Research Article

Optimizing Ultra-Early-Maturing Rice Cultivation: Effects of Pruning and Variety Selection on Agronomic Traits and Yield

Abd Haris Bahrun1,2*, Andi Amran Sulaiman2,3, Amir Yassi1,2, Muh Farid1,2, Yunus Musa1,2, Eka Setiawan4, Ayu Anisa Amir3, Madonna Casimero5, Dian Ratnadilah Abdullah2, Salwa Aulia Haruni1, Azmi Nur Karimah Amas2 and Muhammad Fuad Anshori1,2

1Department of Agronomy, Faculty of Agriculture, Hasanuddin University, Makassar 90245, Indonesia; 2Rice Research Group, Faculty of Agriculture, Hasanuddin University, Makassar 90245, Indonesia; 3Department of Agribusiness, Faculty of Agriculture, Hasanuddin University, Makassar 90245, Indonesia; 4Food Crop Production Technology, Vocational Faculty, Hasanuddin University, Makassar 90245, Indonesia; 5International Rice Research Institute, University of the Philippines Los Baños, Los Baños, Philippines.

Received | October 05, 2025; Accepted | January 12, 2026; Published | June 27, 2026

*Correspondence | Abd Haris Bahrun, Department of Agronomy, Faculty of Agriculture, Hasanuddin University, Makassar 90245, Indonesia; Email: [email protected]

Citation | Bahrun, A.H., A.A. Sulaiman, A. Yassi, M. Farid, Y. Musa, E. Setiawan, A.A. Amir, M. Casimero, D.R. Abdullah, S.A. Haruni, A.N.K. Amas and M.F. Anshori. 2026. Optimizing ultra-early-maturing rice cultivation: effects of pruning and variety selection on agronomic traits and yield. Sarhad Journal of Agriculture, 42(2): 1072-1082.

DOI | https://dx.doi.org/10.17582/journal.sja/2026/42.2.1072.1082

Keywords | Ultra-early-maturing varieties, Climate change resilience, Cultivation optimization, Oryza sativa, Padjajaran variety, Pruning techniques

Copyright: 2026 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Rice is the main food commodity for the Indonesian population (Rozaki, 2020, 2021). Indonesia’s domestic demand for rice continues to increase in line with population growth (Schmidt et al., 2021; Firmansyah et al., 2025). In 2024, total national rice consumption reached 31.21 million tons (Agricultural Ministry, 2024), whereas domestic production was only able to produce 30.62 million tons (Statistics Indonesia, 2025). The disparity between demand and production has resulted in a deficit, prompting an increase in imports to meet national needs (Rozaki, 2020; Yuan et al., 2022; Umar, 2025). In addition, climate change has emerged as an issue that can reduce rice production (Ruminta and Nurmala, 2018; Vogel et al., 2019; Fan et al., 2022). Climate change harms the rice production system, with the risk of crop failure owing to rising temperatures, changing rainfall patterns, and extreme weather events (Caruso et al., 2016; Sulaminingsih et al., 2024; Rajakaruna et al., 2024). Therefore, effective innovation in developing resilient rice varieties to climate change is required to increase rice production in the future.

Resilience to climate change has been pursued through the use of ultra-early maturing rice varieties (Acquaah, 2012; Syukur, 2018). Ultra-early maturing rice varieties with lifespans of less than 100 days can mitigate the negative impacts of extreme climates (Dey et al., 2023). Plants with rapid life cycles can complete their growth and development before the onset of adverse weather conditions (Rohaeni and Ishaq, 2015; Wening et al., 2018; Subekti and Umar, 2022). This advantage not only keeps production stable but also reduces the risk of crop failure owing to unpredictable seasonal changes (Achyadi et al., 2019). Moreover, these varieties open up opportunities to increase planting frequency within a year, thereby significantly improving production yields (Wening and Susanto, 2014; Achyadi et al., 2019; Yun, 2023). Several ultra-early maturing varieties have been developed and released by the Ministry of Agriculture, including Cakrabuana and Padjajaran (Barokah et al., 2021; Balitbangtan, 2021). Additionally, the private sector has contributed to the development of ultra-early maturing varieties such as M70D (Palobo et al., 2019). However, the potential of ultra-early maturing rice varieties still requires cultivation optimization tailored to their growth characteristics (Sutardi et al., 2022; Sitaresmi et al., 2023 a,b). The main difference lies in the vegetative growth phase, which directly affects generative development; therefore, cultivation strategies must be carefully designed (Musa et al., 2023; Anshori et al., 2024). The optimization of ultra-early maturing rice cultivation can be achieved through the optimization of cultivation techniques.

Technical cultivation engineering can be performed through pruning, including in rice. Previous studies have emphasized the role of pruning in improving plant quality and stimulating tiller production (Islam et al., 2006; Suyanto et al., 2023; Chachar et al., 2025). An increase in tiller number is positively correlated with panicle formation and indirectly enhances rice productivity (Musa et al., 2023). In addition, pruning during the vegetative phase has been reported to trigger elicitors that strengthen resistance to pests and diseases (Jamilah et al., 2018). However, most of these studies were conducted on conventional or medium-duration rice varieties, with limited attention paid to ultra-early maturing rice. The timing of pruning, which is critical for synchronizing vegetative growth and reproductive transition, has not been systematically investigated in ultra-early varieties of grapevines. This represents a significant gap, particularly in the context of climate change adaptation, where ultra-early maturing rice is increasingly prioritized to cope with shortened growing seasons and unpredictable rainfall. Therefore, our research highlights the novelty of evaluating pruning time, specifically in ultra-early rice varieties. By integrating agronomic performance with statistical analyses, this study provides new evidence on how pruning can be optimized to maximize the yield potential while enhancing resilience. The objective of this study was to identify the optimal pruning time for ultra-early maturing rice yields as a resilience effort under climate change.

Materials and Methods

Research design

This phase of the research involved two treatments: pruning techniques and ultra-early maturing rice varieties. The combinations were arranged using a split-plot design with a randomized complete block design (RCBD). The main plots in this study were pruning treatments involving three pruning times: no pruning, pruning 5 days before the second fertilization (25 days after planting (DAP)), and pruning 5 days after the second fertilization (35 DAP). The subplots consisted of three ultra-early maturing

 

varieties: Cakrabuana, Padjajaran, and M70D. All combinations were repeated thrice, resulting in 27 experimental units. Each unit had a plot size of 3 × 3 m. The procedure for this study followed Musa et al. (2023); Anshori et al. (2024). These procedures include land preparation, mapping, seedling planting, maintenance and harvesting. Modifications to these procedures were tailored to the treatments used in this study.

Observation parameters

The observations thoroughly covered the agronomic, economic, and social aspects. Other agronomic characteristics observed, consisting of: plant height (cm), total tillers and productive tillers (stems), flag leaf length (cm), days to harvest (DAP), panicle length (cm), grain density (grains cm-1), 1000-grain weight (g), grain yield per hill at 14% moisture content (g), and the yield per ha at 14% moisture content (tons ha-1).

Data analysis

The observational data obtained were analyzed using analysis of variance (ANOVA) followed by the least significant difference (LSD) test at a 0.05 significance level using Statistical Tool for Agricultural Research (STAR) 2.0.1 software and parametric multivariate analysis by RStudio with the ggplot2 package, especially for correlation and bar chart analysis.

Results

The analysis of variance focused on three sources of variation: pruning treatment, varietal differences, and the interaction between pruning and variety (Table 1). Pruning treatments significantly affected plant height, productive tiller number, flag leaf length, total grain number, and grain yield per hill. Variety treatment was the dominant factor significantly influencing almost all characteristics, except for flag leaf length, grain density, and 1000-grain weight. The interaction between the two varieties had a significant effect only on plant height and yield characteristics.

The results of the correlation analysis between the growth characteristics are shown in Figure 1. The correlation was first focused on the yield as the main criterion for evaluation. Based on the figure, yield had a significant positive correlation only with the number of filled grains (NFG) (0.45), number of total grains (NTG) (0.43), grain density (GD) (0.49), and grain yield per hill (GYC) (0.48). The NFG trait was significantly positively correlated with NTG (0.95), PD (0.92), GYC (0.46), plant height (PH) (0.40), and panicle length (PL) (0.48). The NTG trait also showed a significant positive correlation with PD (0.97), BY (0.41), and PL (0.56). PD traits were also significantly positively correlated with GYC (0.39) and PL (0.46). GYC was also positively correlated with PH (0.48), PL (0.47), and W1000G (0.43) measurements.

 

Table 1: Analysis of variance of rice growth character in response to the combination of pruning treatment and ultra-early maturing rice varieties

Character		P values		CVa	CVb
	Pruning (P)	Variety (V)	PxV
PH	0.0213**	0.0171*	0.0395*	3.85	2.71
NTT	0.0585	0.0222*	0.4005	12.23	17.97
NPT	0.0138*	0.0032**	0.5741	8.44	17.88
FLL	0.0083**	0.4168	0.3292	8.99	19.29
PL	0.0532	0.0025**	0.0488	5.75	4.48
NFG	0.0655	0.0010**	0.9337	13.12	14.73
NTG	0.0302*	0.0000**	0.7198	9.48	13.28
PFG	0.6121	0.0012**	0.2233	8.04	5.39
GD	0.0571	0.0001**	0.9559	8.38	12.15
W1000g	0.4225	0.1976	0.3319	11.11	8.68
Grain yield per hill	0.0278*	0.2665	0.6247	16.92	28.18
The Yield	0.0686	0.0469*	0.0230*	15.55	12.97

 

Note: PH: plant height, NTT: Number of total tillers, NPT: Number of productive tillers, FLL: flag leaf length, PL: panicle length (cm), NFG: number of filled grains, NTG: Number of total grains, PFG: Percentage of filled grains, GD: grain density, W1000G: weight of 1000-grains, CVa = coefficient of variance a error, CVb: coefficient of variance b error

 

 

Further independent analyses were performed on grain density (Figure 2) and grain yield per hill (Figure 3). Based on the grain density, the analysis focused on the effect of variety. Padjajaran had the highest grain density (5.07). However, this potential was not significantly different from that of Cakrabuana (4.97). Conversely, the M70D variety had the lowest potential grain density (3.51). Based on the grain yield per hill, the analysis focused on the pruning treatment. Pruning at 25 DAP was considered the best treatment, inducing a grain yield of 23.31 g per hill. However, this potential was not significantly different from the yield without the pruning treatment (21.94 g). Conversely, pruning at 35 DAP resulted in the lowest grain yield per hill, with a potential yield of 16.39 g.

 

Table 2: Interaction analysis of ultra-early rice varieties and pruning treatments on yield

Varieties	no pruning	Pruning in 25 DAP	Pruning in 35 DAP	LSD
Cakrabuana	4.49pab	5.06pb	4.91pa	1.16
Padjajaran	5.37ap	6.37pa	3.70qb
M70D	3.93bp	4.82pb	4.23pab
LSD	1.10

 

Note: LSD = Least square distance

 

The interaction analysis in this study focused on the yield (Table 2). Based on the effect of pruning on each variety, Cakrabuana, Padjajaran, and M70D showed an increase in yield with pruning at 25 DAP, with values of 5.06, 6.37, and 4.82 t/ha, respectively. However, these values were not significantly different from those of other pruning treatments. Based on the pruning treatment, the Padjajaran variety showed significant interaction dynamics between the different pruning treatment patterns. In contrast, Cakrabuana and M70D tended to respond positively to pruning, particularly at 25 DAP.

 

The results of the harvest age observations are shown in Figure 4. Based on the figure, the treatment without pruning was relatively faster than the other treatments. Conversely, treatment with pruning at 25 DAP showed a longer duration than the other treatments, by approximately 3-5 days. All ultra-early rice varieties showed the same trend regarding differences in pruning treatments.

Discussion

The analysis of variance in this study showed that the source of variation from the varieties dominated more than other sources of variation. Conversely, variations due to pruning treatments and their interaction with the varieties only affected a few growth traits. This suggests that each of the ultra-early maturing varieties included in this study exhibited different growth patterns, and the effects of pruning and its interactions were not clearly illustrated. Musa et al. (2023, 2025), Anshori et al. (2024), and Bahrun et al. (2025) reported markedly different growth patterns among these three ultra-early maturing varieties in response to cultivation practices, indicating that varietal diversity strongly dominates the differences in growth traits observed in their research. Nevertheless, certain specific growth characteristics were independently influenced by the supporting treatments and their interactions with the three varieties. This was also observed in the present study, where several significant growth characteristics served as indicators of the response to pruning treatments and their interaction with ultra-early maturing rice varieties. Therefore, evaluations must be conducted in a focused and systematic manner using evaluation criteria.

Determining evaluation criteria has become an important part of the effective assessment of cultivation technologies or varieties. This concept has also been reported by Herzberg et al. (2019), Brown et al. (2020); Saini et al. (2022); Sakinah et al. (2022); Han et al. (2024), including in ultra-early maturing rice (Musa et al., 2023, 2025; Bahrun et al., 2025). The evaluation criteria for rice can be determined through correlation. This effectiveness has also been reported by Saleh et al. (2020); Arifuddin et al. (2021); Thuy et al. (2023); Bahrun et al. (2025). Based on a correlation analysis focusing on yield as the main indicator, the number of filled grains, number of total grains, grain density, and grain yield per hill showed significant positive correlations. This indicates that the increase in yield is likely to be directly influenced by these production components. However, based on the correlation among NFT, NTG, and PD, all variables exhibited a significant correlation exceeding 0.95, indicating the presence of multicollinearity among these variables (Olivoto et al., 2017; Anshori et al., 2021). Consequently, one of these variables, grain density (which has the highest correlation with yield), can be used as a representative criterion for evaluating grain yield per hill. Therefore, both grain density and yield can serve as evaluation criteria, alongside yield, as indicators of the effectiveness of pruning treatment in ultra-early maturing rice varieties.

Grain density is an indicator of productivity related to the number of grains per unit length of a panicle. It reflects the pattern of grain distribution within a panicle, which correlates with the pattern of crop yield increase. A high grain density indicates efficient and effective production per panicle. This characteristic is also associated with genetics, nutrient availability, population density, and environmental conditions (Das et al., 2018; Li et al., 2022). Based on this study, grain density was independently influenced by varietal diversity. The Padjajaran variety had the highest potential for grain density, followed by Cakrabuana. This is important because ultra-early maturity potential requires effective panicle production. Therefore, both varieties are considered to have good potential as superior ultra-early maturing rice varieties.

Grain yield per hill is a supplementary component of the evaluation criteria that is closely related to the productivity. This potential reflects the independent productive capacity without describing the dynamics of competition between individuals in a population. Nevertheless, grain yield per hill still provides a simple overview of the overall potential for accumulation of yield components in a planting (Li et al., 2019; Isnawan et al., 2020; Limbongan et al., 2022; Khamid et al., 2023). According to the results of this study, the grain yield per hill was heavily influenced by the pruning treatment. Pruning at 25 days after planting (DAP) showed a significantly different approach compared to other treatments, particularly compared to pruning at 35 DAP. These findings indicate that the timing of pruning plays an important role in determining vegetative growth efficiency. Cumulatively, pruning at 25 DAP supported an increase in production per hill. In addition, the grain yield per hill complements the yield variation alongside grain density, which synergistically reflects the potential for harvest variation owing to the interaction between these two treatments.

Based on the interaction between pruning treatment and variety, all three varieties (Padjajaran, Cakrabuana, and M70D) experienced an increase in yield with pruning at 25 DAP, especially the Padjajaran variety. In general, ultra-early maturing rice optimizes the potential biomass of tillers, which correlates with the potential of production components. Pruning at a relatively young age induces an increase in the number of tillers and improves the strength of the rice clump base. This is because the phenology of ultra-early maturing rice at 25 days is entering the elongation stage or the quadratic growth phase on the sigmoid curve (Baharuddin et al., 2025). Additionally, pruning stabilizes nutrient content, particularly nitrogen and non-structural carbohydrates, and alters the direction of apical dominance in favor of cytokinin (Yuan et al., 2024). This encourages rice plants to focus on the development of tillering and biomass, which are associated with the yield components. Both of these factors are why rice plants are more responsive to the induction of tiller formation and biomass accumulation, particularly when pruning is applied. Moreover, this process is conducted before the second fertilization at 30 DAP, so biomass accumulation and tiller induction will be even more effective with the pruning treatment at 25 DAP. This was also reported by Suyanto et al. (2023) for the Agro Pawan rice variety (125 days to harvest), where the effectiveness of pruning occurred at 44 days old, when entering the panicle initiation phase and before the third fertilization. This phenomenon is further supported by the genetic potential of the crop, which is related to grain density. The Padjajaran variety, which has a high grain density, was further induced by this pruning treatment, which directly increased production per hill and production per unit area of the population. Furthermore, based on maturation potential, pruning at 25 DAP did not significantly alter the harvest time. This further strengthens the effectiveness of pruning at 25 DAP in ultra-early maturing rice. Therefore, the concept of combining pruning at 25 DAP with the Padjajaran variety is highly recommended in this study to support <the yield> of ultra-early maturing rice varieties.

Conclusions and Recommendations

The application of pruning and ultra-early rice varieties significantly affected plant growth and yields. Specifically, pruning conducted 25 days after planting, in conjunction with the Padjajaran variety, resulted in an optimal yield by enhancing the grain yield per hill and grain density. The treatment factors directly contributed to the increased yield. Grain density emerged as the most critical trait for yield, whereas grain yield per hill played a supportive role. Although a higher grain count is generally associated with an increased yield, it has a negative direct effect, suggesting a complex relationship. The Padjajaran variety demonstrated the most favorable response to pruning, whereas Cakrabuana and M70D exhibited stable positive responses. Selecting the appropriate variety and timing of pruning can enhance ultra-early rice productivity. Therefore, pruning at 25 DAP and using the Padjajaran variety are highly recommended to optimize the IP 300 program.

Acknowledgements

This work was also supported by the Directorate of Research, Technology, and Community Service of the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia under the Penelitian Fundamental Reguler BIMA scheme (069/C3/DT.05.00/PL/2025).

Novelty Statement

This study offers the inaugural comprehensive assessment of the timing of pruning and varietal selection to enhance the productivity of ultra-early maturing rice in Indonesia. By identifying the synergistic interaction between pruning at 25 days after planting (DAP) and the Padjajaran variety, this study introduces an innovative agronomic strategy that significantly enhances grain yield per hill and grain density. These findings provide a practical innovation to support the intensification of rice cropping cycles under the IP 300 program, thereby contributing to sustainable increases in the national rice production.

Author Contributions

Abd Haris Bahrun: Conceptualisation, Methodology, Original draft, Funding acquisition, reviewed the draft

Andi Amran Sulaiman: Conceptualisation, Validation, reviewed the draft, Funding acquisition

Amir Yassi: Validation, reviewed the draft

Muh Farid: Validation, reviewed the draft

Yunus Musa: Validation, reviewed the draft

Eka Setiawan: Methodology, Formal analysis, reviewed the draft

Ayu Anisa Amir: Data Curation, Conceptualisation, reviewed the draft

Madonna Casimero: Validation, reviewed the draft

Dian Ratnadilah Abdullah: Formal analysis, Investigation, reviewed the draft

Azmi Nur Karimah Amas: Data Curation, reviewed the draft

Salwa Aulia Haruni: reviewed the draft

Muhammad Fuad Anshori: Conceptualisation, Methodology, Formal analysis, Visualisation

All co-authors reviewed the final version and approved the manuscript before submission.

Generative AI and AI-assisted technology statement

The authors declare that no generative AI and AI assisted technology was used in the creation of this manuscript

Conflict of interest

The authors have declared no conflict of interest.

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