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Biochemical and Yield Component of Hybrid Chili (Capsicum annuum L.) Resulting from Full Diallel Crosses

Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Jl, Meranti, IPB Dramaga Campus, Bogor 16680, Indonesia
Center for Tropical Horticulture Studies, IPB University, Jl, Raya Padjajaran, IPB Baranangsiang Campus, Bogor 16129, Indonesia
Department of Biochemistry, Faculty of Mathematics and Natural Sciences, IPB University, Jl, Agatis, IPB Dramaga Campus, Bogor 16680, Indonesia
Tropical Biopharmaca Research Center, IPB University, Jl, Taman Kencana, IPB Taman Kencana Campus, Bogor 16128, Indonesia
Study Program of Agrotechnology, Faculty of Industrial Technology, Gunadarma University, Jl, Margonda Raya, Depok 16451, Indonesia
Study Program of Agrotechnology, Faculty of Agriculture, Siliwangi University, Jl, Peta, Tasikmalaya 46196, Indonesia
Vocational School of Sciences, IPB University, Jl, Kumbang, Bogor 16128, Indonesia
Research Center for Genetic Engineering, Research Organization for Life Science and Environment, National Research and Inovation Agency, Jl, Raya Jakarta-Bogor, Cibinong 16915, Indonesia
Authors to whom correspondence should be addressed.
Horticulturae 2023, 9(6), 620;
Received: 1 May 2023 / Revised: 12 May 2023 / Accepted: 23 May 2023 / Published: 25 May 2023


Chili (Capsicum annuum), economically important, is one of the world’s most popular horticultural plants. Functional biochemical components, such as polyphenol content, antioxidants, and α-glucosidase inhibitory properties, are found in chili. The purpose of this study was to evaluate a chili hybrid that resulted through full diallel crosses for its yield components, total phenolic (TPC) and flavonoid content (TFC), antioxidants, and α-glucosidase inhibitory (AGI) activities. The Folin-Ciocalteu and AlCl3-colorimetric assays were, respectively, used for TPC and TFC analyses. Using 2,2-diphenyl-1-picrylhydrazy (DPPH) and ferric reducing antioxidant power assay (FRAP) techniques, the antioxidant activity of a sample was determined. The bioassay of α-glucosidase inhibition was used to evaluate the antidiabetic activity of the sample. The twenty-five genotypes (hybrid and parent) have diverse yield components and biochemical contents. The highest fruit weight per plant was found in IPB074005 (1008.85 g). IPB114367 showed a high AGI (80.25%), antioxidant FRAP (43.42 µmol TE g−1 DW), TFC (3.97 mg QE g−1 DW), and TPC (37.51 mg GAE g−1 DW). These findings suggested that hybrid plants that suppress α-glycosidase and oxidative stress may prevent diabetes and its complications. This vital information could help design replacement drugs and diabetes diets.

1. Introduction

Over time, global challenges lead to increasingly fierce competition. In 2020, the world experienced the era of the corona virus disease pandemic which caused a change in the paradigm of life [1]. Lock-down regulations and policies in various countries have caused an increase in the world’s population. Population increase is a problem associated with world food consumption. The increasing population during the COVID pandemic era has made food consumption and food security an important concern [2]. In addition, food sufficiency accompanied by health-promoting functional compounds is needed in the current pandemic era. Food needs come from various types of plants, where one type of plant that is in great demand to fulfill food comes from the horticulture group.
Chilies are a section of horticultural plants that have the greatest consumer preferences and economic value [3]. They belong to the Solanaceae family and the capsicum genus, which has a total of more than 35 identified species [4]. However, only five of these species: Capsicum annuum L., C. frutescens, C. baccatum, C. pubescens, and C. chinense, are commonly distributed and cultivated throughout the world. The species that is commonly cultivated and widespread on the Asian continent is C. annuum L. [5]. Chili is reported to be one of the contributing factors to inflation in various countries, especially Indonesia [6]. The majority of the Indonesian population uses chilies for fresh consumption and raw materials for processed spicy foods called sambals [7], made into dry powder [8], and several chili varieties are reported to be used as ornamental plants [9,10]. Variations in the utilization of chilies depend on the type and variety of chilies used.
The selection of varieties plays an important role in sufficient food consumption and maintaining food security. Required varieties that have high productivity are cultivated. In addition to high productivity, chilies have a variety of functional metabolites that are good for human health. Chili has a major compound, namely, capsaicin, that makes it spicy [7]. Recent research reports that chili peppers have other functional compounds including: total phenolic content [11], carotenoids [12], terpenoids [13], total flavonoids [14], antioxidant activity [15], and α-glucosidase inhibitory (AGI) activities [16]. α-glucosidase inhibition has an important role in helping patients with type 2 diabetes mellitus [17]. Interestingly, ornamental chilies in our previous study had relatively high levels of AGI compounds [9].
The potential of chili’s functional metabolite compounds is an opportunity to create new varieties. Chili is classified as a self-pollinating/autogamy plant [18] when it is cultivated in a controlled environment in a greenhouse. However, naturally occurring chili plants can become cross-pollinated/allogamous plants (more than 85%) due to many environmental factors (i.e., assisted by insects/entomophiles, assisted by birds/ornithophiles, assisted by wind/anemophilic).
New varieties were developed from hybridization processes by plant breeders by utilizing the allogamy properties of chili plants. Hybridization aims to produce chili hybrid varieties by utilizing the heterosis phenomenon [19]. The phenomenon of heterosis occurs where the performance of the hybrid is greater than the parents used. This is due to a combination of superior traits that are inherited dominantly [20]. We use the heterosis phenomenon in this study to produce chili hybrids that have high metabolite compounds. Therefore, this study aims to evaluate polyphenolic compounds, antioxidant activity, and α-glucosidase inhibitory activities of chili hybrids. In addition, evaluation of the yield component was also carried out in this study to support metabolites data. Furthermore, the results of this study can become information for the development of hybrid varieties that have high functional compounds so that they can be further utilized by industry, agronomists, pharmaceuticals, and plant breeders.

2. Materials and Methods

2.1. Plant Genetic Material

The plant genetic material used in our study was the parent and hybrid genotypes resulting from full diallel crosses. The five parent genotypes used were: IPB C5, IPB 074, IPB 11.145174, ARISA IPB, and NAZLA IPB. These five genotypes were the result of selection from our previous research which was part of the collection of the Plant Breeding Education Laboratory, Department of Agronomy and Horticulture, IPB University. Using full diallel crosses, 20 hybrids and their reciprocals were produced from the combination of crosses which can be seen in Table 1 and the representative plants can be seen in Figure 1.

2.2. Field Experimental

2.2.1. Field Procedure

All field planting procedures were carried out at Alam Sinarsari greenhouse (−6.5847285, 106.7324342) using a single factor randomized complete block design (RCBD). We used 25 plant genotypes with ten sample plants and repeated observations three times. Seeds were sown separately in a hole seedling tray using two seeds in each hole. Treatment in the nursery was done by sprinkling with water every morning and evening for 10 consecutive days. After shoots appeared (11th–14th day), watering was performed once a day in the morning only. Entering the 14th to the 25th day, fertilization was carried out using AB Mix Platinum (2 mL L−1). Chili plants on day 26 were transferred into 30 cm pots and we adjusted the distance between the pots to 20 cm. All watering and fertilizing activities after transplanting were carried out using a drip irrigation system in the greenhouse. Fertilizing twice a week and watering every day was performed automatically using a timer and we always calibrated it so that each plant received 250 mL of water and fertilizer.
Control of diseases and pests was achieved by spraying pesticides regularly every 2 weeks using an insecticide with the active ingredient Abamectin (2 mL L−1). Insecticide spraying was performed based on the plants’ requirements. We increased spraying intensity to once every three days when severe pest attacks affected the chilies’ growth until conditions were under control. Harvesting started in the 8th week after seeding by choosing perfectly ripe red chilies. In general, chilies can be harvested up to twelve times. However, in this study, we harvested eight times. We carried out biochemical measurements using ripe chilies from the third to fifth harvest.

2.2.2. Field Observation

The data obtained from field observations are the yield component, namely: fruit length, fruit diameter, fruit weight, number of fruits per plant, and fruit weight per plant. Our observations refer to the descriptor for capsicum [21]. We measured 10 sample plants for each replicate. We measured fruit weight using digital analytics. Fruit diameter and length were measured using digital calipers and rulers. The number of fruits per plant was calculated from the first to the peak harvest (eight times).

2.3. Biochemical Experimental

2.3.1. Sample Preparation

All sample preparations use 70% ethanol on chilies previously made into powder [9,15]. Harvested ripe fresh chilies were baked in the oven for 48 h at 40 °C. After drying, they were crushed into powder using a blender of up to 10 mesh sizes. Chili powder was dissolved in 70% ethanol with a ratio of 1:20 (1 g chili powder in 20 mL 70% ethanol) and shaken for 72 h in a dark room. After 72 h, it was filtered using filter paper and transferred to a 50 mL vial. The solution was incubated in the refrigerator for 48 h before being used for biochemical analysis.

2.3.2. Total Phenolic Content (TPC)

TPC measurement was performed using gallic acid standard. The chemicals used consist of Folin-Ciocalteu and Na2CO3. The prepared sample was injected in 20 μL quantities onto the microplate and mixed with 100 μL Folin-Ciocalteu 10%, which we previously dissolved in distilled water. The mixture was allowed to stand for 5 min, and then 80 μL of 7.5% Na2CO3 solution (w/v in distilled water) was added. Finally, incubation was carried out in a dark room for 120 min. After incubation, the absorbance was measured using an ELISA reader at a wavelength of 750 nm. The resultant was analyzed and converted to mg GAE (gallic acid equivalent) g−1 DW units.

2.3.3. Total Flavonoid Content (TFC)

Quercetin standards with different concentration levels (25 ppm, 50 ppm, 75 ppm, 100 ppm, 150 ppm, and 200 ppm) were used to measure TFC. The prepared sample was injected in 10 μL quantities onto a flat microplate mixed with 60 μL methanol, 10 μL AlCl3 10% (in methanol), 10 μL CH3COOK 1M (in methanol), and 110 μL distilled water and incubated in the dark for 30 min. After the incubation process, the absorbance of the sample was measured using an ELISA reader at a wavelength of 415 nm. The resulting absorbent was analyzed and converted to mg QE (quercetin equivalent) g−1 DW units.

2.3.4. Antioxidant Activity DPPH and FRAP Methods (DPPH and FRAP)

Measurement of antioxidant activity was performed using two different methods, where both were used to determine the antioxidant activity of samples using the same control solution named Trolox. The DPPH method was used by mixing 100 μL each of 125 μM 2,2-diphenyl-1-picrylhydrazyl solution (in ethanol) and the prepared sample. The mixed solution was incubated for 30 min in a dark room, and then the absorbance was measured at a wavelength of 517 nm. Meanwhile, the FRAP method was carried out by mixing 10 μL with 300 μL of FRAP reagent made from acetate buffer (pH 3.6), 1 mM TPTZ (in 40 mM HCl), and 20 mM FeCl3 (in Aquadest) with a ratio of 10:1:1. The mixed solution was incubated for 30 min in an oven at 37 °C. Then the absorbance was measured at a wavelength of 595 nm. The resulting absorbance was analyzed and converted to mg TE (Trolox equivalent) g−1 DW units.

2.3.5. α-Glucosidase Inhibition (AGI)

AGI was measured by comparing the control (acarbose) with the prepared sample. Previously prepared samples were evaporated to a paste, then redissolved using DMSO. After repreparation was completed, 10 μL of the sample was taken and mixed with 50 μL of 0.1 M phosphate buffer (pH 7), 25 μL of α-glucosidase 0.04 U mL−1, and 25 μL of p-nitrophenyl-α-D glucopyranoside 0.5 mM. We always added a control buffer without enzymes. The mixed solution was incubated for 30 min in the oven at 37 °C. The reaction was stopped with 100 µL of 0.2 M Na2CO3 at 31 min. Absorbance measurements were carried out at a wavelength of 410 nm. The absorbance results were converted using the inhibition activity percent formula.

2.4. Data Analysis

The data we obtained were compiled and analyzed using the F test at a 5% level. Results that were significantly different were continued with the Duncan multiple range test and contrast orthogonal analysis using SAS On Demand for Academics Research ( (accessed on 20 April 2023) and revalidated using Statistical Analysis for Agricultural (STAR v 2.0.1) software. Clustering analysis of the HCA method was also carried out by utilizing the data obtained to determine the grouping of hybrids and parents using the R Studio program ( (accessed on 20 April 2023) package “heatmaply”. The R Color Brewer package assists with color visualization. Correlation analysis used the same software as the “corrplot.mixed” package.

3. Results

The analysis of variance that we carried out aims to determine the effect of genotypes and replicates on the observed variables. All yield components (Table 2) and biochemical variables (Table 3) showed highly significant significances (p < 0.01) for genotype sources. The replication sources of the yield component were not significant, as shown by the observation of FW, FD, NFP, and FWP. Meanwhile, TFC and DPPH showed no significant biochemical parameters. FL and FRAP replication sources differed significantly (p < 0.05). The coefficient of variance of the biochemical parameters was low (<5%), ranging from 1.19% for the observation of DPPH to 3.26% for FRAP. The yield components’ variance coefficients were higher than the biochemical parameters, ranging from 3.36% for FD to 11.64% for FW.
The performance of the hybrid and parent yield components is shown in Table 4. The hybrid fruit length was measured at an interval of 3.37–12.94 cm. Meanwhile, parent fruit length was measured at 3.30 (NAZLA IPB) to 14.07 cm (IPB 074). The combination of diallel and reciprocal crosses between NAZLA IPB and IPB 074 produced the same fruit length of 6.33 cm. Based on the DMRT test, this hybrid was not significantly different from its parent ARISA IPB and hybrid IPB005367. The most extended fruit length of the hybrids in this study was shown by IPB005074, which was significantly different from all parent hybrids. Meanwhile, the reciprocal (IPB074005) produces shorter fruit lengths.
The ARISA IPB parent showed the thickest FD, and the DMRT test results showed a significant difference with all parent and hybrid genotypes. The smallest hybrid chili FD was shown as IPB074114 (7.41 mm). This hybrid was produced from one of the parents with the most minor fruit diameter (5.95 mm) indicated by the IPB 11.145174 genotype. The hybrid FD range produced in our study was 7.41–20.01 mm. The highest hybrid genotype FD was shown by IPB074005, where the DMRT test was not significantly different from the reciprocal of IPB005074 but significantly different from all other hybrids.
The main chili yield component is determined by three observation variables: FW, NFP, and FWP. The IPB114367 hybrid we measured had the lowest fruit weight (2.54 g) compared to all other hybrids. Statistically, the fruit weight of IPB114367 was only significantly different from the other six hybrids. IPB074005 had the highest fruit weight in this study (13.62 g), which was not significantly different from its reciprocal crosses IPB005074, IPB005374, and parent IPB C5. The lowest parent fruit weights were shown by NAZLA IPB and IPB 11.145174, which were not statistically significantly different. The parent with the highest fruit weight is ARISA IPB, followed by IPB C5 and IPB 074. The fruit weights of the three parents were statistically significantly different.
The parent NFP of large chilies and cayenne peppers showed different DMRT test results. IPB 11.145174 is the parent that has the most NFP (92.00 fruits) and is significantly different from the other parents—the most NFPs after IPB 11.145174 were NAZLA IPB, IPB 074, IPB C5, and ARISA IPB. The NFP between IPB 074 and IPB C5 was statistically insignificant. Uniquely, the hybrid resulting from a cross between ARISA IPB and IPB 11.145174 produced the highest NFP (99.67 fruits) of the resulting hybrids and the parents used and was significantly different.
The hybrid FWP in this study was 106.07–1008.85 g, and the parent FWP showed a range of 156.76 (IPB 11.145174)–946.11 g (ARISA IPB). ARISA IPB fruit weight differed significantly from all parent genotypes except the IPB C5 genotype. The IPB074005 hybrid had the highest fruit weight per plant and was significantly different from all hybrid and parent genotypes. The combination of crosses and reciprocals from the two parents with the highest fruit yields (ARISA IPB and IPB C5) produced hybrids with plant weights of 833.50 g and 879.13 g, which were not statistically significantly different between the two.
The total phenolic content of the hybrid and parent in this study was 16.37–39.07 mg GAE g−1 DW. The highest parent TPC was shown by ARISA IPB, which was not significantly different from NAZLA IPB. Meanwhile, the highest hybrid TPC was shown by IPB114367 (37.51 mg GAE g−1 DW), which was also not significantly different from NAZLA IPB. The lowest hybrid TPC was shown by IPB005114 (16.37 mg GAE g−1 DW) and was not significantly different from hybrids with the same TPC value (17.07 mg GAE g−1 extract) in IPB114374 and IPB374367 genotypes.
The parent TFC in this study was 2.43–4.06 mg QE g−1 DW. Meanwhile, the hybrid TFC from the combination of five parent crosses was 1.36–4.00 mg QE g−1 DW. The highest hybrid TFC was shown by IPB367114, which was not significantly different from the parent NAZLA IPB. This hybrid combined two parents with the highest TFC value and was significantly different from all other hybrids.
The highest FRAP as a whole was shown by the parent NAZLA IPB, while ARISA IPB showed the highest DPPH parent. Overall (hybrid and parent), the highest DPPH was shown by IPB367005 of 2.01 µmol TE g−1 DW and was statistically significantly different across all genotypes. The IPB367114 genotype indicated the hybrid with the highest FRAP.
The highest hybrid AGI activity reaching 80.25% inhibition was shown by IPB114367, which was not significantly different from its reciprocal and parent NAZLA IPB. AGI in this study was relatively high, reaching 46.54% to 81.22%. The highest to lowest parent AGI values were NAZLA IPB, IPB 11.145174, IPB C5, ARISA IPB, and IPB 074. The reciprocal AGI hybrid had almost similar ranges of values and was not significantly different.
The results of the hierarchical cluster analysis between the genotypes and observed variables are shown in Figure 2. The observed genotypes and characters were divided into three major groups. Group one for the observed characteristics consisted of TPC, TFC, FRAP, FW, FD, FWP, and FL. Group two was filled only by NFP characteristics. In contrast, the third group consisted of DPPH and AGI. Clustering performed on the genotypes separated ARISA IPB into a separate-group. Meanwhile, the second group was filled with four genotypes consisting of two parents (NAZLA IPB and IPB 11.145174) and the resulting cross-combination hybrids (IPB114367 and IPB367114).
Figure 3 was a Pearson correlation between biochemical variables (TPC, TFC, DPPH, FRAP, and AGI) and yield components (FL, FD, FW, NFP, and FWP). AGI positively correlated with DPPH (r2 value = 0.09) but negatively correlated with TPC and FRAP (r2 values = –0.05 and −0.17). A negative correlation occurs between AGI and all yield component variables. Positive and significantly different correlations were shown between FRAP and TFC (p < 0.001; r2 value = 0.81), FRAP and TPC (p < 0.001; r2 value = 0.41), and TFC and TPC (p < 0.001; r2 value = 0.58). The correlation between antioxidant activity with different methods (DPPH and FRAP) was negative (r2 value = −0.51). The highest significant positive correlation was shown by FD-FW (r2 value = 0.98). Meanwhile, the lowest significant negative correlation was shown by AGI-FWP (r2 value = −0.56).

4. Discussion

Genetic improvement through hybridization activities produces very useful hybrids for human life. The use of hybrid varieties has been extensively studied on various types of plants ranging from food crops [22,23,24], fruit crops [25,26], vegetable crops [27,28], and even perennial plantation crops [29,30]. Hybrid plants are used to produce fast production, increase quality, and produce many fresh products. Fast production is done by looking at the age of flowering and harvesting plants, which initially took a long time to become faster [22,23,24,25,26,27,28,29,30]. In addition, it is also related to the quality and quantity of the results obtained.
Chili pepper has a capsaicin compound as the primary compound, producing different spiciness levels between varieties [31]. Capsaicin belongs to the group of metabolites of the vanillyl amides class, which collect in the chili placenta from fruit formation to ripening [31,32]. In addition to capsaicin, chili produces other functional secondary metabolites that can be developed industrially as functional foods, cosmetics, and pharmaceuticals [33]. Capsaicin is associated with beneficial biological effects in humans, including antioxidant activity [34,35,36], polyphenolic compounds [37,38], and even alpha-glucosidase inhibitory activity [35]. C. annuum L. species are reported to contain capsiate which can increase triglyceride accumulation, hepatic insulin sensitivity, and glycogen storage [39].
In addition, the development of chili hybrids with highly functional biochemical compounds provides added value to varieties with high productivity. Hybrid improvement aims to combine various information on the superior properties of the parents. In this study, we evaluated the performance of five parents and 20 hybrids and their reciprocals resulting from the combination of five parent crosses regarding polyphenol content, antioxidant activity, AGI, and their yield component.
Phenolic compounds are generally polyphenols which form glycoside compounds from tannins, coumarins, cinnamic acid derivatives, lignin, and polyfunctional organic acids [40]. One part of the phenolic compound that has a molecular weight is flavonoids. Flavonoids are the most prominent family of plant polyphenols, and more than 6000 species have been identified [38,41]. Both of these compounds were classified as secondary metabolites, increasing when plant conditions were increasingly stressed. Polyphenol content in chili plants can be found without any environmental stress. The results of this study (Table 5) showed that parent and hybrid chilies contain polyphenol compounds and were grown in a controlled environment in a greenhouse. Polyphenol contents in peppers were been reported in other studies [14,38], which indicated that the potential for polyphenols in hybrids is more significant than in this study. It was reported in previous studies that there is a correlation between capsaicin and polyphenol content [37]. These compounds are spread throughout all parts of the plant as protectors against biotic and abiotic stresses [42]. Polyphenol content in plants is helpful for self-protection mechanisms, so if chilies contain these compounds, it is hoped that they will help the human body’s mechanisms for self-protection. Further medical research is needed regarding the effects of polyphenol content on human self-protection mechanisms.
The human body is made up of a wide variety of complex compounds. Excessive oxidation through burning excess fat causes the body to react and produce free radical compounds [43]. Free radicals are molecules consisting of unpaired electrons such as hydroxyl (OH-), peroxyl (RO2), superoxide (O2), and hydroperoxyl (HO2) [44]. These compounds cause oxidation reactions that cause degenerative diseases that damage cell wall membranes, blood vessels, and lipid tissues [45]. To overcome this, the body naturally produces antioxidant compounds in small quantities. Thus, it is necessary to take in antioxidants from outside the body, which are contained in many types of vegetables and fruit [46]. This study used two methods for measuring antioxidant activity: DPPH and FRAP. The results shown in this study (Table 5) show that DPPH antioxidants were lower than FRAP antioxidants, in line with [47], who reported higher FRAP antioxidant activity than DPPH. Unstable reagents are the main factor affecting the low DPPH results. DPPH reagents have severe damage sensitivity when exposed to oxygen, temperature, and light [48].
In addition to the above compounds, chili peppers were previously reported to have α-glucosidase inhibitor compounds [49,50]. α-glucosidase inhibitors are a hope for the treatment of type II diabetes mellitus. This type is caused by eating patterns that are not controlled so that the accumulation of sugar in the blood increases. One alternative to prevent this disease is to regulate delays in glucose absorption by inhibiting the activity of the α-glucosidase enzyme [51]. To delay glucose absorption into the blood, synthetic α-glucosidase inhibitors, including acarbose, miglitol, and voglibose, were used [51,52]. The results obtained from synthetics are good but have adverse side effects. Therefore, α-glucosidase inhibitor compounds are needed from bioactive peptides, which are proven to have low side effects. Compared to acarbose, chili consumption may be used to prevent type II diabetes. Our results showed that the measured α-glucosidase inhibitors were higher (above 50%) than acarbose. However, more profound research and development are needed on the mechanism of α-glucosidase inhibitors in chili plants.
In contrast to functional compounds, chili productivity is also one of the critical factors in developing varieties. Chili genotypes that have high functional compounds become less valuable if their productivity is low. Our study’s results indicate that several genotypes have high productivity (Table 4) but also have high functional compounds (Table 5). The optimum productivity potential for chili is 20 ton ha−1, where this figure can be produced if chili plants can produce a fruit weight of 800–1000 g per plant [53]. Our study also showed that the polyphenolic compounds and antioxidants of FRAP were grouped with yield components. We also analyzed the Pearson correlation to obtain the relationship between biochemical compounds and yield components. Improvement in future research conducted molecularly is expected to be more accurate in validating the linkage of yield component genes with polyphenol and pharmacological compounds.

5. Conclusions

Developing chili hybrid varieties aimed at functional food is challenging and an excellent opportunity. We conclude that crosses of chili peppers with high and low functional compounds and yield components could produce hybrids with moderate values for both. Hybrid candidates with high AGI (69.18%), TFC (3.97 mg QE g−1 DW), TPC (37.51 mg GAE g−1 DW), and FRAP (33.55 mg TE g−1 DW) extracts (IPB114367) could be developed for pharmaceutical development. The AGI and DPPH activities in hybrids were higher than in the parents. IPB074005 was the hybrid with the highest production balanced with the presence of highly functional biochemical compounds. AGI in this study was closely related to DPPH, where both were positively correlated. Meanwhile, the polyphenolic compounds and the antioxidant activity of FRAP were closely related to the yield component.

Author Contributions

All authors have made equal contributions to this article. All authors have read and agreed to the published version of the manuscript.


This research was funded by Post-Doctoral Programme IPB University, grant number 3/IT3/SP/WCU/2023.

Data Availability Statement

Not applicable.


All authors would like to thank the Ministry of Research, Technology and Higher Education of the Republic of Indonesia, Centre of Tropical Horticulture Studies IPB, and Institut Pertanian Bogor (IPB University).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.


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Figure 1. Representative hybrid genotypes.
Figure 1. Representative hybrid genotypes.
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Figure 2. Hierarchical cluster analysis of chili biochemical and yield component. FL—fruit length, FD—fruit diameter, FW—fruit weight, NFP—number of fruit per plant, FWP—fruit weight per plant, TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition.
Figure 2. Hierarchical cluster analysis of chili biochemical and yield component. FL—fruit length, FD—fruit diameter, FW—fruit weight, NFP—number of fruit per plant, FWP—fruit weight per plant, TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition.
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Figure 3. Pearson correlation visualization. FL—fruit length, FD—fruit diameter, FW—fruit weight, NFP—number of fruit per plant, FWP—fruit weight per plant, TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition.
Figure 3. Pearson correlation visualization. FL—fruit length, FD—fruit diameter, FW—fruit weight, NFP—number of fruit per plant, FWP—fruit weight per plant, TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition.
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Table 1. Chili hybrid and reciprocal genotype.
Table 1. Chili hybrid and reciprocal genotype.
IPB C5IPB 11.145174IPB005114
IPB C5IPB 074IPB005074
ARISA IPBIPB 11.145174IPB374114
NAZLA IPBIPB 11.145174IPB367114
IPB 11.145174IPB C5IPB114005
IPB 11.145174ARISAIPBIPB114374
IPB 11.145174NAZLA IPBIPB114367
IPB 11.145174IPB 074IPB114074
IPB 074IPB C5IPB074005
IPB 074IPB 11.145174IPB074114
Table 2. ANOVA of yield component.
Table 2. ANOVA of yield component.
SourcesMean Square
Genotype27.86 **1498.52 **540.15 **1284.50 **268,976.65 **
Replication0.257 *1.45 ns0.228 ns1.61 ns1088.35 ns
Coefficient of Variance (%)4.1211.643.364.926.89
**—significant at p < 0.01, *—significant at p < 0.05, ns—non-significant, FL—fruit length, FW—fruit weight, FD—fruit diameter, NFP—number of fruit per plant, FWP—fruit weight per plant.
Table 3. ANOVA of biochemical compound.
Table 3. ANOVA of biochemical compound.
SourcesMean Square
Genotype213.84 **1.97 **0.08 **235.80 **302.05 **
Replication4.90 **0.01 ns0.002 ns3.07 *38.40 **
Coefficient of Variance (%)
**—significant at p < 0.01, *—significant at p < 0.05, ns—non-significant, TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition.
Table 4. Means performance of chili hybrid and parent of yield component.
Table 4. Means performance of chili hybrid and parent of yield component.
GenotypeFL (cm)FD (mm)FW (g)NFPFWP (g)
IPB00537412.94 b17.09 d12.93 bc68.00 hi833.50 d
IPB0053675.83 h11.98 fg4.84 f79.00 def382.50 g
IPB0051145.07 i9.53 jk2.81 fg84.33 cd337.05 ghi
IPB00507410.10 d19.26 c13.24 bc68.00 hi900.20 bc
IPB37400510.70 c15.87 e11.42 cd67.00 hi879.13 cd
IPB3743677.53 f8.56 l3.17 fg49.67 k251.23 j
IPB3741148.57 e9.72 j2.95 fg99.67 a293.71 ij
IPB37407411.10 c10.34 ij7.23 e72.67 gh524.94 f
IPB3670054.53 j11.68 gh3.23 fg77.33 efg349.49 ghi
IPB3673747.07 f9.90 j3.91 fg49.67 k251.85 j
IPB3671143.57 k8.73 kl2.64 fg39.00 l110.19 l
IPB3670746.33 gh8.74 kl3.81 fg82.00 cde312.29 hi
IPB1140057.30 f10.98 hi2.88 fg84.67 cd351.80 gh
IPB1143748.33 e9.49 jk3.16 fg98.67 a297.04 hij
IPB1143673.37 k8.18 lm2.54 fg41.67 l106.07 l
IPB1140747.07 f9.98 j3.53 fg40.67 l133.96 kl
IPB07400510.67 c20.01 c13.62 b74.00 fg1008.85 a
IPB07437411.03 c12.70 f7.62 e75.67 fg593.58 e
IPB0743676.33 gh8.57 l3.60 fg82.33 cde296.90 hij
IPB0741148.10 e7.41 m3.72 fg36.33 l135.18 kl
ARISA IPB6.47 g25.3 2 a15.68 a22.33 m946.11 b
IPB 11.1451743.63 k5.95 n1.63 g92.00 b156.76 kl
IPB C510.70 c22.81 b14.00 b58.33 j906.86 bc
NAZLA IPB3.30 k9.89 j2.13 g86.00 c182.92 k
IPB 07414.07 a11.12 hi9.93 d62.67 ij619.40 e
Parent’s Mean7.6325.0228.6864.27562.41
Hybrid’s Mean7.7811.445.6468.52417.47
Hybrid vs. Parent********ns
FL—fruit length, FD—fruit diameter, FW—fruit weight, NFP—number of fruit per plant, FWP—fruit weight per plant. Means followed by the same letter are not significantly different by the DMRT test at 5% probability, **—significant for contrast orthogonal analysis, ns—non-significant for contrast orthogonal analysis.
Table 5. Means performance of chili hybrid and parent of biochemical compound.
Table 5. Means performance of chili hybrid and parent of biochemical compound.
GenotypeTPC (mg GAE g−1 DW))TFC (mg QE g−1 DW)DPPH (µmol TE g−1 DW)FRAP (µmol TE g−1 DW)AGI (%)
IPB00537419.30 k2.01 gh1.60 i30.70 ij57.47 k
IPB00536720.82 j1.70 j1.95 b30.39 j72.46 d
IPB00511416.37 l2.14 g1.81 de32.64 hi69.65 e
IPB00507431.59 g2.81 c1.87 c39.61 def46.54 l
IPB37400518.96 k2.03 gh1.60 i31.91 hij57.91 k
IPB37436717.07 l1.36 l1.89 c19.36 kl78.75 b
IPB37411417.38 l2.12 g1.59 i40.21 de64.83 h
IPB37407432.69 g2.29 f1.75 fg31.00 ij63.97 hi
IPB36700521.38 j1.59 jk2.01 a31.73 hij73.45 cd
IPB36737419.07 k1.37 l1.90 c18.33 l79.07 b
IPB36711436.81 cd4.00 a1.50 j45.18 bc79.03 b
IPB36707436.71 cd1.57 k1.87 c20.76 k68.83 ef
IPB11400517.21 l2.03 gh1.74 g33.55 gh69.18 e
IPB11437417.07 l1.83 i1.52 j33.73 gh66.89 g
IPB11436737.51 bc3.97 a1.44 k43.42 c80.25 ab
IPB11407429.87 h1.90 hi1.94 b33.36 gh62.89 i
IPB07400532.96 fg2.86 c1.78 ef38.64 ef48.30 l
IPB07437434.94 e2.14 g1.68 h33.24 h64.37 hi
IPB07436735.66 de1.52 k1.83 d17.97 l67.32 fg
IPB07411434.39 ef1.96 h1.88 c35.30 g61.07 j
ARISA IPB39.07 a2.83 c1.51 j52.15 a56.66 k
IPB 11.14517433.00 fg3.52 b1.60 i46.88 b74.62 c
IPB C535.62 de2.43 e1.76 fg40.70 d64.63 hi
NAZLA IPB38.69 ab4.06 a1.95 b43.55 c81.22 a
IPB 07427.38 i2.56 d1.70 h38.09 f48.28 l
Parent’s mean34.753.081.7144.2765.08
Hybrid’s mean26.392.161.7632.0566.61
Hybrid vs. Parent**********
TPC—total phenolic content, TFC—total flavonoid content, DPPH—antioxidant DPPH method, FRAP—antioxidant FRAP method, AGI—α-glucosidase inhibition. Means followed by the same letter are not significantly different by the DMRT test at 5% probability, **—significant for contrast orthogonal analysis, ns—non-significant for contrast orthogonal analysis.
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Syukur, M.; Maharijaya, A.; Nurcholis, W.; Ritonga, A.W.; Istiqlal, M.R.A.; Hakim, A.; Sulassih, S.; Perdani, A.Y.; Pangestu, A.Y.; Hatta, A.N.N.L.; et al. Biochemical and Yield Component of Hybrid Chili (Capsicum annuum L.) Resulting from Full Diallel Crosses. Horticulturae 2023, 9, 620.

AMA Style

Syukur M, Maharijaya A, Nurcholis W, Ritonga AW, Istiqlal MRA, Hakim A, Sulassih S, Perdani AY, Pangestu AY, Hatta ANNL, et al. Biochemical and Yield Component of Hybrid Chili (Capsicum annuum L.) Resulting from Full Diallel Crosses. Horticulturae. 2023; 9(6):620.

Chicago/Turabian Style

Syukur, Muhamad, Awang Maharijaya, Waras Nurcholis, Arya Widura Ritonga, Muhammad Ridha Alfarabi Istiqlal, Abdul Hakim, Sulassih Sulassih, Ambar Yuswi Perdani, Arya Yuda Pangestu, Andi Nadia Nurul Lathifa Hatta, and et al. 2023. "Biochemical and Yield Component of Hybrid Chili (Capsicum annuum L.) Resulting from Full Diallel Crosses" Horticulturae 9, no. 6: 620.

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