Changes in Leaf and Growth of Pak Choi in a Semi-closed Greenhouse in Eastern China

Authors:
Xiaotao Ding Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China; and Shanghai Dushi Green Engineering Co., Ltd., Shanghai 201106, China

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Hongmei Zhang Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Lizhong He Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Haijun Jin Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Qiang Zhou Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China; and Shanghai Dushi Green Engineering Co., Ltd., Shanghai 201106, China

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Juan Yang Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Weimin Zhu Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Jizhu Yu Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Tingting Qian Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Abstract

To study and model changes in the development of pak choi (Brassica rapa ssp. chinensis Makino), three pak choi cultivars—Xinxiaqing No. 5 (Xinxiaqing 5), Haiqing, and Huawang—were grown in a modern greenhouse. Four structural parameters, including leaf length, leaf width, and plant height and width, were measured regularly every 3 days. The results showed that the changes in plant height and width, and leaf length and width of the three cultivars followed sigmoidal trends. Logistical regression models {Y = K/[1 + (KL0)/L0 × exp(–r × t)]; Y = K/[1 + (KL0)/L0 × exp(−r × rad)]} of the leaf length and width accumulated with growth days and with accumulated radiation fit the actual data very well, with the correlation coefficient R2 all greater than 0.98. The R2 values of the plant width accumulation models were all greater than 0.93, whereas the R2 values of the plant height regression models were not robust. In this study, the regression models of changes in plant height and width, and leaf length and width of pak choi were used to study the changes of morphological characteristics and analyze the change rules of pak choi growth and development.

Pak choi (Brassica campestris ssp. chinensis Makino), also known as small cabbage, nonheading cabbage, and rape, is an important and popular vegetable in China. Annual consumption accounts for 30% to 40% of the total annual vegetable consumption in eastern China (Ding et al., 2018). Because green vegetables can be cultivated during the entire year, researchers have cultivated many green vegetables cultivars according to the environmental characteristics of different seasons and made them more suitable for artificial cultivation conditions (Zhu et al., 2019).

To grow pak choi in a greenhouse or plant factory, a systematic approach, such as modeling, is required as an efficient tool to predict plant growth (Cho et al., 2015). Plant growth and development are strongly affected by factors such as growth days, growing degree-days (Dwyer and Stewart, 1986), radiation (photosynthetically active radiation) (Bie et al., 2004), and nutrition (Beccafichi et al., 2002). Because the accumulation of pak choi leaf area can reflect the level of yield, it is an important trait that concerns cultivators and producers. Plant growth analysis has developed as the use of computers and control technology has advanced. This technology is a more scientific and universal analytical method that can compare different cultivars at varying growth stages and under variable cultivation conditions (Nicholls and Calder, 1973). To monitor continuous changes in the pak choi leaf area and subsequent growth, Cho and Son (2007) modeled the leaf number and leaf area of pak choi using growing degree-days, and also modeled pak choi growth using the radiation integral and planting density (Cho et al., 2015).

Vegetable development modeling not only focuses on yield, but also concerns quantitative information about major processes involved in plant height and width, and leaf area changes, among others (Ramnarain et al., 2018; Zheng et al., 2018). These morphological parameters are important for evaluating the characteristics of cultivars (Cho and Son, 2007; Zhou et al., 2020). Developmental modeling can be described as a quantitative scheme to predict the growth, development, and yield of a crop given a set of genetic features and relevant environmental variables (Manikandan and Vethamoni, 2017). There are many cultivars of vegetables, and the differences among cultivars are obvious. Thus, the investigation of traits of different cultivars is an enormous endeavor that is difficult to conduct comprehensively. To date, few studies have been conducted to investigate the morphological parameters of the development of different cultivars of pak choi (Liang et al., 2015).

The objective of our study was to develop descriptive mathematical models of leaf development and canopy changes of different cultivars of pak choi to provide an in-depth analysis of the growth characteristics of pak choi and provide guidance for its production.

Materials and Methods

Experimental design.

The experiment was conducted in a modern greenhouse of the National Engineering Research Center of Protected Agriculture, Chongming District, Shanghai, China. Air temperature, relative humidity, CO2 concentration, radiation, and wind speed and direction were recorded automatically by Priva sensors (Priva BV, DeLier, Netherlands) at 5-min intervals. Moreover, the greenhouse air temperature was controlled at ≈20 °C during the day and 10 °C at night. The experiment was conducted from Oct. 2015 to Jan. 2016. Three pak choi cultivars were sown on 23 Oct. 2015. The cultivars used in this study were Xinxiaqing No. 5 (‘Xinxiaqing 5’), ‘Haiqing’, and ‘Huawang’, all provided by the Horticultural Research Institute of the Shanghai Academy of Agricultural Sciences, Shanghai, China.

The pak choi seeds were sown in rock wool blocks (7.5 × 7.5 × 6.5 cm), with two to three seeds per block. Sixty blocks were used for each species, which were divided into three replicates. When the cotyledon of the seedling was fully expanded, only one plant remained for each block, which results in 60 plants for each treatment. Measurement of the structural parameters was initiated on 6 Nov. 2015, when the second leaves unfolded, whereas the accumulation of radiation was monitored starting on 1 Nov. 2015.

Five plants from each cultivar were selected for continuous nondestructive measurement. Four structural parameters—leaf length and leaf width (all unfolded leaves from the bottom to the top), and plant height and width—were measured with calipers once at ≈3 d, for a total of 20 measurements.

Measurements of pak choi leaf length, leaf width, plant height, and plant width.

Leaf length was measured from the lamina tip to the intersection of the lamina and petiole along the lamina midrib; leaf width was measured from tip to tip between the widest lamina lobes (Fig. 1). The accumulated leaf length and width were defined as the sum of the length and width, respectively of all leaves, which were measured each time. Plant height was measured from the base to the tallest point of the plant. Moreover, plant width was measured at the maximum width of the plant.

Fig. 1.
Fig. 1.

Measured leaf length and width of pak choi in the experiment. The leaf length was measured from the lamina tip to the intersection of the lamina and petiole along the lamina midrib. The leaf width was measured from tip to tip between the widest lamina lobes.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Measurements of radiation.

The sum of radiation for each day was downloaded from the Priva computer from 1 Nov. 2015. The growth parameter measurements and the sum of radiation were calculated from 1 Nov. 2015 to the measurement day.

After each measurement, the seedlings were irrigated with tidal irrigation, and the blocks were kept soaked in the nutrient solution for 30 min. The excess nutrient solution was then drained to ensure there was enough nutrient solution in the rock wool blocks during the entire growth period. The electrical conductivity of the irrigation nutrient solution was 1.8 dS⋅m–1, and the pH was 5.8, as described by Ding et al. (2018). Nutrient concentrations are listed in Table 1.

Table 1.

Elements component in the mother nutrient solution A and B in different tanks.

Table 1.

Statistical model development.

To estimate the development processes of different vegetables, we modeled separately the plant height change, plant width change, accumulated leaf length (the sum of all leaf lengths per plant), and accumulated leaf width (the sum of all leaf widths per plant) with growth days or accumulated radiation. SAS statistical analysis version 9.3 software (SAS Institute Inc., Cary, NC) was used for all data analysis and regression; Origin 7.5 software (OriginLab, Northampton, MA) was used for plotting. The logistic curve model used was
Y=K/[1+(KL0)/L0×exp(r×t)]
and
Y=K/[1+(KL0)/L0×exp(r×rad)],
where K is the potential maximum value of Y, L0 is the initial value of Y, r is the growth rate of Y, t is the growth days, and rad is the accumulated radiation. All parameters were calculated and obtained by nonlinear least squares method in SAS software according to measured plant growth data.

Results

Regression analysis of the accumulated leaf length and width with growth days.

The accumulated leaf length and width of the three pak choi cultivars were very consistent with the logistical model (Figs. 24). A comparison of the logistics curve parameters indicated that ‘Xinxiaqing 5’ had the greatest potential maximum (K) of accumulated leaf length and width (Table 2), followed by ‘Haiqing’ and ‘Huawang’. The parameter value of r indicated that the blade of ‘Huawang’ expanded more quickly than the other two cultivars. The F values of regression model of the three cultivars were all very high (P < 0.0001), indicating that the regression model predicted with great accuracy the change in the cumulative amount of leaf length and width of the different cultivars.

Fig. 2.
Fig. 2.

Regression of accumulated leaf length and width during the growth days of pak choi ‘Xinxiaqing 5’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 3.
Fig. 3.

Regression of accumulated leaf length and width with the growth days of pak choi ‘Haiqing’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 4.
Fig. 4.

Regression of accumulated leaf length and width with the growth days of pak choi ‘Huawang’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Table 2.

Regression model parameters of accumulated leaf length and width with growth days for different varieties of pak choi.

Table 2.

A comparison of the results between the simulated and measured data of the three cultivars (Figs. 24) showed that the simulated and measured data were very close; simulated data correlated highly with measured data. The R2 values of the regression models were 0.988, 0.985, and 0.989 for the leaf length of Xinxiaqing 5, Haiqing, and Huawang, respectively, and 0.988, 0.987, and 0.992 for the leaf width of Xinxiaqing 5, Haiqing, and Huawang, respectively. This further illustrates that the model we constructed for accumulated leaf length and width of the three cultivars predicted the leaf growth of pak choi effectively.

Regression analysis of the changes in plant height and width with growth days.

Table 3 shows that the K values of plant height and width of each cultivar did not differ greatly, although those of ‘Huawang’ were slightly greater. The F values of plant height were much lower than the F value of plant width, indicating that the plant height change regression model was not as accurate as that of the plant width change regression model.

Table 3.

Model parameters of the changes in plant height and width with the growth days of different varieties of pak choi.

Table 3.

Figures 5 and 6 show the difference between the simulated and measured data of plant height and plant width of different cultivars of pak choi. As shown in Fig. 5, the height of all the cultivars decreased significantly on 27 Nov. 2015. At that time, the leaves of pak choi changed from upright to flat, resulting in a significant decrease in height. This could be the main reason for the large difference between the simulated and measured data. The simulated and measured plant height data of ‘Xinxiaqing 5’ differed the most, and the slope of the straight line was very small (Fig. 5). The simulated data of plant width was relatively close to the measured data, and the model predicted the changes in plant width of different cultivars (Fig. 6). However, in general, the P values of all the models on changes in the plant height and width were less than 0.0001, so the model described the changes in plant height and width with great accuracy.

Fig. 5.
Fig. 5.

Regression of the changes in plant height with the growth days of three varieties of pak choi.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 6.
Fig. 6.

Regression of the changes in plant width with the growth days of three varieties of pak choi.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Regression analysis of accumulated leaf length and width with accumulated radiation.

Regression models of the leaf length and width and accumulated radiation were also highly consistent with the logistical model. The F value of ‘Haiqing’ in Table 4 was greater than that in Table 2. This indicates that the accumulated radiation had a more significant impact on the expansion of ‘Haiqing’ leaves. The F values of the regression models of the accumulated leaf length and width of the three cultivars were all very high (P < 0.0001), indicating that the regression model predicted the change in the cumulative amount of leaf length and width with accumulated radiation effectively.

Table 4.

Regression model parameters of the accumulated leaf length and width with the accumulated radiation for different varieties of pak choi.

Table 4.

A comparison of the results between the simulated and measured data of the three cultivars (Figs. 79) showed that the simulated and measured data were very close. The R2 value of the regression models was greater than 0.98, which illustrates further that the model constructed for accumulated leaf length and width of the three cultivars predicted the leaf growth of pak choi effectively.

Fig. 7.
Fig. 7.

Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Xinxiaqing 5’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 8.
Fig. 8.

Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Haiqing’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 9.
Fig. 9.

Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Huawang’.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Regression analysis of plant height and width changes with accumulated radiation.

Comparing the F values in Tables 3 and 5, it can be seen that the F value of three cultivars in Table 3 are greater than those in Table 5, indicating that the effect of accumulated radiation on plant height and width is not as significant as growth days.

Table 5.

Model parameters of the changes in plant height and width with the accumulated radiation of different varieties of pak choi.

Table 5.

Figure 10 shows there is a significant difference between the simulated height and the measured data, and the R2 value of the linear fit between the simulated and measured data was less than 0.8. Thus, accumulated radiation has a small effect on the change in plant height. The reason could be that the height of pak choi is closely related to the leaf shape. The simulated data of plant width was relatively close to that of the measured data, and the model predicted the change in plant width of different cultivars (Fig. 11).

Fig. 10.
Fig. 10.

Regression of the changes in plant height change and the accumulated radiation of three varieties of pak choi.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Fig. 11.
Fig. 11.

Regression of the changes in plant width compared with the accumulated radiation of three varieties of pak choi.

Citation: HortScience 57, 5; 10.21273/HORTSCI16523-22

Discussion

Pak choi is a green leafy vegetable with high economic and nutritional relevance in eastern and southeastern Asia. The accumulation of leaf area is an important trait in production that directly determines the formation of yield (Ewert, 2004). Therefore, the monitoring and modeling of leaf area accumulation is highly significant. When simulating the process of accumulation of leaf area, two types of models are usually used: empirical models and mechanistic models (Spitters, 1990). Although mechanistic dynamic models undoubtedly have greater scientific, forecasting, and instructive values, simple empirical models can also provide useful information and predictions, particularly if they are based on biologically meaningful parameters (Ewert, 2004; Tei et al., 1996). In our study, the R2 value of the exponential models for leaf length and width accumulated with growth days or with accumulated radiation of different cultivars of pak choi reached more than 0.98, laying an important foundation for the application of the regression model in future production management.

Because the leaves of pak choi are clustered, they are not suitable for measurements with a leaf area meter. Therefore, in this study, the leaf length and leaf width were measured manually. There are also studies that use analytical imaging methods to measure leaf area. However, because of the oblique angle of the leaves, there is a large error in taking leaf images from a vertical angle to estimate leaf area (Nie et al., 2010). Capturing multiangle leaf images through a stereovision system and segmenting them through a semiautomatic process can produce a more accurate leaf area. In addition, it also meets the needs of automatic nondestructive measurement, and it is possible to replace manual measurement and reduce labor cost, to some extent, in the future (Liang et al., 2015). In our study, accumulated leaf length and width were predicted based on development days and accumulated radiation, respectively. Some studies consider introducing light radiation into the leaf area accumulation model, such as thermal effectiveness and photosynthetically active radiation (Hang et al., 2019), and light and temperature function (Larsen and Persson, 1999). In this study, the greenhouse light was ambient, and growth depended on outside radiation. The simulation results of combining light radiation would not be better than using development days, which is consistent with the results found by Cai et al. (2020) for B. chinensis, and those of others (Tei et al., 1996; Yuan and Bland, 2004) for lettuce (Lactuca sativa L. var. crispa). Light does not always have a positive effect on the accumulation of leaf area. Stronger light may even reduce the leaf area and increase leaf thickness (Kumar et al., 2012). However, supplemental light can increase the leaf area and accumulation of biomass in the winter (Voutsinos et al., 2021). Voutsinos et al. (2021) illustrated that relative growth rate increased with temperature during the vegetative growth stage, whereas maximal growth rate during the linear stage was constrained by radiation more than temperature. In addition, a semiclosed greenhouse has strong capabilities for controlling temperature, and the growth and development of pak choi based on the number of development days serves as a more effective reference for annual production management arrangements.

It is more difficult to measure the changes in height of green vegetables because the inclination angle and the leaf shape determine the height to some extent. As the leaves develop, the original erect leaves appear curled, so the data for plant height in our study fluctuated significantly. Continuous monitoring of plant height and width of different cultivars could provide important data to support the evaluation of plant structures.

Modern greenhouses equipped with computerized climate control systems already cover substantial and increasing numbers of hectares in China, and it is critical to adapt greenhouse designs or climate control strategies to local conditions. Greenhouse climate and growth models can be used to enhance our understanding of the physical greenhouse climate and to test the effectiveness of any greenhouse design or climate management strategy, and thus, to optimally control the greenhouse microclimate (Mashonjowa et al., 2013).

Conclusion

In this study, through regular measurement of plant height and width, and leaf length and width of ‘Xinxiaqing 5’, ‘Haiqing’, and ‘Huawang’, growth models for different cultivars of pak choi were developed. Among them, the regression models for accumulated leaf length and width, and the change in plant width predicted the growth of each cultivar of pak choi effectively. However, the plant height model could be slightly less accurate than other models as a result of the structural characteristics of pak choi. The development of growth regression models of different cultivars of pak choi can help researchers and growers simulate the growth process of pak choi effectively, and should provide helpful guidance and references for the production of pak choi.

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  • Fig. 1.

    Measured leaf length and width of pak choi in the experiment. The leaf length was measured from the lamina tip to the intersection of the lamina and petiole along the lamina midrib. The leaf width was measured from tip to tip between the widest lamina lobes.

  • Fig. 2.

    Regression of accumulated leaf length and width during the growth days of pak choi ‘Xinxiaqing 5’.

  • Fig. 3.

    Regression of accumulated leaf length and width with the growth days of pak choi ‘Haiqing’.

  • Fig. 4.

    Regression of accumulated leaf length and width with the growth days of pak choi ‘Huawang’.

  • Fig. 5.

    Regression of the changes in plant height with the growth days of three varieties of pak choi.

  • Fig. 6.

    Regression of the changes in plant width with the growth days of three varieties of pak choi.

  • Fig. 7.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Xinxiaqing 5’.

  • Fig. 8.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Haiqing’.

  • Fig. 9.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Huawang’.

  • Fig. 10.

    Regression of the changes in plant height change and the accumulated radiation of three varieties of pak choi.

  • Fig. 11.

    Regression of the changes in plant width compared with the accumulated radiation of three varieties of pak choi.

  • Beccafichi, C., Benincasa, P., Guiducci, M. & Tei, F. 2002 Effect of crop density on growth and light interception in greenhouse lettuce. VI International Symposium on Protected Cultivation in Mild Winter Climate: Product and Process Innovation Acta Hort. 614 507 513 https://doi.org/10.17660/ActaHortic.2003.614.75

    • Search Google Scholar
    • Export Citation
  • Bie, Z., Ito, T. & Shinohara, Y. 2004 Effects of sodium sulfate and sodium bicarbonate on the growth, gas exchange and mineral composition of lettuce Scientia Hort. 99 215 224 https://doi.org/10.1016/S0304-4238(03)00106-7

    • Search Google Scholar
    • Export Citation
  • Cai, S., Wu, B., Liao, S., Wu, J., Liu, X. & Lei, J. 2020 Dynamic simulation of physiological index of Brassica chinensis L. in greenhouse based on light and temperature function J. Southern Agr. 51 2191 2198 https://doi.org/10.3969/j.issn.2095-1191.2020.09.018

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Xiaotao Ding Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China; and Shanghai Dushi Green Engineering Co., Ltd., Shanghai 201106, China

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Hongmei Zhang Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Lizhong He Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Haijun Jin Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Qiang Zhou Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China; and Shanghai Dushi Green Engineering Co., Ltd., Shanghai 201106, China

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Juan Yang Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Weimin Zhu Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Jizhu Yu Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Tingting Qian Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China

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Contributor Notes

This work was supported by Agriculture Research System of Shanghai, China (grant no. 202102) and Shanghai Science and Technology Committee Program (19DZ2281300 and 21N21900700).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

X.D. and H.Z. contributed equally to this work.

X.D., H.Z., J.Y., and T.Q. conceived and designed the experiments. X.D., H.Z., L.H., H.J., and T.Q. performed the experiments. H.Z., X.D., and T.Q. analyzed the data. X.D., H.Z., L.H., H.J., Q.Z., J.Y., W.Z., J.Y., and T.Q. contributed reagents, materials, and/or analysis tools. X.D. and T.Q. wrote the manuscript.

J. Y. and T.Q. are the corresponding authors. E-mail: 13636569665@163.com or qiantingting@saas.sh.cn.

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  • Fig. 1.

    Measured leaf length and width of pak choi in the experiment. The leaf length was measured from the lamina tip to the intersection of the lamina and petiole along the lamina midrib. The leaf width was measured from tip to tip between the widest lamina lobes.

  • Fig. 2.

    Regression of accumulated leaf length and width during the growth days of pak choi ‘Xinxiaqing 5’.

  • Fig. 3.

    Regression of accumulated leaf length and width with the growth days of pak choi ‘Haiqing’.

  • Fig. 4.

    Regression of accumulated leaf length and width with the growth days of pak choi ‘Huawang’.

  • Fig. 5.

    Regression of the changes in plant height with the growth days of three varieties of pak choi.

  • Fig. 6.

    Regression of the changes in plant width with the growth days of three varieties of pak choi.

  • Fig. 7.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Xinxiaqing 5’.

  • Fig. 8.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Haiqing’.

  • Fig. 9.

    Regression of the accumulated leaf length and width with the accumulated radiation of pak choi ‘Huawang’.

  • Fig. 10.

    Regression of the changes in plant height change and the accumulated radiation of three varieties of pak choi.

  • Fig. 11.

    Regression of the changes in plant width compared with the accumulated radiation of three varieties of pak choi.

 

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