Optimal combination of canopy management and planting density for yield enhancement in late-sown cotton

Abstract

Background

Cotton growers often face reduced yield and fiber quality after wheat harvest due to the shortened growing season. The delay in wheat harvest is due to a number of reasons, such as labor unavailability, weather, and machinery constraints. The optimal combination of canopy management and planting density may help in mitigating these problems in late-sown cotton.

Methods

A two-year (2022 and 2023) field experiment was carried out at the University of Agriculture, Faisalabad, Pakistan, using a randomized complete block design with a factorial arrangement comprising two factors. The two planting densities (87489 and 58326 plants ha^− 1) and six canopy management techniques, pruning, manual topping, chemical topping, and their combinations.

Results

Cotton growth, yield, and fiber quality were greatly influenced by these techniques. Chemical topping plus pruning increased sympodial branches up to 38%, and seed cotton yield at higher planting density. In contrast, manual topping plus pruning outperformed other methods in improving fiber uniformity and strength.

Conclusions

The results showed that a combination of chemical topping plus pruning enhances seed cotton yield, whereas manual topping integration with pruning improved fiber quality. Finding suggests the importance of selecting an optimal combination according to production needs under a cotton wheat cropping system in late sown conditions.

Introduction

Cotton (Gossypium hirsutum L.) is one of the most important natural fiber cash crops globally and plays an important role in the economic sector of Pakistan [1, 2]. Cotton production depends on different factors such as environment, when to plant, superior variety, and advanced agricultural practices [3, 4]. Changing sowing date causes variations in temperature, light, and environments directly impacting growth [5]. The reason for late sowing is most often the delayed harvest of the preceding crop, resulting in late-sown cotton experiencing greater temperature at the seedling [6], low temperature at the boll development and flowering stage [7]. The suboptimal temperature conditions at the reproductive stage result in inferior fiber quality [8]. These temperature variations at different growth stages collectively reduce cotton yield and deteriorate fiber quality. These problems require agronomic interventions that can optimize resource use efficiency and crop architecture under late sown conditions.

Cotton has an indeterminate growth habit with simultaneous growth of vegetative and reproductive parts; the balance between these branches determines the yield percentage [9, 10]. Vegetative branches (VBs) are monopodial, which remain indeterminate during cotton development [11] and give rise to sympodial branches at leaf axils [12]. Sympodial branches (SBs) are mainly responsible for yield [13]. The monopodial branches create a larger plant structure, making the harvest process difficult [14]. During the short growing period, the excessive vegetative growth increases leaf area index and canopy shading, thereby restricting light penetration into the lower canopy, which impairs boll retention and accumulation of reproductive biomass [15].

Hence, the canopy management practice offers a promising solution for maintaining the reproductive efficiency of cotton. Manual topping, chemical topping, and pruning have been widely studied as solo interventions for plant regulation [16]. Manual topping is a method to control excessive vegetative growth [17], enhance defense against pests [18], inhibit apical dominance, and promote assimilate allocation toward reproductive organs [19]. A high number of laborers is required for manual toping, and meeting such a large labor number is difficult now due to laborers’ migration toward cities, reducing the quantity and quality of farm labor [20]. Therefore, chemical topping uses growth regulators such as mepiquat chloride, which offers a practical solution for limiting excessive stem elongation, promoting compact canopy structure [21], and inhibiting apical dominance [22]. This technique reduces labor cost, compact plant structure, and improves seed quality [23, 24]. The pruning of vegetative branches cuts off the unproductive biomass and improves the light distribution and boll development [25]. The combined effect of these techniques was evaluated to determine whether they would be able to enhance cotton productivity and fiber quality.

Plant density affects canopy structure and plant architecture [26]. The optimal density improves light utilization by changing leaf area index [27], increases lint yield and boll density [28]. Planting density influences competition for water, nutrients, and light [29]. The higher planting density may increase yield but also promote canopy congestion, creating a favorable microclimate that enhances the incidence of sucking pests such as leaf hoppers and whiteflies [30]. This may even get worse under late-sown cotton, where vegetative and reproductive growth overlap under declining temperature. Literature suggests the efficiency of growth regulators and pruning practices may vary under different planting densities, but their combined effect remains insufficiently understood in late-sown field conditions.

Although the effects of plant density on yield formation and VB development are investigated by researchers [25, 31], limited research has been carried out on the interactive effects of planting density and canopy management techniques under late sown conditions. Specifically, the combined manual and chemical topping application has not been vigorously studied in a pictorial framework. Moreover, the majority of the existing studies have evaluated these practices independently under optimal sowing conditions, not in late sown conditions. Therefore, this study aims to assess the interactive effects of different canopy management practices and planting densities on growth, yield, and fiber quality under field conditions in late sown cotton. The findings are expected to demonstrate practical application for optimizing canopy architecture and improving productivity in late sown conditions under cotton wheat cropping systems. Figure 1 represents the graphical abstract of the study.

Fig. 1.

The graphical abstract of the study representing the reason for late sowing of cotton and possible solution to manage cotton crop for better yield

Materials and methods

Field experimentation

A two-year field experiment was carried out during 2022 and 2023 at the Agronomic Research Area at the University of Agriculture, Faisalabad, Pakistan (31.4294° N and 73.0750° E). The average rainfall and temperature during the cotton growing seasons of 2022 and 2023 are shown in Fig. 2. The cotton cultivar (FH-333; developed by Ayub Agricultural Research Institute, Faisalabad, Pakistan) was purchased from Punjab Seed Corporation, Lahore, Pakistan. This cultivar possesses a medium-tall stature with large leaves. This is a registered and approved cultivar by the Federal Seed Certification and Registration Department, Pakistan. It is permitted for cultivation in the Punjab region of Pakistan; therefore, no special permission is required for its cultivation. The crop was sown on June 1st during both years to simulate late sown conditions after wheat harvest. The field trials were laid out in a randomized complete block design (RCBD) with a factorial arrangement consisting of two planting densities and six canopy management treatments. Each replication contains 12 treatments that were randomly allocated to experimental plots, making a total of 36 experimental plots. Each experimental plot has seven rows (0.75 m), and the outer two served as border rows (0.37 m each) while the central one served as the net plot area for data collection. The effective plot width was 4.5 m. The irrigation channel, non-experimental plot, and non-experimental areas were maintained uniform size to ensure uniform water distribution and minimize border effects.

Fig. 2.

Weather characteristics of the experimental site during the two growing seasons

Planting density treatments

The planting density was maintained at two levels.

• D₀:87,489 plants ha− 1 (row spacing 75 cm × plant spacing 15 cm)

• D₁:58,326 plants ha− 1 (row spacing 75 cm × plant spacing 22 cm)

Canopy management treatments

Canopy management has six levels, and all treatments were applied on the same day to ensure uniform crop growth among all treatments.

• C₀ (Control): no pruning and topping

• C₁ (Pruning): removal of all monopodial branches from the main stem at 70 days after sowing (DAS)

• C₂ (Chemical topping): mepiquat chloride application at 70 DAS at the rate of 120 g ha− 1 to suppress apical dominance

• C₃ (Manual topping): physical removal of apical bud at 70 DAS from the main stem

• C₄ (Chemical topping + pruning): integrating mepiquat chloride application (120 g ha− 1) and monopodial branches at 70 DAS

• C₅ (Manual topping + pruning): integrating manual removal of the apical bud and monopodial branches at 70 DAS

Crop management practices

Cotton was sown via the manual dibbling method. The seed rate was 20 kg ha^− 1 with a row-to-row distance of 75 cm and plant-to-plant distances of 15 and 22 cm for D₀ and D₁, respectively. Irrigation was performed at 7–20-day intervals starting from 7 DAS. The recommended doses of phosphorus, potassium, and nitrogen were applied in the form of MOP, DAP, and urea at rates of 75, 88, and 200 kg/ha, respectively. Half of the nitrogen was applied as a basal dose, and the remaining half was applied 30 DAS.

The composite soil samples were collected before sowing and analyzed at the Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad, to determine physiochemical properties (Table 1). Glyphosate (2.5 L/ha) was used as a post-emergence herbicide for weed control. Insecticides and pesticides were used on the basis of the severity of pest or bollworm attacks. Acetamiprid at 300 g/ha was used for the control of white fly adults, aphids, and mealy bugs during the whole growing season. Dinotefuran was used at 250 g/ha to control Jassid during the crop-growing season. Methoxyfenozide at 500 ml/ha was used for the control of armyworm. Spintoram at 125 ml/ha was used for the control of thrips and bollworms. Based on the infestation level, insecticides and pesticides were applied throughout the growing season.

Table 1.

Soil physicochemical attributes of the experimental site during 2022 and 2023

Characteristics	2022	2023
Sand (%)	52.2	52.5
Silt (%)	27.1	27.0
Clay (%)	19.1	19.0
Texture class	sandy clay loam	sandy clay loam
Saturation percentage (%)	36.0	35.8
pH	7.8	7.9
ECe (dS m− 1)	0.38	0.39
Available phosphorous content (mg·kg− 1)	23	22.8
Available potassium content (mg·kg− 1)	186	185
Organic matter content (%)	1.43	1.41
Total nitrogen content (%)	0.07	0.068

Data collection

Data were collected for agronomic parameters such as plant height (cm), monopodial branches per plant, sympodial branches per plant, bolls per plant, seed cotton yield (kg ha^− 1), seed index (g), and seed oil content (%). The cotton fiber quality parameters, such as short fiber index (SFI %), breaking elongation (%), fiber strength (g/tex), fiber length (mm), uniformity index (%), and micronaire, were also measured using standard procedures.

Agronomic and yield parameters

Five randomly tagged plants were selected in each plot (36 plots) for the measurement of plant height, bolls per plant, and branch count. The plant base and tip heights were measured in cm from five different tagged plants from every plot. Seed cotton yield was evaluated by two manually picking at maturity each year. Then, it was weighed after being thoroughly dried under the sun. The total seed yield (kg ha^− 1) was determined for each plot. One hundred randomly selected fuzzy seeds were weighed in grams, and the results provided a seed index.

Fiber quality attributes and oil contents

Fiber quality traits were determined using a high-volume instrument (HV1-900 Zellwegar Uster Ltd., Switzerland) at the Department of Fiber and Textile Technology, University of Agriculture, Faisalabad. The ASTM standard (1997) procedure was adopted. The length at 2.5% span length was considered the fiber length. The 2.5% span length and 50% span length were measured via an optical system through the HVI-900 length module. The 2.5% span length was determined and interpreted in mm. The micronaire is essentially the measurement of fiber weight in µg per unit length of fiber. The pressure gradient around the chamber helps to evaluate the micronaire value as the air stream is transferred via a given weight of fiber contained in the chamber of a fixed volume of module 920. In this way, fiber fineness (micronaire) was determined and interpreted in µg/inch. The ratio of the breaking strength of a bundle of fibers to its weight is the fiber ratio. The length/strength module-920 of HVI-920 is used for measuring the fiber strength via the principle of the contrast rate of force application on the clamped fiber of the sample taken for fiber length measurements. The fiber strength was determined and interpreted in g tex^− 1.

The fiber uniformity ratio was calculated via the formula

HVI-920 was also used for the measurement of fiber strength.

The Soxhlet method was used for oil extraction. The first 20-gram sample was finely ground and sun-dried, and then placed in a cellulose thimble, and hexane was used as the solvent. Then, the thimble was placed in the apparatus and run for 7 h. After extraction, the solvent was evaporated, and the extracted oil was dried to remove residual hexane. The oil content was calculated via the following formula:

Economic analysis

Economic analysis was carried out as per Fan et al. [32]. All the agronomic practices, including land preparation, irrigation, fertilization, crop protection, and harvesting, were included in the fixed cost. The fixed cost was averaged for 2022 and 2023, and it was US$ 819.47 per hectare. Cost of seed, pruning, chemical topping, and manual topping were included in variable cost as per treatment. Net returns were calculated by subtracting total cost from gross income. While the benefit-cost-ratio was calculated by dividing gross income by total cost.

Statistical analysis

Data from both years were pooled after testing for year effects and subjected to combined analysis of variance via Fisher’s ANOVA, and Tukey’s honestly significant difference (HSD) test at a probability of 5% to evaluate the effect of planting density, canopy management, and their interaction. The data were examined for compliance with model assumptions before ANOVA. Outliers were screened using standardized residuals (± 3 SD). Data was tested for normality using Shapiro-Wilk test before ANOVA for homogeneity of variances using Levene’s test. R Studio 4.6.1 (R Studio, Boston, MA, USA) was used with factoextra and ggplot2 packages to perform principal component analysis (PCA) and correlation matrix. Additionally, Microsoft Excel 365 was used for graphical illustrations.

Results

Plant height (cm)

The ANOVA results of the two-year combined study revealed that planting density and canopy management practices have a significant effect on plant height, and their interaction was non-significant (Table 2). Among canopy management treatments, the maximum plant height was observed in the control plot (111.31 cm). The lowest percentage was 33% under chemical topping plus pruning, followed by pruning alone (16%), compared with the control (Fig. 3A and B). With increasing canopy manipulation intensity, the height generally decreased.

Table 2.

F values of various parameters of cotton crops subjected to various canopy management techniques and grown at two densities

Parameters	Planting density	Canopy management technique	Planting density × Canopy management technique
Plant height (cm)	5.8*	20.3**	1.15ns
Number of monopodial branches	17.05**	1093.32**	3.71*
Number of sympodial branches	24.8**	75.47**	1.72ns
Bolls per plant	22.36**	36.20**	2.43ns
Seed index (g)	43.63**	0.98ns	0.14ns
Seed cotton yield (kg ha− 1)	95.32**	48.03**	4.11**
Seed oil contents (%)	8.31**	28.36**	0.21ns
Short fiber index (%)	7.92*	69.48**	0.25ns
Breaking elongation (%)	9.25**	14.20**	0.21ns
Fiber strength (g/tex)	4.74*	4.85**	0.08ns
Fiber length (mm)	11.37**	2.12ns	0.06ns
Uniformity index (%),	12.82**	20.75**	0.6ns
Micornaire	15.27**	4.74**	0.23ns

*Significant

**Highly significant, ns non-significant

Fig. 3.

Influence of various canopy management techniques and planting densities on cotton parameters. (A) Plant height (cm) under different management techniques; (B) Plant height under two planting densities; (C) Number of monopodial branches; (D) Number of sympodial branches under management techniques; (E) Number of sympodial branches under planting densities; (F) Bolls per plant under management techniques; (G) Bolls per plant under planting densities; (H) Seed cotton yield (kg ha⁻¹); and (I) Seed index. Planting densities were D0: 87489 plants ha-1 and D1: 58326 plants ha-1. The data are the means of 2 years (2023 and 2024). Similar letters indicate statistically insignificant (P≥0.05) differences among treatments, whereas bars above the mean represent the standard error of three replications

Monopodial branches per plant

The results from both years of study revealed that both treatment and their interaction had a significant effect on the number of monopodial branches per cotton plant (Table 2). Manual topping has the maximum number of branches under the D₁ planting density, followed by chemical topping, with 2.97 branches per plant. Control has the number of branches, whereas pruning and pruning combined with chemical and manual topping have 0 branches due to deliberate removal as a part of treatment. The maximum number of branches was observed at D₁ planting density compared with D₀. Moreover, the significant interaction indicated that monopodial branches to canopy management response varied with planting densities (Fig. 3C).

Sympodial branches per plant

The results revealed that canopy management treatment and planting density had a significant effect on the number of sympodial branches, whereas the interaction remained non-significant (Table 2). Among treatments, there was a 6% increase in sympodial branches at D¹ as compared with D₀. In the canopy management treatment, the greatest increase of 38% was observed in the pruning plus chemical topping treatment, and the minimum increase of 4% was observed in the pruning alone treatment compared with the control (Fig. 3D and E). A notable increase in sympodial branches was recorded under all canopy management treatments, with the topping plus pruning treatment having a more pronounced effect than pruning alone.

Bolls per plant

The results indicated that canopy management treatment and planting density had a significant effect on the number of bolls, whereas their interaction remained nonsignificant (Table 2). The number of bolls increased by 15% at D₁ compared with D₀. For the canopy management treatment, chemical topping plus pruning showed an increase of 39% relative to the control. This was followed by manual topping plus pruning, which increased the boll number by 28%, whereas manual topping alone resulted in only 2% increase as compared with the control (Fig. 3F and G). Compared with those in the control treatment, the boll numbers in the topping pruning treatment consistently increased, either alone or in combination. The non-significant interaction confirms that uniform treatment responses occurred across both planting densities.

Seed cotton yield (kg ha^− 1)

The analysis of variance revealed a significant interaction effect of canopy management, planting density, and individual treatment on seed cotton yield (Table 2). In terms of the canopy management technique, chemical topping plus pruning resulted in 94% and 89% greater yield at D₀ and D₁ planting densities, respectively, compared with the control (Fig. 3H). This was followed by manual topping plus pruning, which increased D₀ by 80% and D₁ by 46% in chemical topping. At a lower planting density D₀, a greater seed cotton yield was observed. The significant interaction shows that the effect of the canopy management treatment on yield varied with planting density.

Seed index (g)

The results indicated that only planting density had a significant effect on the seed index, whereas canopy management treatment and their interaction were non-significant (Fig. 3I). The D₁ planting density had a greater seed index of 7.95 g than those at D_0, which was 7.33 g, 8.45% increase under denser planting density. The results indicated that there was no consistent trend in the effects of canopy management practices on the seed index.

Seed oil content (%)

Plant density and canopy management treatments have highly significant effects on the oil content during both years of study, whereas the interaction effect remains statistically non-significant (Table 2). Compared with D₀, D₁ resulted in a 3% greater oil content. Tukey’s HSD test (P < 0.05) revealed that a homogeneous mixture had a pronounced effect on the oil content. In terms of canopy management techniques, a significant difference was observed among the treatments, with the highest oil content recorded during pruning, with a 6% increase in oil content compared with that of the control (Fig. 4A and B). On the other hand, the lowest oil content was recorded for chemical topping plus pruning, with a reduction of 15%, followed by chemical topping alone, reflecting an 8% decrease compared with that of the control. The results confirmed the superiority of pruning alone in enhancing the oil content, whereas chemical topping plus pruning reduced the oil content.

Fig. 4.

Influence of canopy management techniques and planting density on cotton seed oil and fiber quality traits. (A) Seed oil contents (%) under management techniques; (B) Seed oil contents under planting densities; (C) Short fiber index (%) under management techniques; (D) Short fiber index under planting densities; (E) Breaking elongation (%) under management techniques; (F) Breaking elongation under planting densities; (G) Fiber strength (g/tex) under management techniques; (H) Fiber strength under planting densities; (I) Fiber length (mm) under planting densities; (J) Uniformity index (%) under management techniques; (K) Uniformity index under planting densities; (L) Micronaire under management techniques; and (M) Micronaire under planting densities. Planting densities were D0: 87489 plants ha-1 and D1: 58326 plants ha-1). Data are the mean of 2 years (2023 and 2024). Similar alphabets showing statistically insignificant (P≥0.05) difference among treatments, while bars above the mean represents standard error of three replications

Fiber quality parameters

Short fiber index (SFI %)

The analysis of variance revealed a significant effect of planting density and canopy management technique on the short-fiber index, whereas the interaction remained non-significant (Table 2). Among the canopy management techniques, the control plot had a high SFI value. In contrast, all canopy management techniques had a negative influence on the short-fiber index. Manual topping plus pruning reduced SFI by 22%, and chemical topping plus pruning reduced 8% compared to the control (Fig. 4C and D). When the planting density D₁ was reduced to D₀, the short-fiber index decreased from 8.22% to 8.02%, with a slight reduction of 2%.

Breaking elongation (%)

The results of the ANOVA revealed that the canopy management technique and planting density had a significant effect on the percentage of fiber elongation, with no significant interaction (Table 2). For the canopy management technique, the greatest fiber elongation was recorded under the chemical topping plus pruning treatment, followed closely by the manual topping plus pruning treatment and the manual topping treatment, with rates of 10%, 9%, and 8%, respectively (Fig. 4E and F). In contrast, the lowest elongation was recorded in the control treatment. Pruning and chemical topping alone resulted in intermediate increases of 3% and 6%, respectively. The findings revealed that, compared with the control and single treatments, the combination of pruning with chemical and manual topping significantly increased fiber elongation, with further improvement, which was supported by the lower planting density D₁.

Fiber strength (g/tex)

A statistical analysis revealed a significant effect of the canopy management technique and planting density on fiber strength (Table 2). A lower fiber strength was detected in the control plot, whereas pruning alone and chemical topping with pruning slightly improved the fiber strength to less than 1%. Conversely, the maximum strength was observed under manual topping plus punning, followed by manual topping alone and chemical topping, representing 5%, 4%, and 2% improvements over the control (Fig. 4G and H). The planting density also had a significant effect on the D₁ plating density, with 1.6% more fibers than D₀. Overall strength improved under low planting density in manual topping plus pruning.

Fiber length (mm)

ANOVA revealed that planting density significantly affected only the mean length of cotton fibers, while no effect of canopy management or its interaction was recorded (Table 2). Tukey’s HSD test (P < 0.05) revealed that the two densities had individual groups, which confirmed a significant difference between them. Compared with D₀, D₁ improved the fiber length by up to 4% (Fig. 4I).

Uniformity index (%)

The ANOVA revealed a significant influence of the planting density and canopy management technique on fiber uniformity; the interaction effect was non significant (Table 2). Across canopy management techniques, manual topping plus pruning resulted in a 3.19% improvement, followed by chemical topping plus pruning, with a 3.10% improvement over the control. A modest improvement of 0.87% was shown by manual topping. Compared with the control, the low planting density slightly improved the uniformity index, with a 0.79% increase. These results indicated that combining manual or chemical topping with pruning improved the uniformity index, which was further enhanced by a low planting density D₁ (Fig. 4J and K).

Micronaire

The factors of both planting density and canopy management technique had a significant impact, and their interaction remained non-significant (Table 2). Among the canopy management techniques, the highest micronaire value was recorded for manual topping plus pruning, with a 1.70% increase over control. Treatments such as pruning alone and chemical topping plus pruning resulted in no improvement. Planting density D₁ increased micronaire by 3%compared with D₀ (Fig. 4L and M).

Correlation matrix and principal component analysis

A correlation matrix revealed significant relationships between the cotton agronomic and quality parameters (Fig. 5). The findings from the analysis revealed that plant height has a strong positive correlation with sympodial branches and fiber elongation, but a negative relationship with the uniformity index. Additionally, the number of sympodial branches was positively correlated with yield, the seed index, and the number of bolls per plant, indicating its importance in increasing yield. Among the quality parameters, the short fiber index was strongly negatively correlated with elongation. The uniformity index has a negative correlation with the short-fiber index, indicating that a relatively high short-fiber content has an adverse effect on fiber uniformity. The analysis revealed a complex interrelationship among fiber and agronomic parameters by emphasizing the critical role of sympodial branches and strength and elongation from quality traits in ensuring overall cotton productivity under the studied agronomic treatments.

Fig. 5.

Correlation matrix and principal component analysis indicating the relationships among the different parameters under study. Height: Plant height, Mono: Monopodial branches, Sym: Sympodial branches, Boll: Bolls per plant, SI: Seed index, Yield: Yield kg per hectare, Oil: oil content, SFI: short fiber index, Elg: Fiber elongation (%), Str: Fiber strength (g/tex), Len: Upper Half Mean Length (mm), UI: Fiber uniformity index (%), Mic: Micronaire

To evaluate the relationships between fiber traits and agronomic quality parameters, principal component analysis (PCA) was performed (Fig. 5). From the biplot diagram, the performance was measured across PC1-41.2% and PC2-20.2%, resulting in a total variation of 61.4%. The correlation circle comprised four major groups in which sympodial branches (Sym), elongation (Elg), and yield were closely related in the first group. Moreover, monopodial branches (Mono) were in contrasting quadrants, forming an adversarial relationship with fiber traits such as elongation (Elg) and strength (Str). However, with respect to PC2 plant height, the seed index (SI) and oil content had lower contributions, limiting their role in the overall plot. These findings highlight elongation, yield, and sympodial branches as strong traits for increasing cotton efficiency.

Economic analysis

The clear profitability among different treatments is given in this economic analysis (Table 3; Fig. 6). The average production cost of two growing seasons was US$ 819.47 ha^− 1. The only cost variation was among topping and pruning treatments. The combined canopy treatment gave a higher economic return density compared to the control at high planting. The benefit cost ratio (BCR) was 1.96 with the highest gross income of US$193.55 ha^− 1 despite having high variable costs. This was followed by manual topping plus pruning treatment, which recorded a net return of 800.69 ha-1 US$, and a BCR of 1.81. Same at lower planting density combination of treatment outperformed the control treatment with the highest net return of (US$ 745.60 ha^− 1) in chemical topping plus pruning and BCR of 1.78. The control treatment has a marginal BCR close to unity (1.01), indicating minimal economic gains without agronomic interventions. However, variable costs increased, but the corresponding increase in gross income with superior profitability compensated for these costs. These results showed that by integrating canopy management practices, farmer can not only enhance their profitability but also yield in late sown cotton.

Table 3.

Economic analysis (US$) of the late sown cotton subject to various pruning and topping treatments under different planting densities

Planting density	Pruning and topping treatments	Variable cost	Total cost	Gross income	Net returns	BCR
87,489 plants ha⁻¹	Control	88.93	908.40	987.92	79.53	1.09
	Pruning	128.46	947.92	1388.18	440.26	1.46
	Chemical Topping	123.90	943.36	1627.77	684.40	1.73
	Manual Topping	128.46	947.92	1467.84	519.91	1.55
	Chemical Topping + Pruning	163.42	982.89	1930.55	947.66	1.96
	Manual Topping + Pruning	167.98	987.45	1788.14	800.69	1.81
58,326 plants ha⁻¹	Control	59.29	878.75	891.09	12.34	1.01
	Pruning	98.81	918.28	996.57	78.29	1.09
	Chemical Topping	94.25	913.72	1307.76	394.04	1.43
	Manual Topping	98.81	918.28	1076.31	158.03	1.17
	Chemical Topping + Pruning	133.78	953.25	1698.84	745.60	1.78
	Manual Topping + Pruning	138.34	957.81	1174.40	216.59	1.23

BCR benefit-cost-ratio

Fig. 6.

Economic analysis (US$) of the late sown cotton subject to various pruning and topping treatments under different planting densities

Discussion

Canopy management and planting density have a significant impact on growth, fiber quality, and yield in a late sowing scenario. The plant architecture is an important factor in modern mechanized farming to enhance yield [33]. The study states that yield is not only assured by individual management practices, but it also has a strong interaction with planting density [34]. Our study found a yield increase under chemical topping plus pruning at high planting density.

The yield enhancement in canopy management treatment is closely related to an increase in boll number and sympodial branches, with boll number (on average, 90%) of lint yield, whereas boll mass accounted for 10% of lint yield on average [35]. Previous studies showed improvement in boll retention using growth regulators and topping treatment, which also aligns with the present study that removing unproductive branches increases biological yield and canopy photosynthesis, but it depends on planting density due to low reproductive portioning [36]. This integrated approach appears beneficial for late sowing, where the crop has limited time to compensate for excessive vegetative growth. Yield increases up to the optimum level at the number per area rather than improvement in individual boll or fiber traits [37]. This approach shows the importance of population-driven yield compensation under late-sown cotton.

The application of plant growth regulators (PGRs) in chemical topping plays an important role in regulating plant response [38]. PGRs such as flumetralin and mepiquat chloride change the canopy structure by shortening internodes, reducing plant height, increasing light distribution, and causing improved boll number [39, 40]. MC functions as a gibberellin inhibitor that suppresses leaf expansion, stem growth, and internode elongation, leading to a compact plant structure that offers efficient light interception [41, 42]. A previous study noted that MCs increased photo assimilation movement toward reproductive organs and restricted vegetative overgrowth to maximize reproductive biomass and lint yield during a short growing period [43]. The study observed 12.2% higher yield in chemical topping than that under manual topping [44].

When chemical topping was compared with the control and manual topping, both methods yielded lower yields. The results of this study prove that canopy management significantly impacts yield but deteriorates fiber quality in late-sown cotton. Our study aligns with that of Li et al. [45], who reported that, compared with manual topping, chemical topping reduces plant height by inhibiting apical dominance and causing an increase in yield. Yield is determined by assimilating movement toward reproductive tissue [46]. Compared with manual or no topping, a medium concentration of chemical topping increased yield by 24.1 to 29.2% and plant architecture, indicating the best balance of yield and plant structure [47]. These authors reported that when mepiquat chloride was used, the yield increased to 19–29% compared to the control. In comparison, Tung et al. [43] reported the opposite result, indicating that the application of MC caused a 6–29% reduction in yield compared with that of the control because of less biomass accumulation in reproductive organs. Chemical topping enhances light penetration in the cotton canopy, which results in the development of bolls that help to maintain yield and quality [48, 49].

The canopy management strategies may not be individually beneficial, but planting density integration boosts yield in late sowing conditions. The highest yield was recorded under high planting density (D₀), compensated by the adverse effect of late sowing on plant population. A study reported by Alfaqeih et al. [50] revealed that the number of monopodial branches was greater at high planting densities than at low densities and that there was a decrease in the number of monopodial branches. This is due to natural competition between plants for nutrients and light. Reddy et al. [51] revealed that among higher planting densities (55,555 plants ha^{− q}), moderate planting densities (37037 plants ha^{− 1}), and lower planting densities (18518 plants ha^{− 1}), moderate planting densities produced more sympodial branches than lower densities. The same results were reported by Shekar et al. [52], who reported that a high planting density resulted in low yield per plant, but it was compensated for by plant population per hectare, indicating a compensatory plant response increasing overall yield.

In contrast, fiber quality parameters expressed sensitivity to canopy management practices. The chemical topping treatment has improved yield attributes at the expense of some fiber quality traits. At the same time, manual topping plus pruning has improved fiber traits. Chemical topping increased seed cotton yield but didn’t affect cotton fiber quality compared to manual topping [44]. Among all canopy management treatments, the topping treatment was found to be the best at improving cotton quality compared with chemical topping, which is consistent with the findings of Yasar et al. [53], who reported that topping after 100 days improved fiber length but had no significant effect on yield, SFI, elongation, or fiber fineness. Dong et al. [54] reported that removing basal branches during the squaring stage increased plant height, plant biomass, fiber strength, and micronaire. A study by Wu et al. [47] revealed that the cotton structure was improved by regulating growth, increasing boll counts, and increasing fiber strength. This treatment combines pruning with chemical topping to increase resource allocation to fruiting branches and increase yield and bolls [14]. Mohammed HA [55] reported that a relatively high concentration of chemicals reduces the fiber strength and elongation rate of cotton, which ultimately reduces the overall fiber quality. This yield improvement mechanism lies in resource allocation by removing the top of cotton growth toward the productive part, which improves yield efficiency and boll production by reducing boll abscission [56]. More controlled growth was observed in manual pruning, as selective removal enables resources to be focused on a desired characteristic without adversely affecting growth, such as chemical topping, hence increasing cotton quality parameters [47]. Although genetic factors are mainly responsible for controlling oil content and fiber traits, they are also influenced by canopy structure and resource distribution when plants are pruned. Jalilian et al. [57] reported that at higher plant density, the lint yield is increased, but the oil content and some quality parameters are reduced compared with those at low planting density. The results support the old literature stating that aggressive growth regulation can alter assimilate distribution, potentially influencing fiber development.

The results show a trade-off between fiber quality improvement and yield maximization. The alternative to manual toping is chemical toping, which is labour efficient and more suitable for areas where labour availability is limited [19]. Conversely, manual topping plus pruning is more labor-intensive but more suitable for premium fiber quality, which can be traded for high labor cost. The economic analysis was conducted, and the labor requirements and input costs should be considered when translating these findings into farm-level recommendations.

Manual topping and pruning are more effective in regulating the canopy, and their adaptation is not possible on a large scale due to operational inefficiency, time, and labor availability. But chemical topping offers a uniform alternative solution under a high planting density system with improved yield. The economic analysis revealed that chemical topping plus pruning is profitable, though farmers need to bear additional management costs, which can be outweighed by higher seed cotton yield. This approach is an economically viable strategy in a late-sown cotton system.

The study has certain limitations despite having promising outcomes. The study was conducted at a single location over two growing seasons, which shows its limitation for application across diverse agroecological zones. Moreover, economic analysis, labor efficiency, and long-term crop response were not evaluated. Future research should emphasize research on multi-location trials, integrate cost-benefit analyses, and also add some physiological measurements to elucidate the mechanisms underlying canopy management effects in late sown cotton sowing.

Conclusions

This study evaluated that planting densities and canopy management methods interactively influence growth, yield, and fiber quality of late-sown cotton under field conditions. The chemical topping plus pruning has been the most effective among all treatments in improving boll number, sympodial branch development, and seed cotton yield at high planting densities. Whereas manual topping plus pruning improved fiber qualities such as fiber strength, elongation, and uniformity.

The results showed that canopy management techniques should be selected for a specific production purpose. The practices to increase yield are different from those used for optimizing fiber quality. The results further highlight the importance of interaction between canopy management and planting density in increasing cotton yield. This offers a balanced crop performance under a short growing season in a cotton-wheat cropping system.

This study was conducted at a single location for a period of over two years. Future research should focus on diverse environments, economic assessments, and multi-regional trials to refine canopy management techniques in a late-sown cotton production system.

Authors’ contributions

Conceptualization, Fahd Rasul; methodology, investigation, Fahd Rasul, Muhammad Abu Bakar Hayat; data curation, Muhammad Abu Bakar Hayat; writing—original draft preparation, Muhammad Abu Bakar Hayat, Fahd Rasul; writing—review and editing, Fahd Rasul, Muhammad Zia Ul Haq, Muhammad Abu Bakar Hayat, Muhammad Talha Aslam, Muhammad N. Sattar, Sallah A. Al Hashedi, Abdul Ghafoor, Muhammad Munir. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Deanship of Scientific Research, King Faisal University, Saudi Arabia, grant number KFU260162 and the Research, Development and Innovation Authority (RDIA), Saudi Arabia through grant number (12877-KFU-R-2-1-SE-).

Data availability

The data are available from the corresponding author and can be furnished upon request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.