ebubekir Altuntaş
0000-0003-3835-1538
Türkiye

Esra Nur Gül
0000-0002-9865-1228
Türkiye

Publication Date

February 28, 2023

Submission Date

September 7, 2021

Acceptance Date

January 14, 2022

Published in Issue

Year 2023 Volume: 26 Number: 1

DOI

https://doi.org/10.18016/ksutarimdoga.vi.992588

IZ

https://izlik.org/JA44AN26FU

Cite

RIS / Bibtex

APA

Mahawar, M., Altuntaş, E., & Gül, E. N. (2023). Mass Modelling of Eggs Based on Shape Index Using Regression Analysis. Kahramanmaraş Sütçü İmam Üniversitesi Tarım Ve Doğa Dergisi, 26(1), 132-139. https://doi.org/10.18016/ksutarimdoga.vi.992588

Cited By

Effect of Cage Environmental Enrichment on Egg Quality in Two Laying Hen Strains

Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi

https://doi.org/10.18016/ksutarimdoga.vi.1610209

The Influences of Maternal Hormones on The Quality Characteristics of Incubating Eggs

Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi

https://doi.org/10.18016/ksutarimdoga.vi.1883524