Improvement of Cacao Pod Characteristics and its Molecular Characterization in 4 F1 Cacao Populations

Improvement of Cacao Pod Characteristics and its Molecular Characterization in 4 F1 Cacao Populations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Improvement of Cacao Pod Characteristics and its Molecular Characterization in 4 F1 Cacao Populations Nur Kholilatul Izzah, Cici Tresniawati, Rubiyo Rubiyo, Dibyo Pranowo, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4766155/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cacao stands as a vital export commodity, necessitating consistent high-quality cocoa beans to meet market demands. Controlled hybridizations for genetic enhancement offer a pathway to improve bean quality and to increase genetic variation. We elucidated the phenotypic variation of pod characteristics in F 1 progenies generated from four distinct cross combinations and its molecular characterization. Phenotypic analysis revealed notable outcomes within progenies of TSH858xDR1 cross, demonstrating high average pod weight and a beans-per-100g count aligning with grades AA/A. Among these progenies, 5 − 1 (2), showcased several advantageous traits including the highest weight of a single dried bean and the lowest pod index reflecting large bean sizes. Molecular characterization revealed that all the F 1 progenies were different from each other, confirming the differences in phenotypic traits were strongly influenced by genetic variation. These findings underscore the efficacy of intentional crosses which are crucial for genetic improvement. cocoa bean quality controlled hybridizations genetic variation molecular characterization SSR markers Figures Figure 1 INTRODUCTION Cacao ( Theobroma cacao L.) is the only source of cocoa beans as the bases of global industries including food, confectionary, beverages, cosmetics, and pharmaceuticals. The quality of these materials must meet the needs of the industry, thus significantly influencing global market prices. However, maintaining consistent quality of cocoa beans poses many challenges due to the lack of cocoa beans that meet quality standards (Rodríguez-Carrasco et al. 2018 ). Diverse factors have a major impact on cocoa bean quality, encompassing genotypic variations, environmental conditions, bean maturity levels, and post-harvest procedures (Calvo et al. 2021 ). Selective crosses between superior genotypes represent a key strategy for attaining high-quality cocoa beans, concurrently enhancing genetic diversity within populations(Izzah et al. 2022 ). Consequently, crosses between genetically distant parents have emerged as a principal method for plant breeders to augment diversity as well as to obtain heterosis effect (Motamayor et al. 2008 ). The role of genetic variation within species is one of the important aspects in breeding studies, serving as a main factor for establishing novel high-yielding varieties (Shilpashree et al. 2021 ). The ensuing F 1 progenies then underwent morphological characterization to pinpoint crucial traits associated with the yield and bean quality. Of which, assessing morphological traits plays a pivotal role in evaluating plant breeding materials, essential in both conventional and modern breeding methods(Bidot Martínez et al. 2017 ), and the collected data serve as a valuable asset for selecting superior genotypes with desired traits (Bekele and Phillips-Mora 2019 ). Although, the two identical parents of cacao cultivars were crossed, in fact, morphological variations in their F 1 progenies were commonly observed, underscoring the need to assess their genetic relationships. Thus, determination of genetic variability in F 1 cacao progenies both through morphological and molecular characterizations had been a prevalent approach (Bekele and Phillips-Mora 2019 ). Such evaluation is essential not only to maintain genetic variability within the progenies but also for making proper decisions about their utilization in breeding programs (Karakaya et al. 2023 ). Morphological characterization itself may not accurately portray the actual genetic variation due to the substantial influence of environmental factors on individual phenotypic performance (Deepashree et al. 2023 ). To mitigate these limitations, urgent integration of molecular characterization becomes imperative. As mentioned by Bustamante et al. ( 2022 ) that molecular approaches have enabled better differentiation among genotypes and understanding of the true genetic diversity. The synergy between morphological and molecular approaches stands as a crucial advancement in elucidating the genetic diversity within F 1 cacao progenies, ensuring a more accurate and comprehensive assessment. Molecular DNA markers serve as reliable tools for discerning genetic relatedness within species. In comparison to other DNA markers, simple sequence repeats (SSR) with many alleles per locus would favor unique fingerprinting of many accessions (Motilal et al. 2009 ). Additionally,Mekonen et al. ( 2022 ) explained that SSR markers, owing to their attributes including high polymorphism, codominance, multi-allelic nature, and widespread distribution across the genome, remain favored among researchers. In cacao, SSR markers have been extensively employed for several purposes, such as in studying genetic diversity, aiding parental selection, and identifying true male parents, which is crucial aspects in breeding programs(Everaert et al. 2020 ; Silva et al. 2023 ). Recognizing the pivotal role of both morphological and molecular characterization in elucidating genetic traits, this study aimed to describe the phenotypic variations in cacao pod characteristics within F 1 progenies and to assess their genetic relationships by exploiting the utility of SSR markers. MATERIAL AND METHODS Plant materials A total of 20 F 1 cacao progenies derived from four distinct combinations of crosses served as the primary experimental materials in this study (Table 1 ). Each combination of crosses consisted of five F 1 progenies, which were arranged in a randomized block design (RBD) with three replications. The experiment was carried out at the Pakuwon Experimental Station, Sukabumi, West Java Province, Indonesia with an altitude of 450 m above sea level (m asl), climate type B based on Schmidt-Ferguson, and Inceptisol soil type. Table 1 Cacao F 1 genotypes used in present study No Combination of Crosses F 1 genotypes 1 ICCRI 03 x TSH 858 1–1 (3), 1–3 (1), 1–7 (1), 1–10 (1), 1–11 (1) 2 ICCRI 03 x DR 1 2 − 1 (1), 2–7 (3), 2–8 (1), 2–8 (3), 2–11 (2) 3 TSH 858 x DR 1 5 − 1 (1), 5 − 1 (2), 5 − 3 (2), 5 − 4 (1), 5–6 (2) 4 DR 1 x SCA 6 9 − 1 (1), 9 − 2 (3), 9 − 5 (2), 9 − 6 (3), 9 − 1 (1) Observation of cacao pod characteristics Cacao pod characteristics were observed across five F 1 genotypes with three replications according to the descriptors established by the International Plant Genetic Resources [IPGRI] (1980), with some modifications. The study encompassed assessments of 16 quantitative traits, including pod length (cm), pod girth (cm), pod weight (g), V and U shapes exocarp thickness (cm), fresh and dried weights of bean/pod (g), dried weight of single bean (g), bean count, pod index, number of dark purple and purple beans/pod, number of light and pale purple beans/pod, and number of normal and defect cocoa beans/pod. Statistical analysis was performed using SAS version 9.1. The dataset underwent an initial Analysis of Variance (ANOVA) to evaluate the treatment effect (F 1 genotypes) on specific traits. Post-significant differences among treatments, further analysis utilized Duncan's Multiple Range Test (DMRT) at a significance level of 5% to discern specific variations. Molecular characterization Molecular characterization was examined using 20 F 1 cacao progenies along with four parental genotypes (ICCRI 03, TSH 858, DR 1 and SCA 6). Genomic DNA extraction from cacao samples utilized a modified CTAB method, following the protocol outlined by (Allen et al. 2006 ). DNA amplification involved the use of 38 SSR markers, comprising 25 primers sourced from PGPI database, while the remaining primers derived from Pugh et al. ( 2004 ). PCR amplification protocols and procedures followed the method used by Izzah et al. ( 2022 ). The amplified products were then separated and visualized using a 6% non-denatured PAGE. The polymorphic SSR markers obtained were scored based on their allele types, and the resulting dataset was utilized for analysis employing DARWIN 6 software. Each combination of crosses was further analyzed to construct individual phylogenetic trees, enabling a comprehensive assessment of genetic relationships. RESULTS AND DISCUSSION Exploring variation in cacao pod characteristics The application of DMRT unveiled significant differences in five distinct cacao pod characteristics across each progeny, notably in pod length, girth, and weight (Table 2 ). Statistical analyses revealed that all F 1 progenies generated from TSH858 x DR1 cross combination exhibited higher average of pod girth and pod weight compared to progenies from other cross combinations. Specifically, the pod girth values within the progenies derived from TSH858 x DR 1 cross ranged impressively between 26.53 to 29.43 cm, accompanied by pod weights spanning 557.79 to 662.22 g. Furthermore, several progenies originating from other cross combinations, 1–7 (1), 2–7 (3), 2–8 (3), 9 − 1 (1), and 9 − 6 (3), statistically showed similar pod girth sizes and weights (Table 2 ). Remarkably, the average weight of cacao pods observed among F 1 progenies in this study surpassed the recorded average weights of pods harvested from cacao trees in Cote d’Ivoire during the major season (Goudsmit et al. 2023 ). These interesting results highlight the real impact of crosses between selected parental clones in enhancing the size and weight of cocoa pods. Table 2 Performance of five cacao pod characters in 20 cacao F 1 progenies Combination of crosses F 1 progenies Pod length (cm) Pod girth (cm) Pod weight (g) V shape exocarp thickness (cm) U shape exocarp thickness (cm) ICCRI03xTSH858 1–1 (3) 17.64gh 24.30cd 316.06cd 1.05de 1.44bcd 1–3 (1) 20.21cdef 24.15cde 388.01c 1.15bcd 1.58bcd 1–7 (1) 19.13efg 27.58ab 545.43ab 1.45ab 1.87ab 1–10 (1) 17.63gh 22.03def 305.44cd 0.67f 1.33cd 1–11 (1) 17.13gh 24.21cde 387.82c 1.15bcd 1.63bcd ICCRI03xDR1 2 − 1 (1) 19.39defg 23.46def 343.26cd 0.99de 1.35cd 2–7 (3) 25.53a 26.93b 596.13a 1.40abc 1.80ab 2–8 (1) 20.21cdef 22.49def 392.64c 1.23abcd 1.71abcd 2–8 (3) 21.67bcd 27.33ab 439.63bc 1.11cde 1.72abc 2–11 (2) 15.75h 21.27f 246.59d 0.79e 1.27d TSH858xDR1 5 − 1 (1) 22.73b 29.38a 662.22a 1.31abcd 2.07a 5 − 1 (2) 20.92bcde 29.43a 627.95a 1.41abc 1.73abc 5 − 3 (2) 21.67bcd 27.00b 600.75a 1.17bcd 1.74abc 5 − 4 (1) 21.08bcde 26.53b 585.00a 1.40abc 1.80ab 5–6 (2) 22.00bc 27.00b 557.79ab 1.17bcd 1.83ab DR1xSCA6 9 − 1 (1) 21.50bcde 27.00b 630.18a 1.53a 2.10a 9 − 2 (3) 18.27fg 21.86ef 315.52cd 1.01de 1.48bcd 9 − 5 (2) 20.36bcdef 23.76cde 431.94bc 1.09cde 1.63bcd 9 − 6 (3) 22.25bc 25.95bc 575.33a 1.52a 2.13a 9 − 7 (1) 19.41defg 23.22def 366.03cd 1.05de 1.49bcd CV (%) 6.17 4.99 15.15 14.59 13.42 Average 20.22 25.24 465.69 1.182 1.69 Note: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels Among the observed pod length characters, three F 1 progenies: 2–7 (3), 5 − 1 (1), and 9 − 6 (3) exhibited the longest pod lengths. These findings notably underscore the capacity for certain F 1 progenies to produce pods of substantial size, a trait highly valued in cacao breeding. Significantly, earlier research has highlighted the correlation between pod size, particularly pod weight, and bean content (Goudsmit et al. 2023 ), emphasizing the relevance of larger pods in cacao breeding objectives. Modern breeding strategies in cacao cultivation strive not only to enhance pod quantity but also to improve their size, aligning with previous studies aiming to elevate cacao production and enhance overall bean quality(Doaré et al. 2020 ). Likewise, Cilas et al. ( 2010 ) explained that the selection process in cocoa improvement should not only take into account the increase in the number of pods. The assessment of pod husk thickness in 20 F 1 progenies revealed an interesting observation. The average measurements of exocarp thickness at both the ridge (U shape) and furrow (V shape) points of cacao pods are detailed in Table 2 . The V shape exocarp thickness spanned from 0.67 cm to 1.45 cm, while the U shape exocarp exhibited a range of 1.27 cm to 2.13 cm. We found six F 1 progenies, including 9 − 1 (1), 9 − 6 (3), 1–7 (1), 2–7 (3), 5 − 1 (2) and 5 − 4 (1), displayed significantly thicker ridge and furrow exocarps compared to others. Meanwhile, three progenies, i.e., 5 − 1 (1), 5–6 (2) and 5 − 3 (2) showed increased thickness exclusively at the ridge (U shape) exocarp. The thickness of the exocarp plays an important role in cacao breeding, attributed to its correlation with resistance against pests and diseases.Nyadanu et al. ( 2011 ) highlighted a substantial negative correlation between exocarp thickness and lesion size, underscoring that thicker exocarps in cacao often correspond to increased resistance against P. palmivora . Similarly, Ando et al. ( 2015 ) demonstrated the protective mechanism present in cucumber fruit, where thicker cuticles and specific peel tissue components inhibited the growth of pathogens, elucidating the role of physical and chemical components in plant resistance mechanisms. Characteristics associated with the yield and quality of cocoa beans Fresh and dried weights of bean/pod are pivotal contributors to overall tree production. In this study demonstrated that the F 1 progeny with the designation 5 − 1 (2) exhibited the highest fresh and dried weights of bean/pod, closely followed by 5–6 (2), 2–7 (3), and 1–1 (3) as shown in Table 3 . These findings strongly suggest that selected parental genotypes effectively transmit advantageous traits to their offspring, a phenomenon well-documented in the study by Izzah et al. ( 2022 ) Thus, the bean weight per pod could be a valuable criterion in selecting high-yielding cacao varieties. (Cilas et al. 2010 ) also highlighted that the number of beans per pod, closely linked to the bean weight per pod, is a trait to enhance production rates. By identifying and understanding these specific progenies with notably higher bean weights per pod, this study elucidates the potential for selecting and cultivating high-yielding cacao varieties, contributing significantly to the advancement of cacao breeding and productivity. Table 3 Characteristics of yield and cocoa beans quality observed in 20 cacao F 1 progenies Combination of crosses F 1 progenies Fresh weight of bean/pod (g) Dried weight of bean/pod (g) Dried weight of 1 bean (g) Bean count Pod index ICCRI03xTSH858 1–1 (3) 57.56b 25.23cd 0.89defg 112.18cde 39.63bcdef 1–3 (1) 37.24cde 22.74cde 0.94cdef 106.95def 44.90bcde 1–7 (1) 49.67bcd 27.36cd 0.93cdef 110.64cde 36.69def 1–10 (1) 38.04cde 22.14cde 0.69gh 145.57b 45.16bcde 1–11 (1) 38.19cde 22.17cde 0.79defg 126.57bcd 46.52bcd ICCRI03xDR1 2 − 1 (1) 39.82bcde 20.31de 0.78efg 129.29bc 50.06bcd 2–7 (3) 54.75bc 31.29bc 0.99bcd 100.99ef 32.48efg 2–8 (1) 40.99bcde 21.77de 0.96cdef 104.42ef 48.50bcd 2–8 (3) 38.06cde 24.66cd 1.19b 83.91fgh 43.98bcde 2–11 (2) 29.79e 14.59e 0.59h 173.33a 70.35a TSH858xDR1 5 − 1 (1) 36.76cde 19.52de 0.90def 84.77fgh 51.22bc 5 − 1 (2) 78.06a 44.43a 1.47a 69.41h 23.93g 5 − 3 (2) 43.45bcde 20.69de 0.98cde 77.60gh 27.17fg 5 − 4 (1) 37.54cde 20.80de 0.89defg 87.76fgh 48.07bcd 5–6 (2) 57.20b 36.81ab 1.14bc 87.46fgh 48.34bcd DR1xSCA6 9 − 1 (1) 49.64bcd 26.50cd 1.00bcd 100.00efg 37.74cdef 9 − 2 (3) 34.20de 19.56de 0.76fgh 130.39bc 67.79a 9 − 5 (2) 33.01de 14.75e 1.00bcd 100.00efg 51.82b 9 − 6 (3) 50.72bcd 23.54cde 1.11bc 89.73efgh 42.49bcde 9 − 7 (1) 44.29bcde 22.62cde 0.96cdef 106.56def 44.60bcde CV (%) 20.98 19.65 11.35 11.17 15.70 Average 44.45 24.07 0.95 106.38 45.07 Note: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels In addition, cocoa bean size and pod index highlights a crucial aspect of cacao productivity. The pod index provides valuable insights into the cost efficiency of production and the selection of F 1 hybrids with large bean sizes (Goenaga et al. 2015 ). The correlation between bean size and pod index within F 1 progenies is noteworthy. Several progenies, such as 5 − 1 (2) and 5 − 3 (2), display large bean sizes and lower pod index (Table 3 ). These findings align with previous research that suggest a preference for lower pod index, correlating them with larger bean sizes and reduced harvest costs (Dinarti et al. 2015 ). This relationship emphasizes the potential productivity achieved by selecting progeny with lower pod index, thus contributing to enhanced efficiency and reduced production costs. On the other hand, the quality of cocoa beans is pivotal for their market value and global acceptance. Cocoa beans quality should meet the specified standards as outlined in the Indonesian National Standards (SNI 01-2323-2008), which is crucial to ensure cocoa beans fulfill stringent criteria encompassing taste and food safety, as highlighted by Ariyanti ( 2017 ) and (Botutihe et al. 2020 ). In addition, Kongor et al. ( 2016 ) underscored various indicators, including bean size, count, color, and acidity, as instrumental in assessing cocoa bean quality. Therefore, the quality of cocoa beans is among the noteworthy characteristics that we investigated in this study. The count of beans per 100 g is a very important aspect in evaluating the quality of cocoa beans and plays a significant role in the classification of various grades. According to the export standards, these counts are categorized into specific groups: AA, A, and B, wherein the desired counts per 100 g fall within the specified ranges (Ariyanti 2017 ). Our investigation revealed significant findings, particularly in progenies generated from the TSH858 x DR1 combination. All progenies derived from this specific cross combination exhibited a count of beans per 100 g less than 100, thereby aligning with grades AA/A (Table 3 ). This outcome is coherent with the large pod sizes observed in the F 1 progenies resulting from this particular cross combination. This correlation between pod size and bean count per 100 grams sheds light on the potential influence of parental combinations on specific quality attributes, strengthening the significance of parental selection in breeding programs to achieve desired bean counts and, consequently, meet quality standards for export. Another F 1 progeny that had a number of cocoa beans in the AA category was 2–8 (3), meanwhile progenies with the A category were 9 − 6 (3), 9 − 1 (1), 9 − 5 (2), 2–7 (3), 2–8 (1), 9 − 7 (1) and 1–3 (1). Thus, genetic factors undoubtedly play a substantial role, as evidenced by the consistent traits observed across specific F 1 progenies. However, the other variables including pod size, pod location, pollen quantity and quality, and environmental conditions also significantly contribute to actual bean counts (Goudsmit et al. 2023 ). The quality of cocoa beans from each F 1 progeny was assessed by observing the number of beans with varying shades of purple, normal and defective beans (Table 4 ). The results revealed that progenies 1–1 (3) and 1–10 (1) from the ICCRI03 x TSH858 crosses exhibited the highest count of dark purple beans, with values of 21.38 and 20.33, respectively. Concurrently, progenies 9 − 5 (2), 5 − 1 (1), 9 − 6 (3), and 9 − 7 (1) originating from crosses between DR1 x SCA 6 and TSH858 x DR 1 displayed the highest count of purple-colored beans, ranging between 15.52 and 20.40. Notably, progenies 5–6 (2), 2–7 (3), and 2–8 (3) resulting from the TSH858 x DR 1 and ICCRI03 x DR 1 crosses exhibited the highest counts for light purple and pale purple beans. These observations emphasize the significant influence of genetic factors from parental sources on the bean color of the progenies. Progenies derived from male parents of Forastero type (SCA6) and Trinitario with purple beans (TSH858) tended to inherit dark and purple seed color traits, whereas those from Trinitario with white beans (DR1) tended to produce progenies with light and pale purple seed colors. Bean color, along with size and count, is a parameter often used to assess cocoa bean quality(Kongor et al. 2016 ). Cocoa bean color significantly contributes to fine flavor cocoa (FFC), characterized by a balanced chocolate taste with unique flavors (Sari et al. 2022 ). The results suggested several F 1 progenies as strong candidates for high yields with high-quality flavor. Table 4 Variation of beans color and the number of cocoa beans in 20 cacao F 1 progenies Combination of crosses F 1 progenies Number of dark purple beans/pod Number of purple beans/pods Number of light purple beans/pod Number of pale purple beans/pod Number of normal cocoa beans/pod Number of defect cocoa beans/pod ICCRI03xTSH858 1–1 (3) 21.38a 12.56abcd 6.29efg 2.00d 33.14cde 3.36efg 1–3 (1) 18.27abc 7.88ef 4.52fg 3.88cd 26.36efgh 2.97efg 1–7 (1) 13.12bcde 12.99abcd 9.78bcde 3.08d 28.63cdefgh 2.82efg 1–10 (1) 20.33ab 15.78abc 9.00cdef 6.60bcd 32.23cdef 6.62c 1–11 (1) 14.39abcde 10.47cdef 7.64defg 5.34bcd 30.31cdefgh 3.75def ICCRI03xDR1 2 − 1 (1) 13.44bcde 8.19def 4.95efg 6.50bcd 29.13cdefgh 1.84fg 2–7 (3) 10.33def 17.33abc 6.11efg 15.67a 35.67bc 2.17efg 2–8 (1) 5.52fg 6.88ef 12.25bcd 6.32bcd 25.44fgh 2.78efg 2–8 (3) 3.00g 4.33f 5.00efg 12.33ab 23.67h 2.33efg 2–11 (2) 5.75fg 10.50cdef 4.83fg 11.33abc 27.83defgh 4.50cde TSH858xDR1 5 − 1 (1) 15.33abcd 18.50ab 3.00g 4.00cd 40.83 ab 2.00efg 5 − 1 (2) 9.00defg 11.33cde 7.67defg 6.67bcd 31.67cdefg 2.33efg 5 − 3 (2) 14.13abcde 11.25cde 11.13bcd 7.71bcd 44.21a 4.22def 5 − 4 (1) 7.02efg 14.98abcd 12.94bc 7.45bcd 42.39a 12.25a 5–6 (2) 16.00abcd Nd 31.00a nd 47.00a 2.00efg DR1xSCA6 9 − 1 (1) 12.00cdef 12.00abcd nd 6.00bcd 30.00cdefgh 1.00g 9 − 2 (3) 12.63cdef 12.46abcd 8.54cdef 7.12bcd 30.62cdefgh 3.16efg 9 − 5 (2) 12.67cdef 20.40a 5.00efg nd 24.43gh 6.00cd 9 − 6 (3) 2.00g 16.50abc 14.00b 1.00d 28.00defgh 10.00b 9 − 7 (1) 14.28abcde 15.52abc 8.76cdef 8.43abcd 34.39bcd 3.17efg CV (%) 30.29 28.28 27.77 57.12 11.57 33.02 Average 12.29 12.62 9.07 6.71 32.29 3.96 Note: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels The number of normal and defective beans per pod was also measured to determine the quality of the cocoa beans in each F 1 hybrid. F 1 Progenies 5–6 (2), 5 − 3 (2), 5 − 4 (1), and 5 − 1 (1) displayed the highest count of normal beans per pod (Table 4 ). These progenies emerged from TSH858 x DR1 crosses, known for their larger pod sizes. These findings align with previous research by (Goudsmit et al. 2023 ), indicating a notable increase in bean count with larger harvested pod weights. The count of normal beans per pod is a vital selection criterion for plant breeders in acquiring new superior clones. Conversely, almost all F 1 progenies exhibited a low count of defective cocoa beans per pod, with only a small fraction showing a slightly higher count. This aligns with anticipated expectations, suggesting potential resistance of the F 1 progenies to pest and disease attacks. Molecular profiling of 4 F 1 cacao populations Molecular markers play a pivotal role in characterizing genotypes within plant breeding programs. They offer insights into genetic relatedness, diversity, and the inherent genetic value of individual plants. This information empowers plant breeders by expediting the identification and selection of desired genotypes for further development and improvement (Dinarti et al. 2015 ). In the present study, we visually depicted the genetic relationships among cacao F 1 hybrids and their parental genotypes, employing 11 polymorphic SSR markers as the basis for analysis (Fig. 1 ). The first phylogenetic tree highlighted the genetic relationships between the two parental genotypes, ICCRI 03 and TSH 858, alongside their progenies. The dendrogram is segregated into three distinct clusters. The first cluster encompassed three cacao F 1 hybrids: 1–7 (1), 1–1 (3), and 1–3 (1). The second cluster included the parental genotype TSH 858 along with two F 1 hybrids, 1–10 (1) and 1–11 (1), whereas the third cluster exclusively featured the parental genotype ICCRI 03. The second phylogenetic tree displayed the genetic relatedness arising from the cross combination of ICCRI 03 x DR 1 and their five descendants, forming three distinct clusters. The first group consisted of three entities, including ICCRI 03 as the parental genotype and two F 1 hybrids (2–8 (1) and 2 − 1 (1)). The second group comprised two progenies, 2–11 (2) and 2–8 (3). Lastly, the third group featured one parental genotype (DR 1) and one progeny (2–7 (3)). The third phylogenetic tree delineated the genetic relationships among the cross combination of TSH 858 x DR 1 and their F 1 hybrids, establishing three distinct clusters. The first cluster featured the parental genotype TSH 858 and two F 1 hybrids, 5 − 4 (1) and 5 − 1 (1). The second cluster comprised DR 1 as the parental genotype, along with two F 1 progenies: 5 − 1 (2) and 5 − 3 (2). Notably, the progeny labeled 5 − 1 (2) demonstrated remarkable similarity to DR 1, its female parent. The third cluster exclusively contained one F 1 hybrid, 5–6 (2). In the fourth phylogenetic tree, the genetic relatedness between the parental genotypes DR 1 x SCA 6 and their five F 1 progenies was depicted, forming three clusters. The first cluster encompassed four members, further divided into two subclusters: subcluster I featured the parental genotype SCA 6 and 9 − 7 (1), while subcluster II comprised DR 1 and 9 − 1 (1). The second cluster contained two F 1 hybrids, 9 − 6 (3) and 9 − 2 (3), whereas the third cluster exclusively featured one F 1 hybrid, 9 − 5 (2). The clustering analysis of cacao F 1 hybrids derived from four cross combinations unveiled substantial genetic diversity, displayed distinctiveness within each F 1 progeny. Certain F 1 progenies shared genetic affinities with either male or female parental genotypes, while others formed discrete clusters, indicating unique genetic profiles distinct from both parents. These results underscore the efficacy of deliberate crosses between selected parental genotypes, crucial for augmenting genetic diversity, an important aspect in cacao breeding programs. This finding aligns with prior research emphasizing the essential role of genetic characterization and variation in fostering successful breeding and conservation of cacao cultivars (Lindo et al. 2018 ). This study highlights the significance of controlled hybridizations and genetic assessments in elevating productivity and cocoa bean quality, providing a framework for future breeding efforts. We found that F 1 progenies resulting from the cross between TSH858xDR1 demonstrated significant outcomes including higher average of pod weight and bean count per 100 g in line with AA/A quality. In particular, progeny coded 5 − 1 (2) had the lowest pod index associated with larger pod and bean sizes. Molecular characterization proved that all F1 progenies were different from each other. Thus, differences in yield and quality of cocoa beans in each progeny are most likely caused by genetic differences between progenies. These findings underscore the efficacy of intentional crosses which is crucial for enhancing genetic diversity, a fundamental aspect in cacao breeding. Declarations FUNDING Authors gratefully acknowledges the Head of Research Institute for Industrial and Beverage Crops, Indonesian Ministry of Agriculture who has supported the field work and molecular activities. This research was supported by the National Indonesian Budget under Ministry of Agriculture year 2018–2020 and Research Organization for Agriculture and Food, National Research and Innovation Agency under the project of Research Program of Superior Crops Varieties year 2022–2023. Author Contribution NKI. carried out research in the lab and field, wrote the main manuscriptCT. carried out research in the field and Data analysesWA, KDS, SS, MP, EBT, AA, NKF. carried out research in the field + reviewed manuscriptRR, DP, ER. reviewed manuscrip Acknowledgement Authors gratefully acknowledges the Head of Research Institute for Industrial and Beverage Crops, Indonesian Ministry of Agriculture who has supported the field work and molecular activities. This research was supported by the National Indonesian Budget under Ministry of Agriculture year 2018-2020 and Research Organization for Agriculture and Food, National Research and Innovation Agency under the project of Research Program of Superior Crops Varieties year 2022-2023 References Allen GC, Flores-Vergara MA, Krasynanski S, et al (2006) A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide. 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Tree Genet Genomes 6:219–226. https://doi.org/10.1007/s11295-009-0242-9 Deepashree G, Raut N, Gasti VD, et al (2023) Molecular and morphological diversity among the cluster bean [Cyamopsis tetragonoloba (L.) Taub.] genotypes. Genet Resour Crop Evol 70:159–168 Dinarti D, Susilo AW, Meinhardt LW, et al (2015) Genetic diversity and parentage in farmer selections of cacao from southern sulawesi, indonesia revealed by microsatellite markers. Breed Sci 65:438–446. https://doi.org/10.1270/jsbbs.65.438 Doaré F, Ribeyre F, Cilas C (2020) Genetic and environmental links between traits of cocoa beans and pods clarify the phenotyping processes to be implemented. Sci Rep 10:1–6. https://doi.org/10.1038/s41598-020-66969-9 Everaert H, De Wever J, Tang TKH, et al (2020) Genetic classification of Vietnamese cacao cultivars assessed by SNP and SSR markers. Tree Genet Genomes 16:2–11. https://doi.org/10.1007/s11295-020-01439-x Goenaga R, Guiltinan M, Maximova S, et al (2015) Yield Performance and Bean Quality Traits of Cacao Propagated by Grafting and Somatic Embryo-derived Cuttings. HORTSCIENCE 50:358–362 Goudsmit E, Rozendaal DMA, Tosto A, Slingerland M (2023) Effects of fertilizer application on cacao pod development, pod nutrient content and yield. Sci Hortic 313:1–15. https://doi.org/10.1016/j.scienta.2023.111869 Izzah NK, Sulistiyorini I, Wicaksono INA (2022) Identification of true male parents in F1 populations of cacao using SSR markers. In: IOP Conference Series: Earth and Environmental Science. IOP Publishing Ltd, pp 1–8 Karakaya O, Yaman M, Balta F, et al (2023) Assessment of genetic diversity revealed by morphological traits and ISSR markers in hazelnut germplasm (Corylus avellana L.) from Eastern Black Sea Region, Turkey. Genet Resour Crop Evol 70:525–537 Kongor JE, Hinneh M, de Walle D Van, et al (2016) Factors influencing quality variation in cocoa (Theobroma cacao) bean flavour profile - A review. Food Research International 82:44–52 Lindo AA, Robinson DE, Tennant PF, et al (2018) Molecular Characterization of Cacao (Theobroma cacao) Germplasm from Jamaica Using Single Nucleotide Polymorphism (SNP) Markers. Trop Plant Biol 11:93–106. https://doi.org/10.1007/s12042-018-9203-5 Mekonen DA, Abraham A, Oselebe H, et al (2022) Genetic diversity and population structure analysis of Grass pea (Lathyrus sativus L.) accessions collected from North-Western Ethiopia using SSR markers. Genet Resour Crop Evol 69:1247–1260 Motamayor JC, Lachenaud P, da Silva e Mota JW, et al (2008) Geographic and genetic population differentiation of the Amazonian chocolate tree (Theobroma cacao L). PLoS One 3:1–8. https://doi.org/10.1371/journal.pone.0003311 Motilal LA, Zhang D, Umaharan P, et al (2009) Increasing accuracy and throughput in large-scale microsatellite fingerprinting of cacao field germplasm collections. Trop Plant Biol 2:23–37. https://doi.org/10.1007/s12042-008-9016-z Nyadanu D, Assuah MK, Adomako B, et al (2011) Thickness of the cocoa pod husk and its moisture content as resistance factors to Phytophthora pod rot. Pugh T, Fouet O, Risterucci AM, et al (2004) A new cacao linkage map based on codominant markers: Development and integration of 201 new microsatellite markers. Theoretical and Applied Genetics 108:1151–1161. https://doi.org/10.1007/s00122-003-1533-4 Rodríguez-Carrasco Y, Gaspari A, Graziani G, et al (2018) Fast analysis of polyphenols and alkaloids in cocoa-based products by ultra-high performance liquid chromatography and Orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap-MS/MS). Food Research International 111:229–236. https://doi.org/10.1016/j.foodres.2018.05.032 Sari IA, Murti RH, Misnawi, et al (2022) Sensory profiles of cocoa genotypes in Indonesia. Biodiversitas 23:648–654. https://doi.org/10.13057/biodiv/d230205 Shilpashree N, Devi SN, Manjunathagowda DC, et al (2021) Morphological characterization, variability and diversity among vegetable soybean (Glycine max L.) genotypes. Plants 10:671 Silva GS, de Santana Souza J, de Souza Junior JO, et al (2023) Mass Selection of Drought Tolerant Cacao in Bahia, Brazil: Morphological, Genetic Structure, and Diversity Analysis. Trop Plant Biol 16:53–66. https://doi.org/10.1007/s12042-023-09330-4 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4766155","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335427843,"identity":"245fdc18-070b-4a35-835f-5f00ca1c8d80","order_by":0,"name":"Nur Kholilatul 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Agency","correspondingAuthor":false,"prefix":"","firstName":"Asif","middleName":"","lastName":"Aunillah","suffix":""},{"id":335427852,"identity":"6a2232f9-8c1b-4bb2-a38d-ad3e5b71b155","order_by":9,"name":"Elsera Br Tarigan","email":"","orcid":"","institution":"Research Center for Agroindustry, Research Organization for Agriculture and Food, National Research and Innovation Agency","correspondingAuthor":false,"prefix":"","firstName":"Elsera","middleName":"Br","lastName":"Tarigan","suffix":""},{"id":335427853,"identity":"bfcb55a5-b2b2-497b-ab4a-3d080d1d9f99","order_by":10,"name":"Mahardika Puspitasari","email":"","orcid":"","institution":"Research Center for Estate Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Mahardika","middleName":"","lastName":"Puspitasari","suffix":""},{"id":335427854,"identity":"d586ea07-9409-44f5-a1ec-c23c33c4eb74","order_by":11,"name":"Susilawati Susilawati","email":"","orcid":"","institution":"Research Center for Estate Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Susilawati","middleName":"","lastName":"Susilawati","suffix":""}],"badges":[],"createdAt":"2024-07-19 04:37:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4766155/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4766155/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63006958,"identity":"ac956952-566b-49d8-b0b1-f106f8142125","added_by":"auto","created_at":"2024-08-22 04:40:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35286,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic relationships among four parental genotypes and 20 F\u003csub\u003e1\u003c/sub\u003e hybrids established using SSR markers: a. Dendrogram depicting relationships within ICCRI 03 x TSH 858, b. Dendrogram illustrating the genetic association within ICCRI 03 x TSH 858, c. Dendrogram showcasing relationships within TSH 858 x DR 1, and d. Dendrogram highlighting the genetic connections within DR 1 x SCA 6.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4766155/v1/057c80bf4f75756b18656c6f.jpg"},{"id":63951248,"identity":"e204b055-0486-4826-8ab4-3a600cb83fa8","added_by":"auto","created_at":"2024-09-04 07:02:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":850353,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4766155/v1/7c6deba4-bf10-439a-8464-7f069ee28191.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Improvement of Cacao Pod Characteristics and its Molecular Characterization in 4 F1 Cacao Populations","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCacao (\u003cem\u003eTheobroma cacao\u003c/em\u003e L.) is the only source of cocoa beans as the bases of global industries including food, confectionary, beverages, cosmetics, and pharmaceuticals. The quality of these materials must meet the needs of the industry, thus significantly influencing global market prices. However, maintaining consistent quality of cocoa beans poses many challenges due to the lack of cocoa beans that meet quality standards (Rodr\u0026iacute;guez-Carrasco et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Diverse factors have a major impact on cocoa bean quality, encompassing genotypic variations, environmental conditions, bean maturity levels, and post-harvest procedures (Calvo et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSelective crosses between superior genotypes represent a key strategy for attaining high-quality cocoa beans, concurrently enhancing genetic diversity within populations(Izzah et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, crosses between genetically distant parents have emerged as a principal method for plant breeders to augment diversity as well as to obtain heterosis effect (Motamayor et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The role of genetic variation within species is one of the important aspects in breeding studies, serving as a main factor for establishing novel high-yielding varieties (Shilpashree et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The ensuing F\u003csub\u003e1\u003c/sub\u003e progenies then underwent morphological characterization to pinpoint crucial traits associated with the yield and bean quality. Of which, assessing morphological traits plays a pivotal role in evaluating plant breeding materials, essential in both conventional and modern breeding methods(Bidot Mart\u0026iacute;nez et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the collected data serve as a valuable asset for selecting superior genotypes with desired traits (Bekele and Phillips-Mora \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough, the two identical parents of cacao cultivars were crossed, in fact, morphological variations in their F\u003csub\u003e1\u003c/sub\u003e progenies were commonly observed, underscoring the need to assess their genetic relationships. Thus, determination of genetic variability in F\u003csub\u003e1\u003c/sub\u003e cacao progenies both through morphological and molecular characterizations had been a prevalent approach (Bekele and Phillips-Mora \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such evaluation is essential not only to maintain genetic variability within the progenies but also for making proper decisions about their utilization in breeding programs (Karakaya et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Morphological characterization itself may not accurately portray the actual genetic variation due to the substantial influence of environmental factors on individual phenotypic performance (Deepashree et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To mitigate these limitations, urgent integration of molecular characterization becomes imperative. As mentioned by Bustamante et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) that molecular approaches have enabled better differentiation among genotypes and understanding of the true genetic diversity. The synergy between morphological and molecular approaches stands as a crucial advancement in elucidating the genetic diversity within F\u003csub\u003e1\u003c/sub\u003e cacao progenies, ensuring a more accurate and comprehensive assessment.\u003c/p\u003e \u003cp\u003eMolecular DNA markers serve as reliable tools for discerning genetic relatedness within species. In comparison to other DNA markers, simple sequence repeats (SSR) with many alleles per locus would favor unique fingerprinting of many accessions (Motilal et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Additionally,Mekonen et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) explained that SSR markers, owing to their attributes including high polymorphism, codominance, multi-allelic nature, and widespread distribution across the genome, remain favored among researchers. In cacao, SSR markers have been extensively employed for several purposes, such as in studying genetic diversity, aiding parental selection, and identifying true male parents, which is crucial aspects in breeding programs(Everaert et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Silva et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Recognizing the pivotal role of both morphological and molecular characterization in elucidating genetic traits, this study aimed to describe the phenotypic variations in cacao pod characteristics within F\u003csub\u003e1\u003c/sub\u003e progenies and to assess their genetic relationships by exploiting the utility of SSR markers.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials\u003c/h2\u003e \u003cp\u003eA total of 20 F\u003csub\u003e1\u003c/sub\u003e cacao progenies derived from four distinct combinations of crosses served as the primary experimental materials in this study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each combination of crosses consisted of five F\u003csub\u003e1\u003c/sub\u003e progenies, which were arranged in a randomized block design (RBD) with three replications. The experiment was carried out at the Pakuwon Experimental Station, Sukabumi, West Java Province, Indonesia with an altitude of 450 m above sea level (m asl), climate type B based on Schmidt-Ferguson, and Inceptisol soil type.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCacao F\u003csub\u003e1\u003c/sub\u003e genotypes used in present study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCombination of Crosses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e genotypes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICCRI 03 x TSH 858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u0026ndash;1 (3), 1\u0026ndash;3 (1), 1\u0026ndash;7 (1), 1\u0026ndash;10 (1), 1\u0026ndash;11 (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICCRI 03 x DR 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 2\u0026ndash;7 (3), 2\u0026ndash;8 (1), 2\u0026ndash;8 (3), 2\u0026ndash;11 (2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH 858 x DR 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2), 5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2), 5\u0026thinsp;\u0026minus;\u0026thinsp;4 (1), 5\u0026ndash;6 (2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDR 1 x SCA 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 9\u0026thinsp;\u0026minus;\u0026thinsp;2 (3), 9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2), 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3), 9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eObservation of cacao pod characteristics\u003c/h2\u003e \u003cp\u003eCacao pod characteristics were observed across five F\u003csub\u003e1\u003c/sub\u003e genotypes with three replications according to the descriptors established by the International Plant Genetic Resources [IPGRI] (1980), with some modifications. The study encompassed assessments of 16 quantitative traits, including pod length (cm), pod girth (cm), pod weight (g), V and U shapes exocarp thickness (cm), fresh and dried weights of bean/pod (g), dried weight of single bean (g), bean count, pod index, number of dark purple and purple beans/pod, number of light and pale purple beans/pod, and number of normal and defect cocoa beans/pod.\u003c/p\u003e \u003cp\u003eStatistical analysis was performed using SAS version 9.1. The dataset underwent an initial Analysis of Variance (ANOVA) to evaluate the treatment effect (F\u003csub\u003e1\u003c/sub\u003e genotypes) on specific traits. Post-significant differences among treatments, further analysis utilized Duncan's Multiple Range Test (DMRT) at a significance level of 5% to discern specific variations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMolecular characterization\u003c/h2\u003e \u003cp\u003eMolecular characterization was examined using 20 F\u003csub\u003e1\u003c/sub\u003e cacao progenies along with four parental genotypes (ICCRI 03, TSH 858, DR 1 and SCA 6). Genomic DNA extraction from cacao samples utilized a modified CTAB method, following the protocol outlined by (Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDNA amplification involved the use of 38 SSR markers, comprising 25 primers sourced from PGPI database, while the remaining primers derived from Pugh et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). PCR amplification protocols and procedures followed the method used by Izzah et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The amplified products were then separated and visualized using a 6% non-denatured PAGE. The polymorphic SSR markers obtained were scored based on their allele types, and the resulting dataset was utilized for analysis employing DARWIN 6 software. Each combination of crosses was further analyzed to construct individual phylogenetic trees, enabling a comprehensive assessment of genetic relationships.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eExploring variation in cacao pod characteristics\u003c/h2\u003e \u003cp\u003eThe application of DMRT unveiled significant differences in five distinct cacao pod characteristics across each progeny, notably in pod length, girth, and weight (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Statistical analyses revealed that all F\u003csub\u003e1\u003c/sub\u003e progenies generated from TSH858 x DR1 cross combination exhibited higher average of pod girth and pod weight compared to progenies from other cross combinations. Specifically, the pod girth values within the progenies derived from TSH858 x DR 1 cross ranged impressively between 26.53 to 29.43 cm, accompanied by pod weights spanning 557.79 to 662.22 g. Furthermore, several progenies originating from other cross combinations, 1\u0026ndash;7 (1), 2\u0026ndash;7 (3), 2\u0026ndash;8 (3), 9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), and 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3), statistically showed similar pod girth sizes and weights (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Remarkably, the average weight of cacao pods observed among F\u003csub\u003e1\u003c/sub\u003e progenies in this study surpassed the recorded average weights of pods harvested from cacao trees in Cote d\u0026rsquo;Ivoire during the major season (Goudsmit et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These interesting results highlight the real impact of crosses between selected parental clones in enhancing the size and weight of cocoa pods.\u003c/p\u003e \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePerformance of five cacao pod characters in 20 cacao F\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eCombination of crosses\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003ePod length (cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003ePod girth (cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003ePod weight (g)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 14.2572%;\"\u003e\n \u003cp\u003eV shape exocarp thickness (cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 5.4788%;\"\u003e\n \u003cp\u003eU shape exocarp thickness (cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eICCRI03xTSH858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e1\u0026ndash;1 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e17.64gh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e24.30cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e316.06cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.05de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.44bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e1\u0026ndash;3 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e20.21cdef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e24.15cde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e388.01c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.15bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.58bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e1\u0026ndash;7 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e19.13efg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e27.58ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e545.43ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.45ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.87ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e1\u0026ndash;10 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e17.63gh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e22.03def\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e305.44cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e0.67f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.33cd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e1\u0026ndash;11 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e17.13gh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e24.21cde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e387.82c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.15bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.63bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eICCRI03xDR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e19.39defg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e23.46def\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e343.26cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e0.99de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.35cd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e2\u0026ndash;7 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e25.53a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e26.93b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e596.13a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.40abc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.80ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e2\u0026ndash;8 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e20.21cdef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e22.49def\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e392.64c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.23abcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.71abcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e2\u0026ndash;8 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e21.67bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e27.33ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e439.63bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.11cde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.72abc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e2\u0026ndash;11 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e15.75h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e21.27f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e246.59d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e0.79e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.27d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eTSH858xDR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e22.73b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e29.38a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e662.22a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.31abcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e2.07a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e20.92bcde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e29.43a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e627.95a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.41abc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.73abc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e21.67bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e27.00b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e600.75a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.17bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.74abc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;4 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e21.08bcde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e26.53b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e585.00a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.40abc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.80ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e5\u0026ndash;6 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e22.00bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e27.00b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e557.79ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.17bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.83ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eDR1xSCA6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e21.50bcde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e27.00b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e630.18a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.53a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e2.10a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;2 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e18.27fg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e21.86ef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e315.52cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.01de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.48bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e20.36bcdef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e23.76cde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e431.94bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.09cde\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.63bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e22.25bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e25.95bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e575.33a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.52a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e2.13a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\n \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e19.41defg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e23.22def\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e366.03cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.05de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.49bcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eCV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e6.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e15.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e14.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e13.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 13.748%;\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.536%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 8.6562%;\"\u003e\n \u003cp\u003e20.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e25.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.4341%;\"\u003e\n \u003cp\u003e465.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 11.1003%;\"\u003e\n \u003cp\u003e1.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"width: 11.915%;\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 70.1659%;\"\u003eNote: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e \u003cp\u003eAmong the observed pod length characters, three F\u003csub\u003e1\u003c/sub\u003e progenies: 2\u0026ndash;7 (3), 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), and 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3) exhibited the longest pod lengths. These findings notably underscore the capacity for certain F\u003csub\u003e1\u003c/sub\u003e progenies to produce pods of substantial size, a trait highly valued in cacao breeding. Significantly, earlier research has highlighted the correlation between pod size, particularly pod weight, and bean content (Goudsmit et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), emphasizing the relevance of larger pods in cacao breeding objectives. Modern breeding strategies in cacao cultivation strive not only to enhance pod quantity but also to improve their size, aligning with previous studies aiming to elevate cacao production and enhance overall bean quality(Doar\u0026eacute; et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Likewise, Cilas et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) explained that the selection process in cocoa improvement should not only take into account the increase in the number of pods.\u003c/p\u003e \u003cp\u003eThe assessment of pod husk thickness in 20 F\u003csub\u003e1\u003c/sub\u003e progenies revealed an interesting observation. The average measurements of exocarp thickness at both the ridge (U shape) and furrow (V shape) points of cacao pods are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The V shape exocarp thickness spanned from 0.67 cm to 1.45 cm, while the U shape exocarp exhibited a range of 1.27 cm to 2.13 cm. We found six F\u003csub\u003e1\u003c/sub\u003e progenies, including 9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3), 1\u0026ndash;7 (1), 2\u0026ndash;7 (3), 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) and 5\u0026thinsp;\u0026minus;\u0026thinsp;4 (1), displayed significantly thicker ridge and furrow exocarps compared to others. Meanwhile, three progenies, i.e., 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 5\u0026ndash;6 (2) and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2) showed increased thickness exclusively at the ridge (U shape) exocarp. The thickness of the exocarp plays an important role in cacao breeding, attributed to its correlation with resistance against pests and diseases.Nyadanu et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) highlighted a substantial negative correlation between exocarp thickness and lesion size, underscoring that thicker exocarps in cacao often correspond to increased resistance against \u003cem\u003eP. palmivora\u003c/em\u003e. Similarly, Ando et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) demonstrated the protective mechanism present in cucumber fruit, where thicker cuticles and specific peel tissue components inhibited the growth of pathogens, elucidating the role of physical and chemical components in plant resistance mechanisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics associated with the yield and quality of cocoa beans\u003c/h2\u003e \u003cp\u003eFresh and dried weights of bean/pod are pivotal contributors to overall tree production. In this study demonstrated that the F\u003csub\u003e1\u003c/sub\u003e progeny with the designation 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) exhibited the highest fresh and dried weights of bean/pod, closely followed by 5\u0026ndash;6 (2), 2\u0026ndash;7 (3), and 1\u0026ndash;1 (3) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. These findings strongly suggest that selected parental genotypes effectively transmit advantageous traits to their offspring, a phenomenon well-documented in the study by Izzah et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) Thus, the bean weight per pod could be a valuable criterion in selecting high-yielding cacao varieties. (Cilas et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) also highlighted that the number of beans per pod, closely linked to the bean weight per pod, is a trait to enhance production rates. By identifying and understanding these specific progenies with notably higher bean weights per pod, this study elucidates the potential for selecting and cultivating high-yielding cacao varieties, contributing significantly to the advancement of cacao breeding and productivity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of yield and cocoa beans quality observed in 20 cacao F\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination of crosses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFresh weight of bean/pod (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDried weight of bean/pod (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDried weight of 1 bean (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBean count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePod index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eICCRI03xTSH858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.56b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.23cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89defg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112.18cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.63bcdef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;3 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.24cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.74cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e106.95def\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.90bcde\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;7 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.67bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.36cd\u003c/p\u003e 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colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;11 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.19cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.17cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79defg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126.57bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.52bcd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eICCRI03xDR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.82bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.31de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78efg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129.29bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50.06bcd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;7 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.75bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.29bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.99ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.48efg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e 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align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.47a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.41h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.93g\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.45bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.69de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.60gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.17fg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e 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\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87.46fgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.34bcd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDR1xSCA6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.64bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.50cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00efg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.74cdef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;2 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.20de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.56de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76fgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e130.39bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.79a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.01de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.75e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00efg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.82b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.72bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.54cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.73efgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.49bcde\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.29bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.62cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e106.56def\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.60bcde\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e106.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn addition, cocoa bean size and pod index highlights a crucial aspect of cacao productivity. The pod index provides valuable insights into the cost efficiency of production and the selection of F\u003csub\u003e1\u003c/sub\u003e hybrids with large bean sizes (Goenaga et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The correlation between bean size and pod index within F\u003csub\u003e1\u003c/sub\u003e progenies is noteworthy. Several progenies, such as 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2), display large bean sizes and lower pod index (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings align with previous research that suggest a preference for lower pod index, correlating them with larger bean sizes and reduced harvest costs (Dinarti et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This relationship emphasizes the potential productivity achieved by selecting progeny with lower pod index, thus contributing to enhanced efficiency and reduced production costs.\u003c/p\u003e \u003cp\u003eOn the other hand, the quality of cocoa beans is pivotal for their market value and global acceptance. Cocoa beans quality should meet the specified standards as outlined in the Indonesian National Standards (SNI 01-2323-2008), which is crucial to ensure cocoa beans fulfill stringent criteria encompassing taste and food safety, as highlighted by Ariyanti (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and (Botutihe et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, Kongor et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) underscored various indicators, including bean size, count, color, and acidity, as instrumental in assessing cocoa bean quality. Therefore, the quality of cocoa beans is among the noteworthy characteristics that we investigated in this study.\u003c/p\u003e \u003cp\u003eThe count of beans per 100 g is a very important aspect in evaluating the quality of cocoa beans and plays a significant role in the classification of various grades. According to the export standards, these counts are categorized into specific groups: AA, A, and B, wherein the desired counts per 100 g fall within the specified ranges (Ariyanti \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Our investigation revealed significant findings, particularly in progenies generated from the TSH858 x DR1 combination. All progenies derived from this specific cross combination exhibited a count of beans per 100 g less than 100, thereby aligning with grades AA/A (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This outcome is coherent with the large pod sizes observed in the F\u003csub\u003e1\u003c/sub\u003e progenies resulting from this particular cross combination. This correlation between pod size and bean count per 100 grams sheds light on the potential influence of parental combinations on specific quality attributes, strengthening the significance of parental selection in breeding programs to achieve desired bean counts and, consequently, meet quality standards for export. Another F\u003csub\u003e1\u003c/sub\u003e progeny that had a number of cocoa beans in the AA category was 2\u0026ndash;8 (3), meanwhile progenies with the A category were 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3), 9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2), 2\u0026ndash;7 (3), 2\u0026ndash;8 (1), 9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1) and 1\u0026ndash;3 (1). Thus, genetic factors undoubtedly play a substantial role, as evidenced by the consistent traits observed across specific F\u003csub\u003e1\u003c/sub\u003e progenies. However, the other variables including pod size, pod location, pollen quantity and quality, and environmental conditions also significantly contribute to actual bean counts (Goudsmit et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe quality of cocoa beans from each F\u003csub\u003e1\u003c/sub\u003e progeny was assessed by observing the number of beans with varying shades of purple, normal and defective beans (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results revealed that progenies 1\u0026ndash;1 (3) and 1\u0026ndash;10 (1) from the ICCRI03 x TSH858 crosses exhibited the highest count of dark purple beans, with values of 21.38 and 20.33, respectively. Concurrently, progenies 9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2), 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1), 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3), and 9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1) originating from crosses between DR1 x SCA 6 and TSH858 x DR 1 displayed the highest count of purple-colored beans, ranging between 15.52 and 20.40. Notably, progenies 5\u0026ndash;6 (2), 2\u0026ndash;7 (3), and 2\u0026ndash;8 (3) resulting from the TSH858 x DR 1 and ICCRI03 x DR 1 crosses exhibited the highest counts for light purple and pale purple beans. These observations emphasize the significant influence of genetic factors from parental sources on the bean color of the progenies. Progenies derived from male parents of Forastero type (SCA6) and Trinitario with purple beans (TSH858) tended to inherit dark and purple seed color traits, whereas those from Trinitario with white beans (DR1) tended to produce progenies with light and pale purple seed colors. Bean color, along with size and count, is a parameter often used to assess cocoa bean quality(Kongor et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Cocoa bean color significantly contributes to fine flavor cocoa (FFC), characterized by a balanced chocolate taste with unique flavors (Sari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The results suggested several F\u003csub\u003e1\u003c/sub\u003e progenies as strong candidates for high yields with high-quality flavor.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariation of beans color and the number of cocoa beans in 20 cacao F\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination of crosses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e progenies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of dark purple beans/pod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of purple beans/pods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNumber of light purple beans/pod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber of pale purple beans/pod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNumber of normal cocoa beans/pod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNumber of defect cocoa beans/pod\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICCRI03xTSH858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.38a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.56abcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.29efg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.14cde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.36efg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;3 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.27abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.88ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.52fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.88cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.36efgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.97efg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;7 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.12bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.99abcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.78bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.08d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.63cdefgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.82efg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;10 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.33ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.78abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.00cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.60bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.23cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.62c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;11 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.39abcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.47cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.64defg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.34bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.31cdefgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.75def\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICCRI03xDR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.44bcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.19def\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.95efg\u003c/p\u003e \u003c/td\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.28abcde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.52abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.76cdef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.43abcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.39bcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.17efg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: Numbers followed by the same letters in the same column are not significantly different according to Duncan Multiple Range Test at 5% levels\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe number of normal and defective beans per pod was also measured to determine the quality of the cocoa beans in each F\u003csub\u003e1\u003c/sub\u003e hybrid. F\u003csub\u003e1\u003c/sub\u003e Progenies 5\u0026ndash;6 (2), 5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2), 5\u0026thinsp;\u0026minus;\u0026thinsp;4 (1), and 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1) displayed the highest count of normal beans per pod (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These progenies emerged from TSH858 x DR1 crosses, known for their larger pod sizes. These findings align with previous research by (Goudsmit et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), indicating a notable increase in bean count with larger harvested pod weights. The count of normal beans per pod is a vital selection criterion for plant breeders in acquiring new superior clones. Conversely, almost all F\u003csub\u003e1\u003c/sub\u003e progenies exhibited a low count of defective cocoa beans per pod, with only a small fraction showing a slightly higher count. This aligns with anticipated expectations, suggesting potential resistance of the F\u003csub\u003e1\u003c/sub\u003e progenies to pest and disease attacks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMolecular profiling of 4 F\u003csub\u003e1\u003c/sub\u003e cacao populations\u003c/h2\u003e \u003cp\u003eMolecular markers play a pivotal role in characterizing genotypes within plant breeding programs. They offer insights into genetic relatedness, diversity, and the inherent genetic value of individual plants. This information empowers plant breeders by expediting the identification and selection of desired genotypes for further development and improvement (Dinarti et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In the present study, we visually depicted the genetic relationships among cacao F\u003csub\u003e1\u003c/sub\u003e hybrids and their parental genotypes, employing 11 polymorphic SSR markers as the basis for analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe first phylogenetic tree highlighted the genetic relationships between the two parental genotypes, ICCRI 03 and TSH 858, alongside their progenies. The dendrogram is segregated into three distinct clusters. The first cluster encompassed three cacao F\u003csub\u003e1\u003c/sub\u003e hybrids: 1\u0026ndash;7 (1), 1\u0026ndash;1 (3), and 1\u0026ndash;3 (1). The second cluster included the parental genotype TSH 858 along with two F\u003csub\u003e1\u003c/sub\u003e hybrids, 1\u0026ndash;10 (1) and 1\u0026ndash;11 (1), whereas the third cluster exclusively featured the parental genotype ICCRI 03. The second phylogenetic tree displayed the genetic relatedness arising from the cross combination of ICCRI 03 x DR 1 and their five descendants, forming three distinct clusters. The first group consisted of three entities, including ICCRI 03 as the parental genotype and two F\u003csub\u003e1\u003c/sub\u003e hybrids (2\u0026ndash;8 (1) and 2\u0026thinsp;\u0026minus;\u0026thinsp;1 (1)). The second group comprised two progenies, 2\u0026ndash;11 (2) and 2\u0026ndash;8 (3). Lastly, the third group featured one parental genotype (DR 1) and one progeny (2\u0026ndash;7 (3)). The third phylogenetic tree delineated the genetic relationships among the cross combination of TSH 858 x DR 1 and their F\u003csub\u003e1\u003c/sub\u003e hybrids, establishing three distinct clusters. The first cluster featured the parental genotype TSH 858 and two F\u003csub\u003e1\u003c/sub\u003e hybrids, 5\u0026thinsp;\u0026minus;\u0026thinsp;4 (1) and 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (1). The second cluster comprised DR 1 as the parental genotype, along with two F\u003csub\u003e1\u003c/sub\u003e progenies: 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 (2). Notably, the progeny labeled 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) demonstrated remarkable similarity to DR 1, its female parent. The third cluster exclusively contained one F\u003csub\u003e1\u003c/sub\u003e hybrid, 5\u0026ndash;6 (2). In the fourth phylogenetic tree, the genetic relatedness between the parental genotypes DR 1 x SCA 6 and their five F\u003csub\u003e1\u003c/sub\u003e progenies was depicted, forming three clusters. The first cluster encompassed four members, further divided into two subclusters: subcluster I featured the parental genotype SCA 6 and 9\u0026thinsp;\u0026minus;\u0026thinsp;7 (1), while subcluster II comprised DR 1 and 9\u0026thinsp;\u0026minus;\u0026thinsp;1 (1). The second cluster contained two F\u003csub\u003e1\u003c/sub\u003e hybrids, 9\u0026thinsp;\u0026minus;\u0026thinsp;6 (3) and 9\u0026thinsp;\u0026minus;\u0026thinsp;2 (3), whereas the third cluster exclusively featured one F\u003csub\u003e1\u003c/sub\u003e hybrid, 9\u0026thinsp;\u0026minus;\u0026thinsp;5 (2).\u003c/p\u003e \u003cp\u003eThe clustering analysis of cacao F\u003csub\u003e1\u003c/sub\u003e hybrids derived from four cross combinations unveiled substantial genetic diversity, displayed distinctiveness within each F\u003csub\u003e1\u003c/sub\u003e progeny. Certain F\u003csub\u003e1\u003c/sub\u003e progenies shared genetic affinities with either male or female parental genotypes, while others formed discrete clusters, indicating unique genetic profiles distinct from both parents. These results underscore the efficacy of deliberate crosses between selected parental genotypes, crucial for augmenting genetic diversity, an important aspect in cacao breeding programs. This finding aligns with prior research emphasizing the essential role of genetic characterization and variation in fostering successful breeding and conservation of cacao cultivars (Lindo et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study highlights the significance of controlled hybridizations and genetic assessments in elevating productivity and cocoa bean quality, providing a framework for future breeding efforts. We found that F\u003csub\u003e1\u003c/sub\u003e progenies resulting from the cross between TSH858xDR1 demonstrated significant outcomes including higher average of pod weight and bean count per 100 g in line with AA/A quality. In particular, progeny coded 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2) had the lowest pod index associated with larger pod and bean sizes. Molecular characterization proved that all F1 progenies were different from each other. Thus, differences in yield and quality of cocoa beans in each progeny are most likely caused by genetic differences between progenies. These findings underscore the efficacy of intentional crosses which is crucial for enhancing genetic diversity, a fundamental aspect in cacao breeding.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFUNDING\u003c/h2\u003e \u003cp\u003eAuthors gratefully acknowledges the Head of Research Institute for Industrial and Beverage Crops, Indonesian Ministry of Agriculture who has supported the field work and molecular activities. This research was supported by the National Indonesian Budget under Ministry of Agriculture year 2018\u0026ndash;2020 and Research Organization for Agriculture and Food, National Research and Innovation Agency under the project of Research Program of Superior Crops Varieties year 2022\u0026ndash;2023.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNKI. carried out research in the lab and field, wrote the main manuscriptCT. carried out research in the field and Data analysesWA, KDS, SS, MP, EBT, AA, NKF. carried out research in the field + reviewed manuscriptRR, DP, ER. reviewed manuscrip\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAuthors gratefully acknowledges the Head of Research Institute for Industrial and Beverage Crops, Indonesian Ministry of Agriculture who has supported the field work and molecular activities. This research was supported by the National Indonesian Budget under Ministry of Agriculture year 2018-2020 and Research Organization for Agriculture and Food, National Research and Innovation Agency under the project of Research Program of Superior Crops Varieties year 2022-2023\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllen GC, Flores-Vergara MA, Krasynanski S, et al (2006) A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide. Nat Protoc 1:2320\u0026ndash;2325. https://doi.org/10.1038/nprot.2006.384\u003c/li\u003e\n\u003cli\u003eAndo K, Carr KM, Colle M, et al (2015) Exocarp properties and transcriptomic analysis of cucumber (Cucumis sativus) fruit expressing age-related resistance to Phytophthora capsici. 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Theoretical and Applied Genetics 108:1151\u0026ndash;1161. https://doi.org/10.1007/s00122-003-1533-4\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Carrasco Y, Gaspari A, Graziani G, et al (2018) Fast analysis of polyphenols and alkaloids in cocoa-based products by ultra-high performance liquid chromatography and Orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap-MS/MS). Food Research International 111:229\u0026ndash;236. https://doi.org/10.1016/j.foodres.2018.05.032\u003c/li\u003e\n\u003cli\u003eSari IA, Murti RH, Misnawi, et al (2022) Sensory profiles of cocoa genotypes in Indonesia. Biodiversitas 23:648\u0026ndash;654. https://doi.org/10.13057/biodiv/d230205\u003c/li\u003e\n\u003cli\u003eShilpashree N, Devi SN, Manjunathagowda DC, et al (2021) Morphological characterization, variability and diversity among vegetable soybean (Glycine max L.) genotypes. Plants 10:671\u003c/li\u003e\n\u003cli\u003eSilva GS, de Santana Souza J, de Souza Junior JO, et al (2023) Mass Selection of Drought Tolerant Cacao in Bahia, Brazil: Morphological, Genetic Structure, and Diversity Analysis. Trop Plant Biol 16:53\u0026ndash;66. https://doi.org/10.1007/s12042-023-09330-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cocoa bean quality, controlled hybridizations, genetic variation, molecular characterization, SSR markers","lastPublishedDoi":"10.21203/rs.3.rs-4766155/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4766155/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCacao stands as a vital export commodity, necessitating consistent high-quality cocoa beans to meet market demands. Controlled hybridizations for genetic enhancement offer a pathway to improve bean quality and to increase genetic variation. We elucidated the phenotypic variation of pod characteristics in F\u003csub\u003e1\u003c/sub\u003e progenies generated from four distinct cross combinations and its molecular characterization. Phenotypic analysis revealed notable outcomes within progenies of TSH858xDR1 cross, demonstrating high average pod weight and a beans-per-100g count aligning with grades AA/A. Among these progenies, 5\u0026thinsp;\u0026minus;\u0026thinsp;1 (2), showcased several advantageous traits including the highest weight of a single dried bean and the lowest pod index reflecting large bean sizes. Molecular characterization revealed that all the F\u003csub\u003e1\u003c/sub\u003e progenies were different from each other, confirming the differences in phenotypic traits were strongly influenced by genetic variation. These findings underscore the efficacy of intentional crosses which are crucial for genetic improvement.\u003c/p\u003e","manuscriptTitle":"Improvement of Cacao Pod Characteristics and its Molecular Characterization in 4 F1 Cacao Populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-22 04:40:09","doi":"10.21203/rs.3.rs-4766155/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02723e05-c6bb-4536-a6cb-dc41f9839c62","owner":[],"postedDate":"August 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-04T06:54:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-22 04:40:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4766155","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4766155","identity":"rs-4766155","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}