Scoring is a common method to evaluate eggshell translucency, and it mainly depends on the area and the density of translucent spots in eggshells. However, the lack of common scoring criteria and the difficulty of quantitatively measuring spots in eggshells impede effective comparisons between research papers and greatly hinder the progress of research on translucent eggshell. To make measurement of translucent eggshells more objective, we optimized the scoring method and compared it with 2 new methods: grayscale recognition and the colorimeter method. Briefly, a total of 354 eggs from 600, 395-day-old dwarf brown laying hens were collected and classified into 4 score groups according to their degree of translucency. This subjective process was repeated 5 times. Then, we captured the profile side of each egg using a camera and measured spot characteristics using grayscale recognition, which involved measuring the quantity of spots (QS), diameter of each spot (DS), average area of each spot (AAES), sum of spot areas (SUSA), sum of shell area (SUSHA), and ratio of SUSA to SUSHA (RSS) on the eggshell. Furthermore, the L, A, and B values of each egg at the sharp, middle, and blunt ends were separately measured using a colorimeter. As a result, average values of 31.31, 29.78, 29.81, and 9.08% of all eggs were divided into score levels 1, 2, 3, and 4 (from opaque to translucent), which correspond with RSS values of 1.34, 3.23, 6.21, and 11.89%, respectively. By grayscale recognition, QS, DS, AAES, SUSA, SUSHA, and RSS all increased along with increased translucency scores (P < 0.05). Using scoring, an egg with a specific RSS value was more easily assigned to a specific score level (50%) or adjacent score levels (50%). The L, A, and B values of eggshells in score level 1 were significantly different from those of eggshells in levels 3 or 4; however, there were no significant differences between any adjacent score levels. In summary, the present study explored objective reference metrics to measure eggshell translucency.

中文翻译：

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半透明卵表型测量方法研究。

评分是评价蛋壳半透明度的常用方法，主要取决于蛋壳中半透明点的面积和密度。然而，缺乏共同的评分标准以及蛋壳中斑点的定量测量困难，阻碍了研究论文之间的有效比较，极大地阻碍了半透明蛋壳研究的进展。为了使半透明蛋壳的测量更加客观，我们优化了评分方法，并将其与2种新方法进行了比较：灰度识别和色度计法。简而言之，共收集了来自 600 只 395 日龄矮褐蛋鸡的 354 个鸡蛋，并根据其半透明程度分为 4 个评分组。这个主观过程重复了5次。然后，我们使用相机捕捉每个鸡蛋的侧面，并使用灰度识别测量斑点特征，其中包括测量斑点的数量 (QS)、每个斑点的直径 (DS)、每个斑点的平均面积 (AAES)、斑点的总和面积 (SUSA)、蛋壳面积总和 (SUSHA) 以及蛋壳上的 SUSA 与 SUSHA 的比率 (RSS)。此外，使用色度计分别测量每个鸡蛋在尖头、中间和钝端的 L、A 和 B 值。结果，所有鸡蛋的 31.31、29.78、29.81 和 9.08% 的平均值分为 1、2、3 和 4 级（从不透明到半透明），对应的 RSS 值为 1.34、3.23、6.21 ，分别为 11.89%。通过灰度识别，QS、DS、AAES、SUSA、SUSHA 和 RSS 都随着半透明分数的增加而增加（P < 0.05）。使用评分，具有特定 RSS 值的鸡蛋更容易分配到特定分数级别 (50%) 或相邻分数级别 (50%)。1 级蛋壳的 L、A、B 值与 3 级或 4 级的蛋壳有显着差异；但是，任何相邻的分数水平之间没有显着差异。总之，本研究探索了衡量蛋壳半透明度的客观参考指标。