The iaa9-3 (TOMPJE2811) and iaa9-5 (TOMJPG0114-1) mutants were isolated and characterised from a mutant population based on MT cultivars (Saito et al., 2011). These mutants and WT-MT as control were cultivated in the greenhouse of the experimental field of the Laboratory of Horticulture, Faculty of Agriculture, Universitas Padjadjaran, with four biological replications; each replication consisted of six individual plants for vegetative analysis. The iaa9-3 and iaa9-5 mutants and WT-MT seeds were sown in plug trays, in accordance with the methods described by Rahmat et al. (2023). After the seedling produced 4–5 leaves, they were transplanted into a 12 cm-diameter pot that was filled with a mixture of soil and commercial coir coco peat (1:1/v:v) and cultivated in two greenhouse conditions, i.e. heat-stress (40 °C/45 °C) and control (30 °C/35 °C) conditions. The heat stress condition was treated for the whole lifespan of the plant, starting from transplanting until the fruit harvest. During the cultivation periods, the plants were fertigated with a commercial nutrient solution with an electrical conductivity (EC) level of 2.0–2.5 dS m⁻¹.

The agronomic features related to plant growth and yield were evaluated. For plant growth, plant canopy diameter that measured as the method described by Iizuka et al. (2017) and the number of shoots were evaluated at 8 weeks after sowing. For plant yield, several characteristics were evaluated; these characteristics included flowering time that was the number of days from sowing until 1^st flowering from each plant (Mubarok et al., 2019c), the number flowers per plant, the number of fruits per plant, the rate of fruit set, fruit weight, length and diameter and the number of seeds. The fruit weight per plant was calculated by dividing the total fruit weight by the total fruit number. The total number of flowers and fruits and the rate of fruit set were counted similarly to those in the study by Pham et al. (2020) at 115 days after sowing. Meanwhile, the rate of fruit set was calculated by dividing the total number of fruits by the total number of flowers. The fruit weight, length and diameter and the number of seeds per fruit were obtained from five individual fruits of each plant.

Pollen viability testing was carried out using 2,3,5-triphenyl tetrazolium chloride (TTC) in accordance with the method used by Ezura et al. (2019). TTC staining is an indicator of cellular survival based on the mitochondrial reduction reaction, where the viable pollen will turn red, and the non-viable pollen will be colourless. Pollens were obtained from five individual flowers, soaked in 1% TTC +50% sucrose and shaken for dispersal in the solution. Afterwards, the TTC solution containing the pollens was left in a dark room at 38°C for 3 h for pollen colouration. Then, 2 µg supernatant was collected and placed in the cell counter. The pollens were then observed under a microscope. The criterion for viable pollens was the absorption of red colour from the TTC solution per 1 mm² cell counter.

H₂O₂ concentration was measured following the method used by the Association of Official Analytical Chemists (AOAC) with modifications (Association of Official Analytical Chemists, 1990). A total of 5 g leaf sample was mixed with 5 mL Aqua Bidest using mortar and pestle in an ice bath. Then, 5 mL ground leaf sample mixture was combined with 25 mL sulfuric acid. The mixture was titrated with 0.1 N potassium permanganate. Each 1 mL of potassium permanganate used in titration corresponded to 1.07 mg H₂O₂. Titration was stopped when the sample mixture changed colour. H₂O₂ was calculated using the following formula:

V = Titrate used in titration (mL)

W = Weight of the leaf sample (g)

The H₂O₂ values were then converted from percentage to µmol/g of fresh weight (FW).

Antioxidant activity was analysed following the method used by Sami and Rahimah (2016). A total of 3 g leaf sample was macerated using methanol (99.8%) for 24 h. After 24 h, the mixture was filtrated using filter paper, and the filtrate was thickened utilising a rotary evaporator. The leaf extract solution (1000 ppm) was created by combining 50 mg thickened leaf extract with 50 mL methanol (99.8%). Next, 0.5 mL 0.4 mM 2,2- diphenyl-2-picrylhydrazyl (DPPH) solution was added to a test tube containing 500 µL leaf extract solution (1000 ppm). The test tubes containing the mixture were then incubated in the dark for 30 min at room temperature. After incubation, each sample absorbance was observed using a spectrophotometer (Orion™ AquaMate 8000, Thermo Fisher Scientific, UK) at 516 nm (Mubarok et al., 2019b). A blank solution containing methanol and DPPH only was also prepared. Sample antioxidant activity was measured using the following equation:

The normalities of data distributions were tested using the Kolmogorov–Smirnov test. For statistical data analysis, data were subjected to a two-factor analysis of variance followed by Duncan’s multiple range test at p< 0.05 for comparisons among the investigated data. The data are represented as the mean values ± standard error (SE) of four replicates. All statistical analyses were performed using SPSS 20.0 statistical software.

The response of plant vegetative growth can be observed from the plant appearance, which was characterised by the plant canopy diameter and the number of shoots. Based on statistical data analysis, the plant canopy diameter of WT-MT, iaa9-3 and iaa9-5 mutants were significantly different in either normal temperature or heat-stress conditions ( Figures 1A–C , respectively). High-temperature/heat-stress condition greatly influenced the size of the plant canopy diameter. Under heat-stress conditions, the plant canopy diameter decreased significantly in all plant genotypes compared with plants under normal conditions. The highest reduction in the plant canopy diameter was observed in WT-MT, and it decreased by approximately 41.3% compared with that under normal condition. The plant canopy diameters of iaa9-3 and iaa9-5 decreased by 40.6% and 36.7%, respectively ( Figures 1A, C ).

At both temperatures tested, the plant canopy diameter of WT-MT was larger than those of iaa9-3 and iaa9-5. As shown in Figure 1A , the plant canopy diameter of WT-MT under normal conditions showed the highest diameter, but it was not significantly different from that of iaa9-3. Meanwhile, iaa9-5 had significantly lower values compared with WT-MT and iaa9-3 ( Figure 1A ). The large plant canopy diameter of WT-MT can also be monitored under heat-stress condition, where the plant canopy diameters of iaa9-3 and iaa9-5 were significantly lower than that of WT-MT ( Figure 1A ).

Many lateral shoots caused the large plant canopy diameter of WT-MT. Statistical data analysis showed a significant difference in the number of lateral shoots between WT-MT and iaa9-3 and iaa9-5 under normal and heat-stress conditions. The heat-stress condition significantly inhibited the growth of new lateral shoots in all investigated plant genotypes, which resulted in a low number of lateral shoots under heat-stress conditions. However, no further reduction in lateral shoots was observed in iaa9-3 under heat stress ( Figure 2B ). The decrease in the number of lateral shoots under heat-stress condition was 23.50%, 17.35% and 38.36% lower compared with those under normal conditions for WT-MT, iaa9-3 and iaa9-5, respectively. Under normal and heat-stress conditions, the mutation in the IAA9 gene significantly reduced the number of lateral shoots in iaa9-3 and iaa9-5. In iaa9-3, the number of lateral shoots was 5.75 and 4.25 fewer compared with that in WT-MT under normal and heat-stress conditions, respectively. Iaa9-5 showed 5.25 and 4.45 fewer lateral shoots compared with WT-MT under normal and heat-stress conditions, respectively ( Figures 2A–C ).

Flowering is strongly influenced by internal and external factors. The time of flowering is one of the several indicators of a plant entering the generative phase. The results showed that the flowering time of the three observed tomato genotypes, namely, iaa9-3, iaa9-5 and WT-MT, differed depending on environmental conditions. Under the normal-temperature condition, the mutation in iaa9-3 and iaa9-5 significantly accelerated flowering time by 3 and 6.7 days earlier than WT-MT, respectively ( Figure 3 ). This result was different from that observed under heat-stress condition. Accelerated flowering time was observed in WT-MT, but iaa9-3 and iaa9-5 experienced a delay in flowering time. The mutants behaved as WT under normal condition when subjected to heat stress.

The flower is an important generative organ for fruit formation. Statistical analysis showed a significant difference in the number of flowers among the tested genotypes under normal and heat-stress conditions. WT-MT had 94.5 and 122.5 more flowers in normal and heat-stress conditions, respectively. Meanwhile, iaa9-3 and iaa9-5 had 68.7 and 74.1 flowers under normal conditions and 91.6 and 84.8 flowers under heat-stress conditions, respectively. Raising the ambient temperature to 45°C during the growth period significantly increased the number of flowers on all tested plants. The number of flowers of WT-MT, iaa9-3 and iaa9-5 increased by 29.63%, 33.33% and 14.43%, respectively; under heat stress compared with those under normal condition ( Figure 3 ).

In the microscopic analysis of pollen viability, three groups, namely, viable, semi-viable and non-viable pollens were determined based on pollen viability level. Based on statistical data analysis, under normal conditions, the percentage of viable, semi-viable and non-viable pollens in the three genotypes of investigated plants did not show any significant difference. Among the three levels of the proportion of pollens, the group of viable pollens had the highest percentage compared with the semi-viable and non-viable pollen groups.

This study proved that the decrease in pollen viability occurred under heat-stress conditions. Raising the temperature up to 45°C significantly reduced the level of pollen viability in all investigated genotypes. The decrease in the percentage of viable pollen under heat-stress conditions occurred in WT-MT, where the percentage of viable pollen decreased by almost 87.15% compared with that under normal condition. Mutations in the IAA9 gene can prevent pollen damage under heat-stress condition, as indicated by the percentages of viable pollen in iaa9-3 and iaa9-5, which reached 32.62% and 33.42%, respectively. The percentages decreased by 49.73% and 47.51%, respectively, compared with those under normal condition. The decrease in the number of viable pollens under heat-stress condition was caused by the increase in pollen sterility, which resulted in a very high number of non-viable pollens in WT-MT (67.57%) due to high temperature, and the decreases in iaa9-3 and iaa9-5 reached 32.97% and 32.56%, respectively ( Figure 4B ).

The fruit set is the percentage ratio of the number of fruits and the number of flowers in the same individual plant. Statistical analysis showed that the fruit set in iaa9-3 and iaa9-5 was significantly higher than that in WT-MT under normal and heat-stress conditions ( Figures 5A, B , respectively). Plant capacity to produce fruit also differed between normal and heat-stress conditions, irrespective of genotypes. Under normal conditions, the fruit sets of iaa9-3 and iaa9-5 were 81.24% and 64.89% or 21.57% and 5.22% higher than that of WT-MT, respectively. The percentage of fruit set from all tested plants decreased dramatically under the heat-stress condition at 45°C ( Figure 5C ). Under the heat-stress condition, WT-MT was unable to produce fruits, whereas iaa9-3 and iaa9-5 did. Thus, mutations in the IAA9 gene can increase the percentage of fruit set in iaa9-3 and iaa9-5 compared with WT-MT under heat-stress conditions. Although both mutants can produce fruit sets under heat-stress conditions, the fruit set was lower compared with that in normal conditions. The fruit sets of iaa9-3 and iaa9-5 under heat-stress conditions were 34.98% and 32.84% or 46.26% and 32.05% lower than those under normal conditions, respectively ( Figure 5C ).

The number of fruits per plant, individual fruit weight and fruit diameter can be used as yield and yield quality variables of tomato fruit. Under the normal-temperature condition, all tested genotypes produced fruits. WT-MT plant produced the highest fruit number and significantly differed from the iaa9-3 and iaa9-5. Under normal conditions, the number of fruits for WT-MT, iaa9-3 and iaa9-5 were 53.3, 47.8 and 46.8 fruits per plant, respectively. The heat condition affected the fruit yield of all investigated genotypes, with the lowest value detected in WT-MT. WT-MT had a small fruit size with no seed inside. However, iaa9-3 and iaa9-5 can still produce fruits under heat-stress condition, with the value being reduced compared with that under normal condition. Under heat condition, the reduction of fruit number varied compared to that in normal condition, i.e. 97.75%, 42.34% and 48.68% for WT-MT, iaa9-3 and iaa9-5, respectively ( Figure 6A ).

Fruit size can be indicated by individual fruit weight, length and diameter. Under normal condition, iaa9-3 and iaa9-5 had a smaller fruit size, indicated by shorter fruit length and diameter and smaller fruit weight, compared with WT-MT. However, the fruit length of iaa9-3 was comparable to that of WT-MT. Under the heat-stress condition, iaa9-3 and iaa9-5 resulted in a longer fruit length and higher fruit diameter compared with WT-MT ( Figures 6B–D ). Although iaa9-3 and iaa9-5 had a few fruit numbers under heat-stress condition, both mutants had a larger fruit size compared with that under normal condition. From the data obtained, Figure 6 indicate a positive relationship between fruit number and fruit size, where more fruits were produced ( Figure 6A ), which resulted in smaller fruit sizes and weights ( Figures 6B–D ). Statistical data analysis showed that the individual fruit weights of iaa9-3 and iaa9-5 were significantly smaller than those of WT-MT under normal condition. However, both mutants had significantly higher fruit weight than WT-MT under heat-stress condition ( Figure 6B ).

In all investigated plants, the number of seeds was highly affected by genetic factors and environmental conditions. Mutation in the IAA9 gene had a significant effect on the number of seeds. Under normal conditions, iaa9-3 and iaa9-5 had lower numbers of seeds compared with WT-MT, with reductions of up to 55.82% and 37.73%, respectively ( Figure 6E ). Heat stress significantly reduced the number of seeds in all investigated plants. Under the heat-stress condition, although iaa9-3 and iaa9-5 resulted in a larger fruit size compared with that under normal conditions, both mutants and WT-MT cannot produce seeds because of the heat-stress condition ( Figure 6E ).

H₂O₂ content was analysed to predict the accumulation of reactive oxygen species (ROS) within their leaves as an effect of IAA9 mutation under two different environmental conditions. Statistical data analysis showed that H₂O₂ content differed under various plant genotypes and environmental conditions. Under normal conditions, the H₂O₂ content was lower than that under heat-stress conditions in all plant genotypes. Mutation in the IAA9 gene significantly reduced H₂O₂ content in iaa9-3 and iaa9-5 compared with WT-MT, with values of 0.44 and 1.90 µmol/g FW, respectively, which is lower than that of WT-MT ( Figure 7A ). Environmental conditions significantly affected the content of H₂O₂ in plants. The rise in temperature resulted in the increased H₂O₂ content in all investigated plants, but iaa9-3 and iaa9-5 showed a lower H₂O₂ content compared with WT-MT. WT-MT had a significantly higher H₂O₂ content than iaa9-3 and iaa9-5, but it was comparable between iaa9-3 and iaa9-5. The increase in H₂O₂ content under heat-stress conditions varied among genotypes, with values of 1.22, 0.56 and 1.82 µmol/g FW for WT-MT, iaa9-3 and iaa9-5, respectively. These values were higher than those under normal conditions ( Figure 7A ).

Antioxidant activity values directly influence ROS accumulation in plants. Antioxidant activity varied among genotypes under normal or heat-stress conditions. The statistical data analysis of antioxidant activity revealed a significant difference in antioxidant activity among genotypes under normal or heat-stress conditions ( Figure 7 ). Under normal conditions, iaa9-5 showed the highest leaf antioxidant activity, followed by iaa9-3 whose value was significantly higher than that of WT-MT. A significant increase in antioxidant activity was detected when the plant was exposed to high temperatures or heat stress. Under heat-stress conditions, similar findings with normal conditions were observed. iaa9-3 had the highest antioxidant activity, followed by iaa9-3 and WT-MT, with increased antioxidant activities of 248.90%, 152.22% and 171.92% compared to the under normal conditions for WT-MT, iaa9-3 and iaa9-5, respectively ( Figure 7C ).