## 1 Introduction  
Globally, rice is a major staple food crop and is a significant energy source for about half of the world's population [1]. Rice is a widely consumed cereal, accounting for approximately 21% of human caloric requirements globally [2]. It is mostly produced and consumed in South and Southeast Asia and accounts for up to \(\sim\)76% of caloric intake in this region. People mostly consume rice in the milled (polished) form, which only consists of endosperm. The processing of hulled/brown rice removes the embryo and bran. The nutritional value of milled rice is largely dependent on the endosperm, which comprises starch (70-80%), proteins (7-10%), and lipids (!1.0%) [3]. The rice endosperm is relatively deficient in many micronutrients or phytontrients. The total seed protein in rice comprises 60-80% gluten and 20-30% prolamin [4, 5]. Multiple genetic factors with a complex genetic basis control GPC in rice. Environment also has a significant impact on GPC. GPC exhibits wide variation among the different varieties. Among the different _japonica_ rice varieties collected from different regions, the GPC ranged from 6.45 to 11.1% ([PERSON] et al. 2023) [6]. Analysis of approximately 4000 rice varieties collected from 57 countries for GPC exhibited a range from 5.3% to 13.6% ([PERSON] et al., 2023). However, the GPC in present-day cultivated varieties ranges from 6.0% to 8.0% only. GPC influences the cooking and eating quality of rice, and affects the physicochemical properties [2]. High GPC causes cooked rice to be hard and loose, resulting in poor eating quality [7]. Consumers usually prefer soft and fluffy cooked rice. Since GPC is a complex trait influenced by multiple factors, it may not be possible to meet the demands of the growing population using only conventional methods of crop improvement. Breeding approaches like marker-assisted breeding (MAB) are very promising. The application of MAB in crop improvement requires information about the genomic regions governing the trait. The mapping of complex quantitative traits like GPC is relatively difficult compared to simple Mendelian traits. Mapping methods such as QTL mapping have been very effective in identifying the genomic regions governing a particular trait. The effectiveness of QTL mapping depends on precise phenotyping and efficient marker-based genotyping. Rice breeders extensively use thousands of 'Simple Sequence Repeats (SSRs)' to perform genotyping across the entire genome [8]. Vast genetic resources are available in rice, including more than 20,000 SSR primers [9]. SSRs are very useful for the construction of linkage maps, mapping of genes, and marker-assisted selection [9]. To date, more than 40 QTLs with small effects on GPC have been identified [10, 11, 12, 13], but very few QTLs have been cloned and functionally validated [14]. _OsASNI_, _OsNAC74_, _OsAUX5_, and _SEMIDWARF1_ (_SD1_) are some of the important candidate genes that play a role in rice GPC [15, 16, 17, 18]. Despite the success, two major drawbacks of the QTLs identified so far are as follows: first, the QTLs identified are mostly in brown rice; and second, the parents used in breeding lacked the required variation/difference in GPC. Hence, the identification of stable-GPC QTLs specifically in milled rice, without any undesirable effects on agronomic traits and grain quality, is crucial. This is very essential for the genetic enhancement of the GPC in milled rice and the eating quality of cooked rice. The objective of the present study is to identify QTLs specifically for GPC in milled rice, and for grain quality traits and yield, in an F\({}_{2}\) population developed from BPT 5204 X JAK-686. The GPC of BPT 5204 and JAK-686 is \(\sim\)8.0% and \(\sim\)12.0%, respectively. BPT 5204 is a very popular variety, with a medium-slender grain type, low GPC, and excellent cooking quality, while JAK-686 is a high-GPC germplasm line, which shows early maturity (110 days).