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Current IssueSpecial IssueEditorial BoardOnline First ArticlesArchive

Full Research Article

End-trimming Applied after Flowering Changes Canopy Structure and Photosynthetic Production in Soybean

S
Sesil Hong1,2,#
K
Kieun Song1,3,4,#
H
Hee Chan Ahn2
S
Seung Jun Kim2
S
Seung Hyeon Park2
S
Seung Hyeon Park2
S
Sangin Shim1,3,4,*
1Department of Agronomy, Gyeongsang National University, Jinju 52828, Korea.
2Division of Applied Life Science, Gyeongsang National University, Jinju 52828, Korea.
3Institute of Agricultural and Life and Sciences, Gyeongsang National University, Jinju 52828, Korea.
4Research Institute of Life Sciences, Gyeongsang National University, Jinju 52828, Korea.

  • Submitted23-08-2026|

  • Accepted03-10-2026|

  • First Online 15-10-2026|

  • doi 10.18805/LRF-977

ABSTRACT

#Co-first author.

Background: Global warming has accelerated vegetative growth in soybeans, delayed maturation and reduced seed quality. To address these challenges, this study investigated the effects of end-trimming the upper canopy after flowering on soybean growth and yield.

Methods: End-trimming was conducted at the R2 stage (full flowering) using a trimmer at different intensities based on canopy height: no trimming (T0), - 10 cm (T1), - 20 cm (T2) and - 30 cm (T3). Plant growth, pod formation, seed development and physiological responses were evaluated across treatments.

Result: Trimming reduced plant height, with no recovery in later stages. Moderate trimming (T1) enhanced pod formation and seed growth, yielding the highest pod number and weight, while excessive trimming (T3) resulted in fewer and lighter pods compared to the control. End-trimmed plants showed higher photosynthetic rates and improved light penetration to the lower canopy, which promoted photosynthesis and sink activity, ultimately contributing to better seed development.

INTRODUCTION

Soybean [Glycine max (L.) Merr.] is one of the most widely cultivated crops worldwide due to its high protein and lipid content, serving both as food and as raw material for products such as soap, pharmaceuticals and industrial ink. The yield potential of soybean is largely determined by canopy light interception, biomass conversion and partitioning to grains (Quijano and Morandi, 2023). Because growth habits differ between determinate and indeterminate types, grain setting becomes complex. In particular, the leaf area index (LAI) strongly influences canopy photosynthesis; however, excessive leaf area can reduce yield since respiration may surpass photosynthesis and shading limits the activity of lower leaves. Given the challenges posed by climate change and population growth, securing a stable soybean supply has become increasingly urgent (Corrales et al., 2022). Although positive correlations exist between leaf area, biomass and yield (Liu et al., 2008), overly dense canopies hinder light penetration and reduce efficiency. Moreover, climate change has led to persistent rainfall during the flowering period, resulting in excessive vegetative growth and lodging, as well as yield losses due to restricted efficient translocation of photosynthate; consequently, a scientific analysis of the effects of end-trimming is required.
       
To address these limitations, end-trimming has been introduced as a practice that modifies canopy structure. This technique improves photosynthetic efficiency, enhances translocation of assimilates to reproductive organs and reduces lodging by removing excess leaves and stems (Nie et al., 2021; Yang et al., 2023; Philbrook and Oplinger, 1988). Nevertheless, its effectiveness depends greatly on timing and method and despite being a customary practice among Korean farmers, scientific research on its impact remains scarce. Thus, timely trimming or leaf removal may improve canopy structure and light penetration, but precise evaluation of physiological responses at different growth stages is essential.
       
The present study aims to analyze the impact of end-trimming after flowering on soybean growth traits and canopy architecture, while also exploring the feasibility of hyperspectral imaging for efficient growth assessment. By combining traditional agronomic practices with advanced imaging technology, this research seeks to provide insights into optimizing soybean yield and ensuring stable production under changing environmental conditions.

MATERIALS AND METHODS

This study was conducted from 2022 to 2023 at the experimental farm of Gyeongsang National University in Jinju-si, South Korea (35°08'57"N, 128°05'49"E). The soil was sandy loam with pH 6.5, EC 0.6 dS m-1, organic matter 17.4 g/kg, available P2O5 150 mg/kg and cation exchange capacity 17.4 cmol/kg. The soybean cultivar used was ‘Seonpung’, a large-seeded determinate type. Seeds were sown on June 13, 2022, at 60 × 20 cm spacing with two plants per hill. Fertilizers were applied at recommended rates of 30 kg N/ha, 30 kg P2O5/ha and 37 kg K2O/ha according to soil test results. Meteorological data from the Korea Meteorological Administration showed that temperatures during growth in 2022 and 2023 were higher than the 30-year average (Fig 1).

Fig 1: Average temperature and precipitation during the soybean growing season in 2022 and 2023.


       
The experiment followed a randomized complete block design with three replicates. Four different trimming treatments were applied and each treatment applied in three plots. The size of each plot was 40 m2 (4 m × 10 m). End-trimming was performed at the full flowering stage (R2) using a hedge trimmer (HT220-100, Zenoah, Japan). The reason for end-trimming in this study was to remove the overgrown leaves above the apical meristem without cutting the stem itself; therefore, it was performed at the R2 stage, before pod development, when reproductive organs halt vegetative growth and have a high demand for photosynthates. Treatments included no trimming (T0), trimming 10 cm below canopy height (T1), 20 cm below (T2) and 30 cm below (T3). In 2022, trimming was conducted on August 11, ten days after first flowering, while in 2023 sowing occurred on June 13, flowering on August 3 and trimming on August 16.
       
Growth traits such as plant height, aboveground biomass, pod number and pod weight per plant were measured in the field. Leaf area index (LAI) was determined using a portable leaf area meter (LP-80, Decagon Devices, USA). Photosynthetic characteristics were analyzed by leaf position (upper, middle, lower). At 24 days after treatment (DAT), photosynthetically active radiation (PAR) was measured using a spectroradiometer (SpectraPen SP, Photon Systems Instruments, Czech Republic). Stomatal conductance was measured with LI-600 (LI-COR, USA), photosynthetic rate with CID-340 (Bio-Science, USA) and SPAD values with a chlorophyll meter (SPAD-502, Minolta, Japan). Growth and physiological characteristics, including LAI, aboveground weight, pod number and weight, as well as photosynthesis, stomatal conductance and SPAD value, were measured with three replications in a plot and each replication was the average of three measurements.
       
Hyperspectral images of uppermost leaves that were affixed to black hardboard using stickers obtained using a Specim IQ camera (Specim Ltd, Finland) were obtained to evaluate reflectance characteristics under different trimming intensities. Measurements were taken under artificial light with a 100 W halogen lamp positioned approximately 80 cm above the target plants and radiometric calibration was performed using a 99% barium sulfate reference plate. Reflectance spectra from 400-900 nm were processed with ENVI 5.1 software (Exelis Visual Information Solution, USA). Vegetation indices were calculated based on formulas listed in Table 1.

Table 1: Vegetative indices and formulas for calculation.


       
Statistical analyses were conducted using SAS software (ver. 9.4, SAS Institute, USA). Two-way ANOVA was used to assess differences among years and treatments and Duncan’s multiple range test was applied for mean comparisons. Significance was determined at p<0.05.

RESULTS AND DISCUSSION

Growth parameters
 
Plant height that reflects growth condition among vegetative traits was significantly different under various conditions (Shadakshari et al., 2014) and these differences persisted even in the later stages, showing the order T0 > T1 > T2 > T3. Aboveground biomass was higher in T1 and T2 than in T0 in the early period (13 DAT) and even in the late period (42 DAT), biomass in T1 was greater than that of T0 (Table 2). Despite greater plant height in T0 compared to T1, the shoot weight was lower in T0, which was similar to reduced pod weight. The lower pod number observed in T2 and T3 is due to the occurrence of pod abortion after 30 DAT. This result is similar to the study by Torres et al., (2023), which found that end-trimming treatments resulted in reduced plant height, with the height difference not recovered thereafter. End-trimming treatments reduced plant height by 6-27%, implying a reduced risk of lodging; indeed, the incidence of lodging was lower in end-trimmed plants under field conditions (data not shown).

Table 2: Vegetative and reproductive parameters and yield of soybean affected by end-trimming treatments.


       
Pod weight per plant in T1 was consistently higher than in T0, whereas T3 showed the lowest values. In the case of T1, slight trimming removed leaves that previously functioned as sinks, allowing assimilates to be used for making pods. In contrast, the heavy trimming in T3 led to assimilate translocation toward new leaf formation rather than pod filling, resulting in lower pod weight. As shown in Table 3, the pod weight showed significant differences between years, possibly due to variation in meteorological conditions (Fig 1). Seed size distribution based on 100-seed weight (Fig 2) revealed that T1 produced seeds with greater size and less variability.

Table 3: Mean square of aerial biomass, pod number, 100-seed weight, seed number and yield of soybean in response to end-trimming treatments.



Fig 2: Distribution of seed weight according to end-trimming intensity.


       
Mild trimming treatments promoted aboveground biomass accumulation. Aboveground biomass was higher in T1 and T2 than in T0 during the early period and remained higher in T1 than in T0 in the late period. This result suggests that mild trimming treatments may promote aboveground biomass accumulation.
       
Seed weight is highly sensitive to leaf or pod removal (McAlister and Krober, 1958). In our study, T1 had a higher number and weight of seeds. T1 had a higher pod number but fewer seeds than T0, which resulted in a lower overall yield, but the 100-seed weight was greater. While pod removal generally increases seed size by enhancing assimilate translocation to the remaining pods (McAlister and Krober, 1958), this is not always the case (Munier-Jolain et al., 1998). Seed number is primarily influenced by canopy photosynthesis and assimilate availability during the early reproductive stages (R1-R3). In contrast, seed size is affected by assimilate supply during the seed growth stage (R5) (Egli and Bruening, 2003). The end-trimmed plants produced larger and more uniform seeds than the control (Fig 2). This result implies that end-trimming treatments promoted assimilate translocation.
       
In Korea, soybean yields exhibit significant year-to-year variation, largely driven by substantial annual fluctuations in weather conditions during the vegetative growth stage following flowering. Notably, significant differences were observed in aerial biomass rather than in seed number and 100-seed weight. In this condition, the end-trimming proved effective in preventing yield loss by mitigating the inhibition of reproductive growth caused by excessive vegetative growth.
       
The changes in canopy structure occurred due to altered leaf distribution on the main stem in response to trimming intensities. At 30 DAT, the control exhibited the most extended petiole lengths across all layers (Fig 3). When comparing treatments, petiole lengths in the middle layer were the longest across all treatments at 24 DAT. The petiole lengths of the upper layer increased, resulting in both upper and middle layers being longer than the lower layer. In contrast, T3 did not show a notable increase in petiole length compared to other treatments and the middle layer had longer petioles than the upper layer. Petiole length in the upper layer increases to facilitate morphological adaptation and overcome light competition by accumulating leaves in the middle and upper layers. At 30 DAT, the total number of leaves per plant followed the order: T1 > T3 > T0 > T2, whereas leaf weight followed the order: T1 > T0 > T2 > T3 (Fig 3). The difference in these results is due to the thinner, smaller leaves of T3, as indicated by the low leaf weight. This study showed that light reaching the lowest leaves was higher in treatments T2 and T3 (Fig 4).

​

Fig 3: Leaf number and petiole length according to end-trimming intensity.



Fig 4: Leaf area index at 44 DAT and light intensity (PAR) according to end-trimming intensity.


       
Petiole length can affect canopy architecture and is a key factor in assimilate transport efficiency (Zhu et al., 2010). The elongation of petioles in the upper canopy is a plant’s morphological adaptation to overcome light competition from the accumulation of leaves in the middle and upper layers. While 80% of assimilates are produced in the top 20% of the canopy (Hatfield and Carlson, 1978), most pods are located in the lower two-thirds of the plant (Hansen et al., 1981) and longer petioles therefore increase the distance for assimilate translocation (Gent, 1982). The changes in petiole length in this research may explain the lower pod number in T0 (Table 2 and 3), as the elongation of petioles in the middle layer could have hindered assimilate transport to the pods located there.
       
Excessive leaf area can limit light penetration and negatively affect yield (Liu et al., 2008) by lowering the leaf photosynthesis (Gholamhoseini et al., 2017). Conversely, a smaller leaf area can improve light penetration and air circulation in densely planted crops, positively impacting yield (Jin et al., 2009). Our findings are consistent with previous reports that a dense leaf distribution in the upper canopy can severely limit light penetration (Ogbuehi and Brandle, 1982). In our study, the light reaching the lowest leaves was higher in the T2 and T3 treatments (Fig 4). At 44 DAT, the leaf area index (LAI) for T1, where end-trimming intensity was low, was similar to the control, whereas T3, subjected to higher end-trimming intensity, exhibited the lowest LAI. Because reductions in petiole length could modify plant architecture and improve canopy structure, positively influencing yield (Egli, 1988) and plant architecture influences the soybean yield (Zhu et al., 2024), the differences in PAR levels within the plant canopy were due to the altered canopy architecture resulting from the changed petiole length. In this study, T3 maintained elevated chlorophyll levels in the lower leaves throughout the later growth stages.
 
Photosynthesis-related characteristics
 
At 44 DAT, leaf area index for T1, where end-trimming intensity was low, was similar to the control, whereas T3, subjected to higher end-trimming intensity, exhibited the lowest LAI. T3 had shorter petioles and smaller newly developed leaves than the untreated control, resulting in a lower LAI. Chlorophyll content at 13 DAT showed an initial decrease with increasing end-trimming intensity, but at later stages, T3 showed the highest chlorophyll content (Fig 5). When analyzing chlorophyll level by leaf position, treatments T1 and T2 showed similar or lower values in the upper leaves than the control, but higher values in the middle layer. T3 maintained elevated chlorophyll levels in the lower leaves throughout the later growth stages.

Fig 5: Changes in leaf chlorophyll level by end-trimming intensity.


       
We observed that stomatal conductance in trimmed plants remained higher than in the control. Because leaf color influences light distribution within the photosynthetic tissues, improving photosynthetic efficiency (Adegoye et al., 2023), newly emerged leaves after trimming may exhibit strong photosynthetic activity. The plants that have new leaves emerging after trimming may grow vigorously. Overall, stomatal conductance was greater in end-trimmed plants, with T3 showing uniformly high stomatal conductance across upper, middle and lower layers. At 30 DAT, photosynthetic rates in the upper layer increased with higher end-trimming intensity. T3 showed the highest rate in the middle layer, while T1 showed the lowest.
       
Strong end-trimming (T3) increased photosynthesis in the upper layer and mild trimming (T1) showed a smaller increase in photosynthetic rate (Fig 6). These results suggest that defoliation reduces resource competition between leaves, enhances the efficiency of photosynthesis in the remaining leaves and improves light penetration into the inside of the canopy, thereby accelerating the photosynthetic activity of individual plants. Generally, soybean leaves absorb 85-90% of incoming light, with the upper 25% of the canopy accounting for about 75% of total light interception (Campbell and Norman, 1998). However, the uppermost leaves often reach light saturation, causing the excess irradiance to be dissipated as heat and reducing light-use efficiency. In contrast, the lower canopy receives less than half the light saturation point, resulting in a structurally inefficient light distribution, excess light at the upper layer and deficiency at the lower layer. Reducing chlorophyll content in the upper leaves limits their light absorption, allowing more light to penetrate the lower layer and resulting in a more balanced irradiation on the total leaves. Consistent with these findings, this study also observed that treatments T1 and T2 had higher chlorophyll content in the middle layer than in the upper layer (Fig 5). It was suggested that petiole length in the upper layer increases to facilitate morphological adaptation and overcome light competition by accumulating leaves in the middle and upper layers. SPAD values, stomatal conductance and photosynthetic rates all showed similar trends in response to end-trimming; however, stomatal conductance was the trait that particularly well-reflected the treatment effects. Stomatal conductance clearly demonstrated the effects of end-trimming at early after-treatments and, when combined with LAI, enabled verification of treatment efficiency.

Fig 6: Leaf stomatal conductance and photosynthetic rate by leaf position.


 
Hyperspectral reflectances and vegetation indices
 
Hyperspectral reflectance showed noticeable differences among treatments at wavelengths above 700 nm during the early period after end-trimming (13 DAT). In contrast, no significant differences occurred during the later period (42 DAT) (Fig 7). Based on hyperspectral reflectance, there were notable differences among treatments in the early period after end-trimming (13 DAT), whereas by the later period (42 DAT), the differences between treatments weakened. T2 exhibited the lowest vegetation index values at 13 DAT but showed recovered reflectance to intermediate levels by 42 DAT. In the early period, the control generally showed the highest index values, while vegetation indices tended to decrease with greater end-trimming intensity. However, as the plants grew after end-trimming from 13 to 42 DAT, T3 recorded the highest values (Table 4). Vegetation indices such as Vog REI1, PSSRa, PSSRb, GNDVI and GCI were lowest in T2 and T1 at 13 and 42 DAT, respectively and maintained higher values in T3 throughout the later period. PSRI (Plant Senescence Reflectance Index) produced negative values close to zero when leaf color was darker and shifted to positive values with senescence. PRI increased with end-trimming intensity at 13 DAT, then decreased at 42 DAT. Across treatments, the control consistently showed the highest value in most vegetation indices. T1 showed vigorous initial growth at 13 DAT, followed by the occurrence of senescence symptoms. T2 exhibited initial stress by mechanical trimming but recovered in the later period. T3 showed better growth during the early period after end-trimming than T2 and maintained better growth through mid-period before declining.

Table 4: Vegetation indices calculated based on hyperspectral reflectance in 2022.



Fig 7: Changes in hyperspectral reflectance according to the end-trimming intensity.


       
Typical plant leaves exhibit strong light absorption near 450 nm and 670 nm and a remarkable increase in reflectance beyond 690 nm (Slattery et al., 2017). Hyperspectral reflectance indicated that all end-trimmed treatments showed lower NIR reflectance than the control (Fig 7). This result suggests that increased light penetration into the canopy following end-trimming resulted in greater NIR absorption. Especially, at 30 DAT, hyperspectral reflectance beyond 700 nm decreased as end-trimming intensity increased.
       
Plants respond to shading conditions by increasing specific leaf area, enhancing antenna complexes, decreasing the chlorophyll a:b ratio and allocating nitrogen between pigment-protein complexes to maximize light absorption and photosynthetic efficiency (Evans and Poorter, 2001). In T0, higher leaf density in the upper layer likely led to increased shading within the canopy, initiating nitrogen redistribution to enhance light absorption in the lower layer. Conversely, T3 showed consistently lower reflectance over 450-700 nm than other treatments, suggesting stronger absorption of blue and red lights.
       
Vegetation indices calculated using hyperspectral data and multivariate statistical methods that enable the interpretation of entire reflectance spectra are helpful in field research due to instant and nondestructive (Sellami et al., 2022). Specifically, vegetation index analysis is one of the most widely studied and applied methods for estimating crop conditions from spectral reflectance data (Morcillo-Pallarés et al., 2019). Vegetation indices such as Vog REI1, PSSRa, PSSRb, GNDVI and GCI are related to chlorophyll content (Vogelmann et al., 1993; Mahlein et al., 2010). T2 showed lower values at 13 DAT than at 42 DAT, suggesting a recovery from inhibition by strong trimming as new leaves are emerging. PSRI (Plant senescence reflectance index), which is associated with leaf aging, produced negative values close to zero when leaves were darker and shifted to positive values with senescence (Merzlyak et al., 1999). The vegetation indices used to estimate light use efficiency include PRI (Photochemical reflectance index) and SIPI (Structure insensitive pigment index), which reflect the radiation use ability of plants (Kohzuma and Hikosaka, 2018). PRI increased with end-trimming intensity at 13 DAT, then decreased at 42 DAT.
       
Vegetation indices also provide insights into canopy function. Chlorophyll-related indices such as Vog REI1, PSSRa and GNDVI decreased with increasing trimming intensity in early stages but later increased in T3, suggesting delayed senescence. PSRI values further confirmed this, as T3 maintained lower values, indicating slower leaf aging. These results agree with the research of Merzlyak et al., (1999), who developed PSRI as a reliable indicator of senescence progression. PRI and SIPI with higher values reflected improved light-use efficiency in trimmed plants, especially in T3, which decreased as leaves aged at 42 DAT. According to Sims and Gamon (2002), PRI is linked to xanthophyll cycle activity and photosynthetic radiation-use efficiency, supporting the interpretation that canopy restructuring improved radiation balance. Overall, hyperspectral traits confirmed that trimming modulated not only structural but also functional responses of the soybean canopy.

CONCLUSION

This study demonstrates that end-trimming after flowering is an effective canopy management strategy in soybean cultivation. Moderate trimming increased pod weight, improved seed size uniformity and reduced lodging risk by reducing plant height, whereas strong trimming reduced pod and seed numbers but delayed senescence and enhanced photosynthetic efficiency in the lower canopy. Moderate trimming modulates light absorption and canopy function, with implications for yield stability under varying conditions. Overall, timely and moderate apical trimming represents a practical strategy to balance vegetative growth with reproductive development, contributing to improved seed quality and stable yield outcomes in soybean production. These findings may contribute to the development of optimized soybean architecture and to the development of cultivation practices improving grain yield under excessive vegetative growth.

ACKNOWLEDGEMENT

The present study was supported by the Institute of Life Sciences, Gyeongsang National University. 

CONFLICT OF INTEREST

The authors declare that there are no conflicts of interest regarding the publication of this article.

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    End-trimming Applied after Flowering Changes Canopy Structure and Photosynthetic Production in Soybean

    S
    Sesil Hong1,2,#
    K
    Kieun Song1,3,4,#
    H
    Hee Chan Ahn2
    S
    Seung Jun Kim2
    S
    Seung Hyeon Park2
    S
    Seung Hyeon Park2
    S
    Sangin Shim1,3,4,*
    1Department of Agronomy, Gyeongsang National University, Jinju 52828, Korea.
    2Division of Applied Life Science, Gyeongsang National University, Jinju 52828, Korea.
    3Institute of Agricultural and Life and Sciences, Gyeongsang National University, Jinju 52828, Korea.
    4Research Institute of Life Sciences, Gyeongsang National University, Jinju 52828, Korea.

    • Submitted23-08-2026|

    • Accepted03-10-2026|

    • First Online 15-10-2026|

    • doi 10.18805/LRF-977

    ABSTRACT

    #Co-first author.

    Background: Global warming has accelerated vegetative growth in soybeans, delayed maturation and reduced seed quality. To address these challenges, this study investigated the effects of end-trimming the upper canopy after flowering on soybean growth and yield.

    Methods: End-trimming was conducted at the R2 stage (full flowering) using a trimmer at different intensities based on canopy height: no trimming (T0), - 10 cm (T1), - 20 cm (T2) and - 30 cm (T3). Plant growth, pod formation, seed development and physiological responses were evaluated across treatments.

    Result: Trimming reduced plant height, with no recovery in later stages. Moderate trimming (T1) enhanced pod formation and seed growth, yielding the highest pod number and weight, while excessive trimming (T3) resulted in fewer and lighter pods compared to the control. End-trimmed plants showed higher photosynthetic rates and improved light penetration to the lower canopy, which promoted photosynthesis and sink activity, ultimately contributing to better seed development.

    INTRODUCTION

    Soybean [Glycine max (L.) Merr.] is one of the most widely cultivated crops worldwide due to its high protein and lipid content, serving both as food and as raw material for products such as soap, pharmaceuticals and industrial ink. The yield potential of soybean is largely determined by canopy light interception, biomass conversion and partitioning to grains (Quijano and Morandi, 2023). Because growth habits differ between determinate and indeterminate types, grain setting becomes complex. In particular, the leaf area index (LAI) strongly influences canopy photosynthesis; however, excessive leaf area can reduce yield since respiration may surpass photosynthesis and shading limits the activity of lower leaves. Given the challenges posed by climate change and population growth, securing a stable soybean supply has become increasingly urgent (Corrales et al., 2022). Although positive correlations exist between leaf area, biomass and yield (Liu et al., 2008), overly dense canopies hinder light penetration and reduce efficiency. Moreover, climate change has led to persistent rainfall during the flowering period, resulting in excessive vegetative growth and lodging, as well as yield losses due to restricted efficient translocation of photosynthate; consequently, a scientific analysis of the effects of end-trimming is required.
           
    To address these limitations, end-trimming has been introduced as a practice that modifies canopy structure. This technique improves photosynthetic efficiency, enhances translocation of assimilates to reproductive organs and reduces lodging by removing excess leaves and stems (Nie et al., 2021; Yang et al., 2023; Philbrook and Oplinger, 1988). Nevertheless, its effectiveness depends greatly on timing and method and despite being a customary practice among Korean farmers, scientific research on its impact remains scarce. Thus, timely trimming or leaf removal may improve canopy structure and light penetration, but precise evaluation of physiological responses at different growth stages is essential.
           
    The present study aims to analyze the impact of end-trimming after flowering on soybean growth traits and canopy architecture, while also exploring the feasibility of hyperspectral imaging for efficient growth assessment. By combining traditional agronomic practices with advanced imaging technology, this research seeks to provide insights into optimizing soybean yield and ensuring stable production under changing environmental conditions.

    MATERIALS AND METHODS

    This study was conducted from 2022 to 2023 at the experimental farm of Gyeongsang National University in Jinju-si, South Korea (35°08'57"N, 128°05'49"E). The soil was sandy loam with pH 6.5, EC 0.6 dS m-1, organic matter 17.4 g/kg, available P2O5 150 mg/kg and cation exchange capacity 17.4 cmol/kg. The soybean cultivar used was ‘Seonpung’, a large-seeded determinate type. Seeds were sown on June 13, 2022, at 60 × 20 cm spacing with two plants per hill. Fertilizers were applied at recommended rates of 30 kg N/ha, 30 kg P2O5/ha and 37 kg K2O/ha according to soil test results. Meteorological data from the Korea Meteorological Administration showed that temperatures during growth in 2022 and 2023 were higher than the 30-year average (Fig 1).

    Fig 1: Average temperature and precipitation during the soybean growing season in 2022 and 2023.


           
    The experiment followed a randomized complete block design with three replicates. Four different trimming treatments were applied and each treatment applied in three plots. The size of each plot was 40 m2 (4 m × 10 m). End-trimming was performed at the full flowering stage (R2) using a hedge trimmer (HT220-100, Zenoah, Japan). The reason for end-trimming in this study was to remove the overgrown leaves above the apical meristem without cutting the stem itself; therefore, it was performed at the R2 stage, before pod development, when reproductive organs halt vegetative growth and have a high demand for photosynthates. Treatments included no trimming (T0), trimming 10 cm below canopy height (T1), 20 cm below (T2) and 30 cm below (T3). In 2022, trimming was conducted on August 11, ten days after first flowering, while in 2023 sowing occurred on June 13, flowering on August 3 and trimming on August 16.
           
    Growth traits such as plant height, aboveground biomass, pod number and pod weight per plant were measured in the field. Leaf area index (LAI) was determined using a portable leaf area meter (LP-80, Decagon Devices, USA). Photosynthetic characteristics were analyzed by leaf position (upper, middle, lower). At 24 days after treatment (DAT), photosynthetically active radiation (PAR) was measured using a spectroradiometer (SpectraPen SP, Photon Systems Instruments, Czech Republic). Stomatal conductance was measured with LI-600 (LI-COR, USA), photosynthetic rate with CID-340 (Bio-Science, USA) and SPAD values with a chlorophyll meter (SPAD-502, Minolta, Japan). Growth and physiological characteristics, including LAI, aboveground weight, pod number and weight, as well as photosynthesis, stomatal conductance and SPAD value, were measured with three replications in a plot and each replication was the average of three measurements.
           
    Hyperspectral images of uppermost leaves that were affixed to black hardboard using stickers obtained using a Specim IQ camera (Specim Ltd, Finland) were obtained to evaluate reflectance characteristics under different trimming intensities. Measurements were taken under artificial light with a 100 W halogen lamp positioned approximately 80 cm above the target plants and radiometric calibration was performed using a 99% barium sulfate reference plate. Reflectance spectra from 400-900 nm were processed with ENVI 5.1 software (Exelis Visual Information Solution, USA). Vegetation indices were calculated based on formulas listed in Table 1.

    Table 1: Vegetative indices and formulas for calculation.


           
    Statistical analyses were conducted using SAS software (ver. 9.4, SAS Institute, USA). Two-way ANOVA was used to assess differences among years and treatments and Duncan’s multiple range test was applied for mean comparisons. Significance was determined at p<0.05.

    RESULTS AND DISCUSSION

    Growth parameters
     
    Plant height that reflects growth condition among vegetative traits was significantly different under various conditions (Shadakshari et al., 2014) and these differences persisted even in the later stages, showing the order T0 > T1 > T2 > T3. Aboveground biomass was higher in T1 and T2 than in T0 in the early period (13 DAT) and even in the late period (42 DAT), biomass in T1 was greater than that of T0 (Table 2). Despite greater plant height in T0 compared to T1, the shoot weight was lower in T0, which was similar to reduced pod weight. The lower pod number observed in T2 and T3 is due to the occurrence of pod abortion after 30 DAT. This result is similar to the study by Torres et al., (2023), which found that end-trimming treatments resulted in reduced plant height, with the height difference not recovered thereafter. End-trimming treatments reduced plant height by 6-27%, implying a reduced risk of lodging; indeed, the incidence of lodging was lower in end-trimmed plants under field conditions (data not shown).

    Table 2: Vegetative and reproductive parameters and yield of soybean affected by end-trimming treatments.


           
    Pod weight per plant in T1 was consistently higher than in T0, whereas T3 showed the lowest values. In the case of T1, slight trimming removed leaves that previously functioned as sinks, allowing assimilates to be used for making pods. In contrast, the heavy trimming in T3 led to assimilate translocation toward new leaf formation rather than pod filling, resulting in lower pod weight. As shown in Table 3, the pod weight showed significant differences between years, possibly due to variation in meteorological conditions (Fig 1). Seed size distribution based on 100-seed weight (Fig 2) revealed that T1 produced seeds with greater size and less variability.

    Table 3: Mean square of aerial biomass, pod number, 100-seed weight, seed number and yield of soybean in response to end-trimming treatments.



    Fig 2: Distribution of seed weight according to end-trimming intensity.


           
    Mild trimming treatments promoted aboveground biomass accumulation. Aboveground biomass was higher in T1 and T2 than in T0 during the early period and remained higher in T1 than in T0 in the late period. This result suggests that mild trimming treatments may promote aboveground biomass accumulation.
           
    Seed weight is highly sensitive to leaf or pod removal (McAlister and Krober, 1958). In our study, T1 had a higher number and weight of seeds. T1 had a higher pod number but fewer seeds than T0, which resulted in a lower overall yield, but the 100-seed weight was greater. While pod removal generally increases seed size by enhancing assimilate translocation to the remaining pods (McAlister and Krober, 1958), this is not always the case (Munier-Jolain et al., 1998). Seed number is primarily influenced by canopy photosynthesis and assimilate availability during the early reproductive stages (R1-R3). In contrast, seed size is affected by assimilate supply during the seed growth stage (R5) (Egli and Bruening, 2003). The end-trimmed plants produced larger and more uniform seeds than the control (Fig 2). This result implies that end-trimming treatments promoted assimilate translocation.
           
    In Korea, soybean yields exhibit significant year-to-year variation, largely driven by substantial annual fluctuations in weather conditions during the vegetative growth stage following flowering. Notably, significant differences were observed in aerial biomass rather than in seed number and 100-seed weight. In this condition, the end-trimming proved effective in preventing yield loss by mitigating the inhibition of reproductive growth caused by excessive vegetative growth.
           
    The changes in canopy structure occurred due to altered leaf distribution on the main stem in response to trimming intensities. At 30 DAT, the control exhibited the most extended petiole lengths across all layers (Fig 3). When comparing treatments, petiole lengths in the middle layer were the longest across all treatments at 24 DAT. The petiole lengths of the upper layer increased, resulting in both upper and middle layers being longer than the lower layer. In contrast, T3 did not show a notable increase in petiole length compared to other treatments and the middle layer had longer petioles than the upper layer. Petiole length in the upper layer increases to facilitate morphological adaptation and overcome light competition by accumulating leaves in the middle and upper layers. At 30 DAT, the total number of leaves per plant followed the order: T1 > T3 > T0 > T2, whereas leaf weight followed the order: T1 > T0 > T2 > T3 (Fig 3). The difference in these results is due to the thinner, smaller leaves of T3, as indicated by the low leaf weight. This study showed that light reaching the lowest leaves was higher in treatments T2 and T3 (Fig 4).

    ​

    Fig 3: Leaf number and petiole length according to end-trimming intensity.



    Fig 4: Leaf area index at 44 DAT and light intensity (PAR) according to end-trimming intensity.


           
    Petiole length can affect canopy architecture and is a key factor in assimilate transport efficiency (Zhu et al., 2010). The elongation of petioles in the upper canopy is a plant’s morphological adaptation to overcome light competition from the accumulation of leaves in the middle and upper layers. While 80% of assimilates are produced in the top 20% of the canopy (Hatfield and Carlson, 1978), most pods are located in the lower two-thirds of the plant (Hansen et al., 1981) and longer petioles therefore increase the distance for assimilate translocation (Gent, 1982). The changes in petiole length in this research may explain the lower pod number in T0 (Table 2 and 3), as the elongation of petioles in the middle layer could have hindered assimilate transport to the pods located there.
           
    Excessive leaf area can limit light penetration and negatively affect yield (Liu et al., 2008) by lowering the leaf photosynthesis (Gholamhoseini et al., 2017). Conversely, a smaller leaf area can improve light penetration and air circulation in densely planted crops, positively impacting yield (Jin et al., 2009). Our findings are consistent with previous reports that a dense leaf distribution in the upper canopy can severely limit light penetration (Ogbuehi and Brandle, 1982). In our study, the light reaching the lowest leaves was higher in the T2 and T3 treatments (Fig 4). At 44 DAT, the leaf area index (LAI) for T1, where end-trimming intensity was low, was similar to the control, whereas T3, subjected to higher end-trimming intensity, exhibited the lowest LAI. Because reductions in petiole length could modify plant architecture and improve canopy structure, positively influencing yield (Egli, 1988) and plant architecture influences the soybean yield (Zhu et al., 2024), the differences in PAR levels within the plant canopy were due to the altered canopy architecture resulting from the changed petiole length. In this study, T3 maintained elevated chlorophyll levels in the lower leaves throughout the later growth stages.
     
    Photosynthesis-related characteristics
     
    At 44 DAT, leaf area index for T1, where end-trimming intensity was low, was similar to the control, whereas T3, subjected to higher end-trimming intensity, exhibited the lowest LAI. T3 had shorter petioles and smaller newly developed leaves than the untreated control, resulting in a lower LAI. Chlorophyll content at 13 DAT showed an initial decrease with increasing end-trimming intensity, but at later stages, T3 showed the highest chlorophyll content (Fig 5). When analyzing chlorophyll level by leaf position, treatments T1 and T2 showed similar or lower values in the upper leaves than the control, but higher values in the middle layer. T3 maintained elevated chlorophyll levels in the lower leaves throughout the later growth stages.

    Fig 5: Changes in leaf chlorophyll level by end-trimming intensity.


           
    We observed that stomatal conductance in trimmed plants remained higher than in the control. Because leaf color influences light distribution within the photosynthetic tissues, improving photosynthetic efficiency (Adegoye et al., 2023), newly emerged leaves after trimming may exhibit strong photosynthetic activity. The plants that have new leaves emerging after trimming may grow vigorously. Overall, stomatal conductance was greater in end-trimmed plants, with T3 showing uniformly high stomatal conductance across upper, middle and lower layers. At 30 DAT, photosynthetic rates in the upper layer increased with higher end-trimming intensity. T3 showed the highest rate in the middle layer, while T1 showed the lowest.
           
    Strong end-trimming (T3) increased photosynthesis in the upper layer and mild trimming (T1) showed a smaller increase in photosynthetic rate (Fig 6). These results suggest that defoliation reduces resource competition between leaves, enhances the efficiency of photosynthesis in the remaining leaves and improves light penetration into the inside of the canopy, thereby accelerating the photosynthetic activity of individual plants. Generally, soybean leaves absorb 85-90% of incoming light, with the upper 25% of the canopy accounting for about 75% of total light interception (Campbell and Norman, 1998). However, the uppermost leaves often reach light saturation, causing the excess irradiance to be dissipated as heat and reducing light-use efficiency. In contrast, the lower canopy receives less than half the light saturation point, resulting in a structurally inefficient light distribution, excess light at the upper layer and deficiency at the lower layer. Reducing chlorophyll content in the upper leaves limits their light absorption, allowing more light to penetrate the lower layer and resulting in a more balanced irradiation on the total leaves. Consistent with these findings, this study also observed that treatments T1 and T2 had higher chlorophyll content in the middle layer than in the upper layer (Fig 5). It was suggested that petiole length in the upper layer increases to facilitate morphological adaptation and overcome light competition by accumulating leaves in the middle and upper layers. SPAD values, stomatal conductance and photosynthetic rates all showed similar trends in response to end-trimming; however, stomatal conductance was the trait that particularly well-reflected the treatment effects. Stomatal conductance clearly demonstrated the effects of end-trimming at early after-treatments and, when combined with LAI, enabled verification of treatment efficiency.

    Fig 6: Leaf stomatal conductance and photosynthetic rate by leaf position.


     
    Hyperspectral reflectances and vegetation indices
     
    Hyperspectral reflectance showed noticeable differences among treatments at wavelengths above 700 nm during the early period after end-trimming (13 DAT). In contrast, no significant differences occurred during the later period (42 DAT) (Fig 7). Based on hyperspectral reflectance, there were notable differences among treatments in the early period after end-trimming (13 DAT), whereas by the later period (42 DAT), the differences between treatments weakened. T2 exhibited the lowest vegetation index values at 13 DAT but showed recovered reflectance to intermediate levels by 42 DAT. In the early period, the control generally showed the highest index values, while vegetation indices tended to decrease with greater end-trimming intensity. However, as the plants grew after end-trimming from 13 to 42 DAT, T3 recorded the highest values (Table 4). Vegetation indices such as Vog REI1, PSSRa, PSSRb, GNDVI and GCI were lowest in T2 and T1 at 13 and 42 DAT, respectively and maintained higher values in T3 throughout the later period. PSRI (Plant Senescence Reflectance Index) produced negative values close to zero when leaf color was darker and shifted to positive values with senescence. PRI increased with end-trimming intensity at 13 DAT, then decreased at 42 DAT. Across treatments, the control consistently showed the highest value in most vegetation indices. T1 showed vigorous initial growth at 13 DAT, followed by the occurrence of senescence symptoms. T2 exhibited initial stress by mechanical trimming but recovered in the later period. T3 showed better growth during the early period after end-trimming than T2 and maintained better growth through mid-period before declining.

    Table 4: Vegetation indices calculated based on hyperspectral reflectance in 2022.



    Fig 7: Changes in hyperspectral reflectance according to the end-trimming intensity.


           
    Typical plant leaves exhibit strong light absorption near 450 nm and 670 nm and a remarkable increase in reflectance beyond 690 nm (Slattery et al., 2017). Hyperspectral reflectance indicated that all end-trimmed treatments showed lower NIR reflectance than the control (Fig 7). This result suggests that increased light penetration into the canopy following end-trimming resulted in greater NIR absorption. Especially, at 30 DAT, hyperspectral reflectance beyond 700 nm decreased as end-trimming intensity increased.
           
    Plants respond to shading conditions by increasing specific leaf area, enhancing antenna complexes, decreasing the chlorophyll a:b ratio and allocating nitrogen between pigment-protein complexes to maximize light absorption and photosynthetic efficiency (Evans and Poorter, 2001). In T0, higher leaf density in the upper layer likely led to increased shading within the canopy, initiating nitrogen redistribution to enhance light absorption in the lower layer. Conversely, T3 showed consistently lower reflectance over 450-700 nm than other treatments, suggesting stronger absorption of blue and red lights.
           
    Vegetation indices calculated using hyperspectral data and multivariate statistical methods that enable the interpretation of entire reflectance spectra are helpful in field research due to instant and nondestructive (Sellami et al., 2022). Specifically, vegetation index analysis is one of the most widely studied and applied methods for estimating crop conditions from spectral reflectance data (Morcillo-Pallarés et al., 2019). Vegetation indices such as Vog REI1, PSSRa, PSSRb, GNDVI and GCI are related to chlorophyll content (Vogelmann et al., 1993; Mahlein et al., 2010). T2 showed lower values at 13 DAT than at 42 DAT, suggesting a recovery from inhibition by strong trimming as new leaves are emerging. PSRI (Plant senescence reflectance index), which is associated with leaf aging, produced negative values close to zero when leaves were darker and shifted to positive values with senescence (Merzlyak et al., 1999). The vegetation indices used to estimate light use efficiency include PRI (Photochemical reflectance index) and SIPI (Structure insensitive pigment index), which reflect the radiation use ability of plants (Kohzuma and Hikosaka, 2018). PRI increased with end-trimming intensity at 13 DAT, then decreased at 42 DAT.
           
    Vegetation indices also provide insights into canopy function. Chlorophyll-related indices such as Vog REI1, PSSRa and GNDVI decreased with increasing trimming intensity in early stages but later increased in T3, suggesting delayed senescence. PSRI values further confirmed this, as T3 maintained lower values, indicating slower leaf aging. These results agree with the research of Merzlyak et al., (1999), who developed PSRI as a reliable indicator of senescence progression. PRI and SIPI with higher values reflected improved light-use efficiency in trimmed plants, especially in T3, which decreased as leaves aged at 42 DAT. According to Sims and Gamon (2002), PRI is linked to xanthophyll cycle activity and photosynthetic radiation-use efficiency, supporting the interpretation that canopy restructuring improved radiation balance. Overall, hyperspectral traits confirmed that trimming modulated not only structural but also functional responses of the soybean canopy.

    CONCLUSION

    This study demonstrates that end-trimming after flowering is an effective canopy management strategy in soybean cultivation. Moderate trimming increased pod weight, improved seed size uniformity and reduced lodging risk by reducing plant height, whereas strong trimming reduced pod and seed numbers but delayed senescence and enhanced photosynthetic efficiency in the lower canopy. Moderate trimming modulates light absorption and canopy function, with implications for yield stability under varying conditions. Overall, timely and moderate apical trimming represents a practical strategy to balance vegetative growth with reproductive development, contributing to improved seed quality and stable yield outcomes in soybean production. These findings may contribute to the development of optimized soybean architecture and to the development of cultivation practices improving grain yield under excessive vegetative growth.

    ACKNOWLEDGEMENT

    The present study was supported by the Institute of Life Sciences, Gyeongsang National University. 

    CONFLICT OF INTEREST

    The authors declare that there are no conflicts of interest regarding the publication of this article.

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