Optimal Shoot Mass for Propagation to Increase the Yield and Quality of Pineapple

Abstract

This study investigates the impact of shoot mass on the growth, flowering, and yield of pineapple plants in two consecutive crops (2019–2020 and 2020–2021). Four treatments with varying shoot masses (200–300 g, 350–400 g, 450–500 g, >500 g) were analyzed for their flowering time, fruit harvesting, and yield parameters. To induce flowering, Ethrel was applied at a concentration of 0.4%. Each shoot was treated with 20–25 mL of Ethrel, resulting in synchronized flowering in the pineapples. The experiment employed a complete randomized block design (RCBD) comprising four treatments. The results reveal that bigger shoot masses lead to earlier flowering and a shorter time for fruit harvesting, ranging from mid-February to early July. Furthermore, this study explored the yield factors, showing that shoot masses of 350–500 g consistently result in higher harvest numbers, fruit weights, and theoretical yields. The influence of shoot mass on fruit quality parameters, including size, biochemical composition, and edibility, was also examined. Notably, smaller shoot masses are associated with higher dry matter, vitamin C, sugar, and brix levels, indicating superior quality. The findings suggest that optimizing shoot mass could significantly impact the pineapple cultivation timeline, yield, and fruit quality, providing valuable insights for pineapple farmers and cultivators. These findings carry profound implications for pineapple cultivation practices and market strategies. By optimizing shoot mass, growers can strategically adjust planting schedules to capitalize on favorable flowering and harvesting periods, potentially enhancing market competitiveness. Moreover, the insights gleaned regarding fruit quality parameters offer avenues for targeted marketing strategies, catering to discerning consumer preferences for superior-quality produce. Thus, this study not only advances scientific understanding but also provides actionable insights that could revolutionize pineapple cultivation practices and market positioning strategies, ultimately benefiting farmers and cultivators alike.

1. Introduction

Pineapple (Ananas comosus) cultivation, owing to its economic importance and nutritional value, has become a key focus in agricultural research and development [1]. Pineapple stands as a tropical jewel in the realm of global agriculture, valued not only for its exquisite taste but also for its economic significance and nutritional richness. As the demand for this tropical fruit continues to rise, propelled by consumer preferences for diverse and unique flavors, the challenge to enhance both yield and quality becomes a central concern for pineapple cultivators worldwide [2]. In this pursuit, the interplay between shoot mass, a pivotal aspect of plant architecture and vigor, and the strategic application of Ethrel—a plant growth regulator leveraging the active compound ethephon—emerges as a potential key to unlocking unprecedented advancements in pineapple cultivation [3]. The pineapple industry has witnessed remarkable growth, transitioning from local subsistence farming to a globalized market, driven by the fruit’s versatility and widespread popularity [4]. Indigenous and cultivated varieties alike contribute to this vibrant market, each presenting unique opportunities and challenges for growers [5]. Achieving optimal yield and quality requires a nuanced understanding of the complex physiological processes governing plant growth and development, where the significance of shoot mass has become increasingly evident [6]. Currently, pineapples are cultivated in about 90 countries and regions worldwide, covering a total area exceeding 400,000 hectares. The primary cultivation regions are in Asia, America, and Africa. The top 10 pineapple-producing countries—Thailand, the Philippines, China, Brazil, India, Nigeria, Costa Rica, Mexico, Indonesia, and Kenya—collectively account for approximately 73% of the global pineapple output. Pineapple is a major player in the global tropical fruit trade, with an annual trade volume surpassing USD 2.5 billion [2]. By 2005, the Centro Internacional de la Recherche Agricole–Département Productions Fruitières et Horticoles had accumulated a collection of over 600 pineapple germplasm materials. Each of these materials included comprehensive data on their origin, plant characteristics, and agronomic traits [7]. The first pineapple breeding program was initiated in Florida, USA, with the goal of developing varieties better adapted to local conditions and with enhanced fruit quality. Subsequently, pineapple breeding programs were also established in Hawaii (USA), South Africa, India, Malaysia, Côte d’Ivoire, Brazil, Japan, and other countries (Coppens d’Eeckenbrugge) [8]. Different breeding methods and cultivation measures have a significant impact on fruit yield and quality. For instance, tissue culture techniques have been utilized to produce uniform and disease-free planting material, which is essential for establishing high-yielding pineapple plantations. The integration of these techniques with traditional farming practices has led to improved fruit size, sweetness, and overall marketability [9]. Moreover, the development of sustainable cultivation practices, such as organic farming and integrated pest management (IPM), has been a focal point of recent research. These methods aim to reduce the environmental impact of pineapple production while maintaining high yields and fruit quality. The combined application of advanced breeding techniques and optimized cultivation practices presents a promising approach to meeting the growing demand for pineapples in the global market [10].

Shoot mass, encompassing the weight and distribution of shoots on a pineapple plant, plays a pivotal role in determining the plant’s overall health, resource allocation, and its capacity to bear and sustain fruit [11]. The challenge lies in deciphering the delicate balance between promoting robust vegetative growth for enhanced fruit-bearing potential while avoiding excessive biomass that might compromise fruit quality [12]. In this delicate equilibrium, the application of plant growth regulators such as Ethrel offers a targeted approach to modulating key physiological processes [13].

Ethrel, containing ethephon as its active ingredient, has been recognized for its potential to influence flowering, fruiting, and overall plant development across various crops. Ethylene is a natural plant hormone that regulates a wide range of processes such as promoting the ripening of fruits by enhancing the activity of enzymes involved in the softening, color change, and flavor development of fruits. It can induce flowering in certain plants, like pineapples. Ethylene promotes the shedding of leaves, flowers, and fruit. It accelerates the aging process in plants. High levels of ethylene can inhibit stem elongation and promote lateral expansion [14,15]. Ethylene is a key plant hormone that plays a crucial role in regulating a wide range of physiological processes in plants, including growth, development, and response to stress [14]. Ethylene inhibits stem elongation and promotes lateral expansion, leading to thicker, shorter stems. In seedlings, ethylene induces the triple response, characterized by reduced elongation, increased stem thickness, and horizontal growth. This helps seedlings navigate through soil obstacles [16,17]. Ethylene promotes the formation of lateral roots, enhancing the root system’s ability to absorb water and nutrients. Ethylene stimulates the development of root hairs, increasing the root surface area for absorption [18]. Ethylene can either promote or inhibit flowering depending on the plant species. For example, it promotes flowering in pineapples and mangoes but inhibits it in many annual plants [14].

However, the optimal application rates and the nuanced interplay between Ethrel and shoot mass in the context of pineapple cultivation remain areas that demand rigorous investigation [19]. This was particularly crucial given the diversity of pineapple varieties and the varied ecological conditions in which they thrive. We hypothesize that increasing shoot mass will positively correlate with enhanced plant vigor, earlier flowering, increased fruit production, and higher overall yield. However, excessive shoot mass may compromise fruit quality due to resource allocation issues. We expect that strategic Ethrel application will effectively induce synchronized flowering, leading to improved fruit set and yield. We anticipate that different shoot mass categories may require varying Ethrel application rates to achieve optimal results. We predict that Ethrel application will have a significant impact on pineapple fruit quality parameters, including size, biochemical composition, and edibility. We hypothesize that smaller fruits may exhibit superior quality traits, such as higher dry matter, vitamin C content, sugar levels, and brix levels, compared to larger fruits. By addressing these objectives and hypotheses, this research aims to provide actionable insights for pineapple growers, enabling them to optimize cultivation practices and maximize both yield and quality in pineapple production. This research endeavors to fill this critical knowledge gap by delving into the intricate relationship between shoot mass and Ethrel application, with the overarching goal of maximizing both yield and quality in pineapple cultivation. By conducting comprehensive studies that consider the unique attributes of diverse pineapple varieties, this research seeks to provide evidence-based insights that can inform precision agricultural practices and foster sustainable growth within the pineapple industry.

2. Materials and Methods

2.1. Plant Materials

The research material comprised the pineapple variety belonging to the Queen pineapple group, with shoot masses of 200–300 g, 350–400 g, 450–500 g, and >500 g, featuring robust and healthy shoots, free from diseases (Figure 1). Each shoot mass category corresponds to the weight range of individual pineapple shoots, with one plant cultivated per shoot. This meticulous approach ensured consistency in the experimental design and allowed for accurate evaluations of the impact of shoot mass on plant growth and productivity. The careful selection of robust, disease-free shoots further ensured uniformity across the experiment.

2.2. Experimental

The experiment consisted of four treatments: treatment 1—shoot mass, 200–300 g; treatment 2—shoot mass, 350–400 g; treatment 3—shoot mass, 450–500 g; and treatment 4—shoot mass, >500 g (Figure 1). The experiment was arranged using a complete randomized block design (RCBD) with four treatments. Each treatment was replicated three times, and each replication consisted of thirty plants. The spacing between plants was 35 cm × 55 cm, resulting in a plant density of 52,000 plants per hectare. The planting season was in March (spring crop). Flowering was induced when the pineapple plants had 28–30 leaves, with leaf tips displaying the characteristic deep red color of the variety. The induction was performed using Ethrel (Ethephon) at a concentration of 0.4%. Each shoot received 20–25 mL of Ethrel solution to promote synchronous flowering. The Ethrel application was timed to coincide with the stage when plants had 28–30 leaves with deep red leaf tips. The Ethrel was applied once, as the goal was to achieve synchronous flowering in the treated plants. Subsequently, post-flowering, a supplementary fertilizer was applied to support fruit development. Other care practices: All experimental treatments received fertilizer consisting of 50 g of organic microbial fertilizer, 25 g of urea, 37.5 g of potassium chloride, and 12.5 g of NPK buffalo head fertilizer (20-20-15). This fertilization was complemented by pest and disease control measures. Additionally, nutrient supplementation through foliar spraying was administered as per the recommendations of the Fruit and Vegetable Research Institute. The implementation period was January 2019–August 2021.

2.3. Measurements

Indicators related to flowering and fruit setting: Time from treatment to flowering (days)—this measures the time from the treatment date until 10% of pineapple plants start flowering. Time from flowering to harvest (days)—this indicates the time from the onset of flowering until the beginning of fruit harvesting. Flowering rate (%)—this is calculated as the percentage of flowering plants out of the total number of treated plants. These indicators were observed for 30 plants per replication, with each treatment observed for a total of 90 plants.

Productivity indices: Average fruit weight (g)—calculated as the average weight of 30 fruits per repetition, with three repetitions. Individual fruit weights were measured using an analytical scale, and the average value was derived. Number of harvested fruits (fruits)—calculated as the total count of fruits harvested in each repetition for a specific treatment. Actual yield (tons/ha)—calculated by weighing all harvested fruits in each repetition for a specific treatment, then determining the average yield per hectare. The theoretical yield per tree was calculated by multiplying the average fruit weight by the number of harvested fruits per tree.

Biometric characteristics of the fruit: Fruit height (cm)—measured using calipers from the top to the bottom of the fruit. Thirty fruits were measured randomly per repetition, with three repetitions. The average value was recorded. Fruit diameter (cm)—measured using calipers at the widest part of the fruit. Thirty fruits were measured randomly per repetition, with three repetitions. The average value was recorded.

* Ratio of edible parts (%) = (W fruit − (W seeds + W peel))/W fruit × 100

W: Weight.

W fruit: Total weight of the fruit.

W seeds: Weight of the seeds of the fruit.

W peel: Weight of the peel of the fruit.

Biochemical fruit indicators: The biochemical indicators of the fruit, including brix, dry matter content, total acid content, reducing sugar content, and vitamin C content, were analyzed for 10 fruits, and the analyses were conducted at the Fruit and Vegetable Quality Control Department of the Fruit and Vegetable Research Institute. The dry matter content (%) was determined according to the method reported by Nasiruddin et al., 2019 [20]. To determine the dry matter content of fruit, one must homogenize the sample and weigh approximately 10 g into a pre-weighed dish, dry the sample in an oven at 105 °C for 24 h or until a constant weight is achieved, then cool the dish in a desiccator and reweigh. Finally, calculate the dry matter content using the formula % dry matter = Weight of dried sample/Weight of fresh sample × 100. The vitamin C content (mg) was determined following the method of Nasiruddin et al., 2019 [20]. First, approximately 10 g of the fruit was homogenized with a 5% metaphosphoric acid solution to extract the vitamin C. After filtration to obtain a clear extract, 10 mL of the sample was titrated with a standard dye solution (DCPIP) until a pink color persisted for 15 sec. The volume of DCPIP solution used in the titration was then used to calculate the amount of vitamin C present in the sample. This method allows for a reliable assessment of vitamin C content in fruits. The total acid content (%) was determined following the method of McDonald et al., 2013, with modification. To determine the acid content in fruit juice, one must start by homogenizing the fruit flesh, then weighing 10 g of the juice mixture and placing it in a 100 mL conical flask. Add 50 mL of distilled water, shake well, and heat in a boiling water bath for 30 min. After cooling, transfer the mixture to a 100 mL volumetric flask, dilute to the mark with distilled water, shake well, and filter. For titration, pipette 10 mL of the filtered solution into a 100 mL conical flask, add distilled water to dilute, then add 0.25 mL of 0.1% phenolphthalein indicator. Using a burette, titrate with 0.1 N NaOH until a pink color persists for 30 sec. Record the volume of NaOH used. Repeat this process three times for each sample [21]. Degrees brix (%) was determined following the method of McDonald et al., 2013 [21]. To determine the brix in fruit juice, first homogenize the fruit flesh. Then, weigh 10 g of the juice mixture into a 250 mL volumetric flask, add water to half the volume, cover with a condenser, and heat in a water bath at 80 °C for 30 min. After cooling, remove the proteins using 10% lead acetate and remove excess lead with saturated potassium oxalate. Adjust the volume, let the precipitate settle, and then filter. Pipette 10 mL of the filtrate into a 250 mL conical flask, add 5 mL of HCl, boil for 30 min, cool, neutralize with 30% NaOH, transfer to a 250 mL volumetric flask, dilute to the mark, and filter. For the titration, pipette 10 mL of this filtrate into a conical flask, add 25 mL each of Fehling solutions A and B, boil for 3 min, and filter the CuO precipitate. Dissolve the precipitate with Fe₂(SO4)₃ and titrate with 0.1 N KMnO₄ until a pink color persists for 1 min. Record the volume of KMnO₄ used and use the Bectrang table to calculate the glucose content; finally, determine the percentage of total sugar in the sample.

2.4. Statistical Analysis

All parameters were recorded from 30 fruits (n = 30). The data were analyzed using SPSS software (version 20.0; IBM Corp., Armonk, NY, USA). The experimental results were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple range test. The mean values of the treatment groups were compared using Tukey’s test, at a significance level of p ≤ 0.05.

3. Results and Discussion

3.1. The Influence of Shoot Mass on the Time of Flowering Induction and Fruit Harvesting in Pineapples

Table 1. Effects of bud weight on flowering and fruit harvest time of pineapple.

Treatments	Time (mm/dd/yy)			Time
	Flowering Treatment	Bloom	Harvest	Flowering Treatment to Bloom (Days)	Bloom to Harvest (Days)	Planting to Flowering Treatment (Days)	Planting to Harvest (Days)
2019–2020
200–300 g	15–20 December 2019	16–23 January 2020	19–27 June 2020	31–33	153–154	265–268	449–455
350–400 g	5–10 October 2019	6–15 November 2019	10–18 April 2020	31–35	153–154	195–198	380–386
450–500 g	15–20 September 2019	14–22 October 2019	19–28 March 2020	29–32	155–156	175–178	359–366
>500 g	5–10 August 2019	5–12 September 2019	19–28 February 2020	30–32	164–166	135–138	331–336
2020–2021
200–300 g	15–20 December 2020	22–28 January 2021	1–8 July 2021	37–39	158–159	265–268	461–466
350–400 g	5–10 October 2020	5–14 November 2020	26 April–7 May 2021	30–34	171–173	195–198	396–405
450–500 g	15–20 September 2020	14–22 October 2020	3–9 April 2021	29–32	167–169	175–178	373–377
>500 g	5–10 August 2020	5–11 September 2020	24 February–5 March 2021	30–31	169–174	135–138	334–343

shows that at the same planting time from 20 to 22 March, different initial shoot masses affected the growth rate of pineapple plants, the time it took to reach 28–30 leaves, the flowering period, and fruit formation. This, in turn, directly influenced the time it took to complete the standard flowering treatment, the flowering time, and the time for fruit harvesting of the pineapple. Pineapple plants with varying shoot masses treated for flowering at different times all resulted in a 100% flowering rate. The largest shoot mass (>500 g) achieved the fastest average time from planting to reaching the standard flowering treatment, ranging from 135 to 138 days (4.5 to 4.6 months). Shoot masses of 450–500 g took from 175 to 178 days (5.8–5.9 months) to reach the standard flowering treatment. Shoot masses of 350–400 g took 195 to 198 days (6.5–6.6 months) from planting to achieving the standard flowering treatment. For the smallest shoot mass (200–300 g), a considerable amount of time was needed for pineapple plants to go through the flowering and fruit formation process, taking 265 to 268 days (8.8–8.9 months) to reach the standard flowering treatment. The results indicate that smaller shoot masses require a longer post-planting care period to fulfil the standard flowering treatment, while bigger shoot masses can equate to a significantly shortened time required to achieve the standard flowering treatment.

The time required for flowering treatment and fruit harvesting was highly dependent on the shoot mass used for cultivation. Here, the >500 g treatment showed the earliest flowering treatment in early August (5–10 August) and the earliest fruit harvesting time, from late February to early March (24 February–5 March). The 450–500 g treatment underwent flowering in mid-September (15–20 September) and fruit harvesting from mid-March to early April (19 March–9 April). The 350–400 g treatment experienced the flowering treatment in early October (5–10 October) and fruit harvesting from mid-April to early May (10 April–7 May). The 200–300 g treatment showed the latest flowering treatment, at around mid-December (15–20 December), and the latest fruit harvesting from mid-June to early July (19 June–8 July). Therefore, bigger shoot masses result in earlier flowering treatments and earlier fruit harvesting, while smaller shoot masses lead to later flowering treatment, subsequently delaying fruit harvesting. For pineapple production using these four different shoot masses, the harvesting period will extend from mid-February to early July (19 February–8 July), resulting in a staggered harvest season lasting approximately 4–4.5 months.

The treatments led to a fluctuation in the time from flowering treatment to actual flowering, ranging from approximately 29 to 35 days. The 200–300 g treatment, however, stands out with the longest duration, ranging from 37 to 39 days. This extended timeframe can be attributed to the winter of 2020 arriving earlier and being colder compared to 2019, thereby delaying the pineapple flowering period. The average time from flowering to fruit harvesting ranged from 153 to 166 days in pineapple crop 1 (2019–2020) and averaged from 158 to 174 days in pineapple crop 2 (2020–2021). The time from flowering to fruit harvesting in pineapple crop 2 was longer by 5 to 8 days compared to that in crop 1, depending on the flowering treatment time and annual weather conditions.

The time from planting to fruit harvesting was shortest for the >500 g treatment, averaging 331 to 343 days (11.1–11.4 months). Next was the 450–500 g treatment, with a time range from planting to fruit harvesting of 359 to 377 days (12.0–12.6 months). Then came the 350–400 g treatment, with a time range from planting to fruit harvesting of 380 to 405 days (12.7–13.5 months). Lastly, the 200–300 g treatment showed the longest duration from planting to fruit harvesting, ranging from 449 to 466 days (15.0–15.5 months). Thus, the >500 g treatment displayed the shortest time from planting to fruit harvesting—shorter than that for the 450–500 g treatment by 28 to 34 days, the 350–400 g treatment by 59 to 62 days, and the 200–300 g treatment by 118 to 123 days. Bigger shoot masses result in a shorter time from planting to fruit harvesting, while smaller shoot masses lead to a longer duration.

Pineapples were planted in the spring season (March) in order to shorten the time from planting to harvesting, increase land utilization, and spread the harvesting season from February to May. Therefore, planting various shoot masses weighing 350 g or more will result in different flowering and harvesting times. Shoots should be uniformly sorted by size before planting. If smaller shoot masses (200–300 g) were preferred, planting should be advanced by approximately 3–4 months (around December to January) to allow sufficient time for the flowering treatment, enabling fruit harvesting in the desired months. This helps avoid fruit harvesting in June–July, coinciding with the main harvesting season, causing concentration and consequent challenges in labor and product consumption.

3.2. The Influences of Shoot Mass on the Constituent Factors of Yield and Pineapple Productivity

Table 2. Effects of bud mass on yield components and productivity of pineapple.

Treatments	Number of Harvested Fruits (Fruits/Plant)	Fruit Weight (kg/Plant)	Yield Theoretical (kg/Tree)	Yield Actual (kg/Tree)
2019–2020
200–300 g	278.3 b	0.81 b	220.5 b	38.2 b
350–400 g	292.6 a	0.86 a	242.7 a	42.1 a
450–500 g	290.1 a	0.89 a	249.8 a	43.3 a
>500 g	287.2 a	0.82 b	227.9 b	39.5 b
Significance	**	**	**	***
2020–2021
200–300 g	273.1 b	0.83 b	221.9 b	38.5 b
350–400 g	291.5 a	0.89 a	247.6 a	42.9 a
450–500 g	293.7 a	0.91 a	254.3 a	44.1 a
>500 g	289.2 ab	0.84 b	229.8 ab	39.8 ab
Significance	*	**	**	*
A × B	NS	*	NS	NS

NS: no significant differences; * significant differences at * p ≤ 0.05, ** p ≤ 0.01, and *** p ≤ 0.001; values represent the means of three replicates with 10 fruits (n = 3). Different letters indicate significant differences among the treatments, determined using Tukey’s test. A, effect of treatment (in both years); B, effect of year (in all treatments); and A × B, interaction between A (treatments) and B (years).

presents the yield data for different treatments in two consecutive years (2019–2020 and 2020–2021), categorized by the mass of pineapple shoots. The factors analyzed include the number of harvest fruits per plant, fruit weight per plant, theoretical yield per tree, and actual yield per tree. In both years, there was a significant difference in the number of harvest fruits among the different shoot mass categories (200–300 g, 350–400 g, 450–500 g, >500 g). The treatments with shoot masses ranging from 350 to 500 g generally resulted in a higher number of harvest fruits compared to the 200–300 g category. Similar to the number of harvest fruits, the fruit weight per plant was significantly influenced by the shoot mass. Shoot masses of 350–500 g consistently produced fruits with higher weights compared to the 200–300 g category. The theoretical yield per tree, calculated based on the number of harvest fruits and their average weight, exhibits significant differences between the shoot mass categories. Treatments with shoot masses of 350–500 g show higher theoretical yields compared to the 200–300 g category.

The actual yield per tree, representing the practical results, follows a similar trend. Shoot masses of 350–500 g contribute to a higher actual yield per tree compared to the 200–300 g category. The significance levels, denoted by asterisks, indicate the statistical significance of the differences observed. The higher the number of asterisks, the more significant the difference. The interaction effect between the years and shoot mass categories (A × B) was found to be significant for the fruit weight and theoretical yield. This suggests that the impact of shoot mass on these parameters varied between the two years. In this study, the influence of shoot mass on pineapple yield was investigated over two consecutive years. The results presented in Table 2 demonstrate clear trends in the number of harvested fruits, fruit weight, theoretical yield, and actual yield per tree across different shoot mass categories [22,23]. The interaction effect between the years and shoot mass categories was found to be significant in the fruit weight and theoretical yield. This suggests that the impact of shoot mass on these parameters varies between the two years, emphasizing the dynamic nature of the relationship. In summary, this study demonstrated clear and consistent trends, indicating that optimizing shoot mass, particularly in the range of 350–500 g, positively influences pineapple yield in terms of quantity and weight. The significance of these findings underscores the practical implications for pineapple cultivation strategies. These findings align with previous research highlighting the importance of shoot mass in determining pineapple yield [24].

3.3. Effects of Bud Mass on Quality Indexs of Pineapple

Across both years, the treatment groups exhibited variations in fruit weight, as shown in

Table 3. Effects of bud mass on pineapple mechanical parameters.

Treatments	Fruit Weight (kg/Plant)	Fruit Height (cm)	Fruit Diameter (cm)	Ratio of Edible Parts (%)
2019–2020
200–300 g	0.81 b	12.3 b	9.8	57.6 b
350–400 g	0.86 a	13.2 a	10.2	58.4 a
450–500 g	0.89 a	13.4 a	10.0	58.9 a
>500 g	0.82 b	12.1 b	9.9	57.4 b
Significance	**	**	NS	*
2020–2021
200–300 g	0.83 b	12.4 b	10.1	57.8 b
350–400 g	0.89 a	13.2 a	10.3	58.5 a
450–500 g	0.91 a	13.6 a	10.5	58.7 a
>500 g	0.84 b	12.4 b	9.7	57.5 b
Significance	**	**	NS	*
A × B	*	*	NS	NS

NS: no significant differences; * significant differences at * p ≤ 0.05, ** p ≤ 0.01; values represent the means of three replicates with 10 fruits (n = 3). Different letters indicate significant differences among the treatments, determined using Tukey’s test. A, effect of treatment (in both years); B, effect of year (in all treatments); and A × B, interaction between A (treatments) and B (years).

. In the 2019–2020 season, the 350–400 g and 450–500 g treatments resulted in significantly higher fruit weights compared to the other categories, denoted by the letters ‘a’ and ‘b’. However, in the subsequent season (2020–2021), there was a general increase in fruit weight across all treatments, with the 450–500 g category consistently showing the highest values. The significance of the A × B interaction term suggests that the combined effect of factors A (fruit weight categories) and B (years) was noteworthy. Fruit height and diameter also exhibited variations across treatments and years. In both seasons, the 450–500 g treatment consistently produced fruits with the tallest height and largest diameter. The statistical significance of these parameters emphasizes the reliability of these differences. It is interesting to note that while there were variations in the absolute values, the relative trends seem to be consistent across both years. The ratio of edible parts was a critical parameter, and it was intriguing to observe that, despite variations in fruit weight, the percentage of edible parts remained relatively stable across treatments. This indicates a potential resilience of the trees in maintaining the edible portion, irrespective of the size of the fruit. The statistically significant differences in this parameter should be further explored to understand their implications for yield and quality. The presence of significance underscores the reliability of the observed differences. In summary, the results indicate that the choice of treatment significantly influences various fruit characteristics. Greater shoot masses, particularly in the range of 350–500 g, consistently led to fruits with greater weight, greater height and diameter, and a higher ratio of edible parts. The significance levels reinforce the reliability of these observed differences, and the interaction effect underscores the dynamic nature of these relationships across the two years (

Table 4. Effects of bud mass on biochemical parameters of pineapple fruit.

Treatments	Dry Matter Content (%)	The Vitamin C Content (mg/100g)	Sugar (%)	Bix (%)	Total Acid (%)
200–300 g	19.48 a	25.12 a	16.54 a	18.3 a	0.405 b
350–400 g	19.70 a	26.50 a	16.67 a	18.4 a	0.389 b
450–500 g	17.61 b	22.32 b	14.02 b	16.3 a	0.602 a
>500 g	15.87 c	20.64 b	12.49 c	14.5 b	0.740 a
Significance	**	**	*	*	**
200–300 g	19.73 a	26.27 a	16.23 a	18.5 a	0.389 b
350–400 g	19.94 a	25.88 a	16.92 a	18.8 a	0.362 b
450–500 g	18.06 a	21.93 b	14.73 b	16.9 b	0.536 a
>500 g	16.52 b	20.51 b	13.62 b	15.2 b	0.620 a
Significance	**	**	**	**	**
A × B	*	*	*	*	**

NS: no significant differences; * significant differences at * p ≤ 0.05, ** p ≤ 0.01; values represent the means of three replicates with 10 fruits (n = 3). Different letters indicate significant differences among the treatments, determined using Tukey’s test. A, effect of treatment (in both years); B, effect of year (in all treatments); and A × B, interaction between A (treatments) and B (years).

).

The dry matter content of fruits is a critical parameter influencing their overall quality. In both years, the 200–300 g and 350–400 g treatments consistently demonstrated a higher dry matter content compared to the bigger fruit categories (>500 g). The significant differences highlight the influence of fruit weight on dry matter accumulation. The trend was consistent across both years, suggesting a reliable pattern. Vitamin C content is a key nutritional aspect, and the data show that the smaller fruit categories (200–300 g and 350–400 g) consistently had higher vitamin C contents compared to the bigger fruit categories in both years. This finding aligns with expectations, as smaller fruits often concentrate nutrients more efficiently [25]. The significant levels emphasize the reliability of these differences. Sugar content and brix levels were important indicators of fruit sweetness [26].

The data indicate that, in both years, the smaller fruit categories had higher sugar contents and brix levels compared to the bigger fruit categories. This could have implications for taste and overall consumer satisfaction. The significant levels underline the robustness of these differences. The total acid content is crucial to the overall flavor profile of fruits. In both years, the 450–500 g and >500 g treatments exhibited higher total acid contents compared to the smaller fruit categories. This suggests that bigger fruits may have a more pronounced acidic taste. The significance levels highlight the reliability of these differences. The presence of interaction effects (A × B) across all parameters suggests that the impact of fruit weight on the measured characteristics was consistent across the two years. This strengthens the argument that the observed trends were not isolated to a specific growing season but represent a more general pattern. The findings suggest that, while bigger fruits may have certain characteristics such as a higher total acid content, smaller fruits consistently exhibit superior qualities in terms of their dry matter content, vitamin C content, sugar content, and brix levels. These factors are crucial considerations for both agricultural practices and consumer preferences.

The observed variations in pineapple yield and quality parameters across different shoot mass categories can be attributed to several physiological mechanisms, such as nutrient allocation and assimilation. Plants with larger shoot masses likely have more extensive root systems and a greater leaf area, enhancing their photosynthetic capacity and nutrient uptake [27,28]. This results in better carbohydrate synthesis and storage, which is crucial for flowering and fruit development. Enhanced nutrient assimilation supports the growth of more robust fruits with greater weights [11]. Shoot mass influences the hormonal balance within the plant. Larger shoots might produce higher levels of growth hormones such as auxins and cytokinins, which promote cell division and expansion. These hormones are vital for initiating flowering and supporting fruit set and growth, leading to expedited flowering and increased fruit production [29]. Greater shoot mass might improve the plant’s ability to access and utilize water efficiently. Enhanced water uptake and retention support sustained metabolic activities, critical for flowering and fruiting. Proper hydration ensures that fruits develop optimally, maintaining size and quality [30]. The study’s findings can guide farmers in selecting optimal shoot masses (350–500 g) for planting to achieve higher yields and better fruit quality. By focusing on these categories, farmers can maximize productivity and profitability. These findings align with previous research highlighting the importance of shoot mass in determining pineapple yield. Although direct studies on the specific impact of shoot mass on pineapple growth, flowering, and yield are limited, the review by Fan et al. (2020) provides valuable insights into the shoot mass of fruit plants on plant growth and fruit yield [31]. To further substantiate our results, we draw upon studies from other crops that have explored the relationship between shoot mass and yield. Plants have shown that larger shoot biomass can enhance nutrient uptake and photosynthetic capacity, leading to improved fruit yield and quality [32]. Similarly, a report has demonstrated that optimal shoot mass is crucial for balancing vegetative growth and fruit production, thereby maximizing yield [33].

4. Conclusions

In conclusion, this study on pineapple cultivation with varying shoot masses revealed key insights into growth, flowering, and yield. Shoots weighing 350–500 g were found to be optimal, consistently producing higher harvest numbers, increased fruit weights, and greater yields. Larger shoot masses led to accelerated growth, earlier flowering, and shorter harvest times, aiding the development of efficient planting and harvesting schedules. While larger fruits had higher total acid contents, smaller fruits exhibited superior quality in terms of their dry matter, vitamin C, sugar, and brix levels. These findings highlight the importance of shoot mass in optimizing pineapple productivity, quality, and cultivation practices, providing valuable guidance for farmers and researchers.