Growth characteristics of cabbage plug seedlings due to mutual shading among neighbouring seedlings

b i o s y s t e m s e n g i n e e r i n g 1 2 1 ( 2 0 1 4 ) 7 7 e8 4

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Research Paper

Growth characteristics of cabbage plug seedlings due to mutual shading among neighbouring seedlings Takashi Fukushima*, Kunio Sato, Takashi Ohi, Mansu Cho Graduate School of Bioresources, Mie University, Kurimamachiyacho 1577, Tsu, Mie 514-8507, Japan

article info

Plug seedlings are increasingly used in vegetable cultivation in Japan, because they are

Article history:

suitable for machine operations and are disease resistant; however, in cabbage cultivation,

Received 1 October 2013

variation in seedling growth affects plant growth after transplanting to the field, and

Received in revised form

eventually, harvesting all the cabbages at the same time is not possible. In this paper, a

12 February 2014

simulation model used to express the growth variation in cabbage plug seedlings is pro-

Accepted 20 February 2014

posed to reveal their cultivation characteristics and consider a cultivation technique that

Published online 13 March 2014

would produce uniform growth among seedlings. In this simulation model, the mutual shading among neighbouring plug seedlings resulting from high-density planting, which is one of the factors of variation in seedling growth, was modelled. The model parameters were obtained from the results of a cultivation experiment comparing growth against the light quantity that seedlings could receive; however, there were differences between the growth of a single seedling in the cultivation experiment and the growth of the plug seedlings. It is believed that growth rate and mass would be greater for a single seedling than for the plug seedlings. This simulation was able to express the growth variation of the actual plug seedlings by adjusting the model parameters. ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.

1.

Introduction

Plug trays are often used to raise seedlings (Fig. 1) because they are easy to produce and manage and are suitable for use with an automatic seeding machine and seedling transplanter. In addition, high-quality production in a large-scale seedling-raising facility improves the productive efficiency of each farmer, helping them cope with the decreasing labour force in Japanese agriculture (Fujiwara, Yoshioka, & Sato, 1999). Plug seedlings are used mainly for growing fruits,

vegetables, and flowers. However, this method is known to have several disadvantages (Oda, 2007). When seedlings are raised using plug trays, the soil area is limited, soil moisture is low, and seedling density is high. Under such harsh environmental conditions, plug seedlings suffer from multiple stressors as they grow, such as limited root area and mutual shading, and exhibit effects such as the following: (1) restricted growth after transplanting to the field because of excessive growth of the root ball during the seedling stage, (2) changes in physiological responses such as the production of plant hormones and water potential, (3) reduced seedling

* Corresponding author. Tel./Fax: þ81 59 2319597. E-mail address: [email protected] (T. Fukushima). http://dx.doi.org/10.1016/j.biosystemseng.2014.02.007 1537-5110/ª 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.

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b i o s y s t e m s e n g i n e e r i n g 1 2 1 ( 2 0 1 4 ) 7 7 e8 4

Nomenclature t tg ti W gw Kw A B Li gL1 KL1 Ri gRi KRi Si Q Qr PPFD

Days after sowing, d Days to germination, d Emergence date of true leaf, d Seedling dry mass, mg Increase rate in seedling dry mass Increase potential of seedling dry mass, mg Maximum rate parameter of seedling dry mass increase Coefficient in equation for seedling dry mass increase True leaf petiole length, mm Growth rate of Li Growth potential of Li, mm True leaf radius, mm Growth rate of Ri Growth potential of Ri, mm Overlap area between true leaves, mm2 PPFD value, m mol m2 s1 Relative effective light Photosynthetic photon flux density

quality because of excessive elongation, and (4) reduced seedling uniformity. These issues have been reported in vegetables and flowers including cabbage (Brassica oleracea L.; Sato et. al., 2003), tomatoes (Lycopersicon esculentum Mill.; Nobuoka, Nishimoto, & Toi, 2005), snap beans (Phaseolus vulgaris L.; Carmi, 1993), cucumbers (Cucumis sativus L.; Robbins & Pharr, 1988), spinach (Spinacia oleracea L.; Shimizu, Yoshioka, Fukuoka, & Fujiwara, 1995), and Chrysanthemum morifolium (Dendranthema grandiflora Kitamura; Goto, Masaoka, Kageyama, & Konishi, 1998). Although Japanese cabbage cultivation systems use agricultural machinery to improve efficiency and reduce labour, harvesters are not used because of the non-uniform growth of the products. When a harvester is used, the cabbages must all be harvested at one time, and this is not possible when growth

is very variable. The uniformity of the cabbage head is related to growth after transplanting to the field (Fujiwara, Yoshioka, & Sato, 2000; Kenmochi, 2002); therefore, seedling quality is important in cabbage cultivation. It has been reported, however, that variation in growth has been observed at approximately 20 d after transplanting, even though the plug seedlings had high uniformity during the seedling stage, and seedlings grown in the nursery showed a higher degree of growth uniformity than the plug seedlings after transplanting (Kenmochi, 2002). Other studies have reported a long growth period in the field (Takegawa & Ohnishi, 1996) and a limited time for transplanting (Shiraki, 1999, pp. 32e42). These studies assessed seedling growth by measuring the apparent size of the seedling, such as plant height and fresh mass; however, these indices would not be indicative of substantive seedling quality. Consequently, we assessed seedling quality by measuring seedling dry mass, which is related to root growth and the formation of the root ball (Fukuoka, Yoshioka, Shimizu, & Fujiwara, 1996), as seedling quality. This paper proposes the use of a simulation model to express growth variation in cabbage plug seedlings to understand cultivation characteristics and to consider cultivation techniques that would produce uniform seedlings. The actual growth of cabbage plug seedlings varies, even though the apparent size of the seedling appears to be uniform. This variation would be caused by stressors such as high-density cultivation and limited soil area. We focused on the mutual shading of plug seedlings resulting from high-density cultivation. Little has been reported about the influence on the growth of the interaction among plug seedlings, although some studies have reported on the environmental controls used in seedling-raising facilities (e.g. Fujiwara, Yoshioka, Kumakura, Sato, & Nakagawa, 2003). An investigation of the interactions among plug seedlings would also need to consider the cultivation method, and to do so, the cultivation characteristics of the plug seedlings as a result of their interactions will need to be revealed. In this paper, the cultivation experiment assumed mutual shading of the seedlings, and the parameters used in the simulation were evaluated based on the experimental results. In this simulation, the increase in seedling dry mass was expressed using a general growth model, and the parameters in the growth model were set to vary according to the extent of shade on neighbouring seedlings. The simulation was verified by comparing growth variation between experimental and simulated results.

2.

Material and methods

2.1.

Cultivation experiments

2.1.1. Experiment I: light-shading experiment to determine growth rate in the simulation model

Fig. 1 e Cabbage plug seedlings.

The decrease in photosynthesis resulting from shading in the interaction among plug seedlings would be a key factor in the non-uniformity of cabbage seedlings. It has been reported that respiration activity and dry mass decreased with the extent of shade and defoliation treatments in cabbage (Sato, Higashio, Uragami, & Tokuda, 2004). It is obvious that light restriction affects substantive seedling growth. The relationship between

b i o s y s t e m s e n g i n e e r i n g 1 2 1 ( 2 0 1 4 ) 7 7 e8 4

Table 1 e Measured conditions. (a) Experiment I Variety

Plug tray Environmental setting of chamber

PPFD conditions during light period

Coverage pattern Coverage duration Number of samples (b) Experiment II Variety

Plug tray Environmental setting of chamber

PPFD conditions during light period Number of samples

‘Matsunami’ (Ishii Seed Growers Co., Ltd., Shizuoka, Japan) 128 holes (volume of 40.5 cm3 per plug hole) Light period: 13 h, 30  C, 75% relative humidity (RH) Dark period: 11 h, 26  C, 90% RH High PPFD: 386 m mol m2 s1 Low PPFD: 167 m mol m2 s1 0%, 50%, 75% 16e28 d after sowing (for 12 d) 15 per coverage pattern ‘Matsunami’ (Ishii Seed Growers Co., Ltd., Shizuoka, Japan) 128 holes (volume of 40.5 cm3 per a plug hole) Light period: 13 h, 30  C, 75% RH Dark period: 11 h, 26  C, 90% RH High PPFD: 386 m mol m2 s1 128

the growth rate of cabbage seedlings and effective light, calculated from measured results under the conditions of covered true leaves or varying light intensities in the controlled growth chamber, was examined. The cabbage cultivar ‘Matsunami’ (Ishii Seed Growers Co., Ltd., Shizuoka, Japan) was used in this experiment. The seedlings were grown in plug trays (128 holes, cell size 30  30  45 mm) using commercially available soil and vermiculite for raising seedlings in the growth chamber (CF415, Tomy Seiko Co., Ltd., Tokyo, Japan), and one seed per hole was sown. Until 3 d after sowing, the temperature was 20  C; the relative humidity (RH) was 80% under dark conditions; and, except for the initial watering after seeding, the seeds were not watered until the fourth day to prevent them from moving with water flow. In addition, the plug tray was covered with thin paper to prevent drying. The experimental conditions from 4 d after sowing are shown in Table 1(a). There were two PPFD conditions during the 13-h light period. In this study, the light intensity is expressed as photosynthetic photon flux density (PPFD). The base of each seedling was watered each day shortly after the beginning of the light period and liquid fertiliser (HYPONeX N:P:K ¼ 6:10:5, HYPONeX Japan Co., Ltd., Osaka, Japan) was applied at 12 and 22 d after sowing. Each seedling was grown separately at 10 d after sowing because the seedlings in the plug trays begin to have contact with neighbouring seedlings at approximately 13 d. The true leaves of the seedlings were covered with aluminium foil at 13 d, as shown in Fig. 2. Sampling consisted of 3 conditions of coverage (0%, 50%, and 75%) with 15 samples in each coverage condition for a total of 45 samples. The true leaves and the aluminium foil were

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monitored each day and adjusted to keep the proper coverage, because both the number and area of true leaves increased daily. In addition, the distance between the seedlings was monitored so that there was no contact among neighbouring seedlings. Five samples per coverage group were selected at 14, 21, and 28 d after sowing, and dry mass, true leaf-stem length, and dimensions of the true leaf were measured.

2.1.2. Experiment II: Cultivation experiment to verify the simulation model The cabbage cultivar ‘Matsunami’ (Ishii Seed Growers Co., Ltd., Shizuoka, Japan) was used in experiment II. The seedlings, fertilisation, and watering were similar to those in experiment I. An empty hole, in which seed did not germinate, was filled with a backup seedling. The experimental conditions are shown in Table 1(b). The dry mass of each seedling was measured at 28 d after sowing.

2.2.

Growth simulation of plug seedlings

2.2.1.

Outline of simulation

The plug tray used in this study contained 128 holes and is the type generally used in Japanese cabbage cultivation. The growth model was used to assess plant growth in each of the holes. A logistic function (Hsu, Nelson, & Chow, 1984) was used for the increase in seedling dry mass, and Richards’ function (Osumi & Ishikawa, 1983) was used for the growth of the true leaves. One seedling was added to each hole, and the seed’s mass, day of germination, and true leaf direction (set randomly at the initial state) were recorded. After the simulation began, the true leaves grew with time and overlapped with those of neighbouring seedlings. The vertical positions of the true leaves were determined by the germination day. The true leaves of the seedling that germinated the earliest were located above those of the seedlings that germinated later. The growth rate in the growth model of the lower seedling varied according to the amount of overlap with the neighbouring true leaves. The increase in seedling dry mass was calculated using its growth rate by time step until 28 d after sowing.

Fig. 2 e Light-shading experiments. True leaves were covered with aluminium foil. Each seedling was grown without contact with neighbouring seedlings.

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2.2.2.

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Growth model of seedling dry mass

2.2.3.

The increase in seedling dry mass, which would indicate substantive seedling quality, was expressed in this simulation. The logistic function (Eq. (1)) that would be similar to the growth curve of the seedling dry mass was used.   dW W ¼ gW W 1  dt KW

(1)

where Kw is increase potential of seedling dry mass W (mg), and gW is increase rate of seedling dry mass W. The logistic function was devised as a population growth model and is now widely applied to measure the growth and proliferation of various organisms (Iwasa, 1998, pp. 2e12). The growth rate in this simulation varied by the amount of light that the true leaf received according to the overlap area with neighbouring true leaves over time and as the seedlings grew. The growthmass increment per unit time was calculated by Eq. (2), which discretised Eq. (1), and seedling dry mass was derived by their integrated value.   W Dt DW ¼ gW W 1  KW

(2)

Growth rate is discussed in section 2.2.4. The initial mass was randomly set from 1.0 to 5.0 mg, which follows the distribution of actual cabbage seeds.

Growth model and overlap of true leaves

Overlap of true leaves would be influenced by the true leaf direction and the three dimensional structure such as leaf stem tilt, leaf angle, leaf width and leaf length. However, it would be difficult to consider all of them in the simulation. In this model, a true leaf was approximated by a circle and a petiole was expressed as a line in two dimensions to more easily determine the overlap of leaves, as shown in Fig. 3. The radius of the leaf was the average of the horizontal and vertical lengths of the actual leaf. The emergence of 2 true leaves was simulated, because the first and second true leaves generally overlapped during the seedling stage. The direction of the first true leaf was randomly set, and that of the second leaf was set in the opposite direction. The increase in the true leaf radius and the petiole length were expressed by Richards’ function, as shown in Eqs. (3) and (4), because the error in the measured curve-fitting data was lower using this function than with the logistic function.  3 Ri ¼ KRi 1  egRi ðtti Þ

(3)

 3 Li ¼ KLi 1  egLi ðtti Þ

(4)

where Ri and Li are leaf radius and petiole length (mm), KRi and Li are increase potential of Ri and Li (mm), gRi and gLi are increase rate of Ri and Li, and ti is emergence date of true leaf (d).

Fig. 3 e Representation of true leaves in the simulation. (a) True leaves are shown as circles. (b) Direction of the first true leaf emergence was determined at random. Direction of the second true leaf was determined to be opposite that of the first true leaf. (c) Overlap area S between each leaf was calculated.

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Table 2 e Measured results of (a) dry mass of plug seedling, (b) petiole length, and (c) leaf area of the first true leaf in the light-shading experiment. Days after sowing, d

High-PPFD

Low-PPFD Coverage, %

0 (a) Dry mass of plug seedling, mg 14 57.4 a 21 202 a 28 372 a (b) Petiole length of the first true leaf, mm 14 21.9 a 21 30.5 a 28 33.4 a (c) Leaf area of the first true leaf, mm2 14 788 a 21 1151 a 28 1172 a

50

75

0

50

75

59.0 a 173 ab 354 ab

50.0 a 168 abc 306 ab

45.6 a 141 bcd 286 bc

45.2 a 122 cd 229 c

44.6 a 100 d 216 c

23.0 a 33.0 a 37.9 a

24.2 a 35.7 a 35.4 a

24.3 a 53.2 b 48.9 b

26.0 a 45.1 b 48.6 b

26.0 a 47.5 b 50.2 b

877 a 1186 a 1368 a

806 a 1269 a 1265 a

902 a 1531 a 1548 a

922 a 1508 a 1549 a

866 a 1308 a 1503 a

Means in each row with similar letters are not significantly different at 5% level by Tukey test.

The parameters for growth rate and potential were constant during the calculation, and were obtained from previous experimental results. Overlap was determined from the relationship between the centre-to-centre distance of two leaves and the sum of the radii of the two leaves. The scope of calculating overlap area was defined with the surrounding 8 seedlings of each seedling. However, for simplicity, the overlap between only 2 seedlings of which the overlap area is largest in the 8 seedlings was calculated, without determining the overlap between more than 2 seedlings.

2.2.4.

Growth rate and effective light

Growth rate in the seedling dry mass model varied according to the amount of light that the true leaf received; however, for simplicity, the growth rate in the true leaf model remained constant in this simulation. The effective light, which was obtained using the product of the non-overlap area and PPFD value, and the relative effective light Qr, which was the amount of light relative to the greatest light in experiment I, were defined. The relationship between the relative effective light and the growth rate of the seedling dry mass was obtained from the results of the light-shading experiment, in which the growth rate was assumed to be 0 when the effective light is 0 and peaks as the effective light increases. The growth rate gW and the relative effective light Qr are expressed by Eqs. (5) and (6): A$Qr B þ Qr

(5)

pRi  Si Q 1 Si Q þ $ $ $ 386 3 pRi 386 pRi

(6)

gW ¼

Qr ¼

where A is maximum rate parameter of seedling dry mass increase, B is coefficient in equation for seedling dry mass increase, Ri is true leaf radius (mm), Si is overlap area between true leaves (mm2), and Q is PPFD value (m mol m2 s1). In relative effective light, the light in the overlap area should be considered, because a leaf that is under another leaf is not entirely shaded; therefore, it was believed that the growth rate

would not decrease by much and the seedling in which the growth is extremely low would not be observed. Light in the overlap area was determined as one-third of the standard light from a simple measurement that examined the level of light permeability of the leaf.

3.

Results and discussion

3.1.

Results of light-shading experiment

Data for seedling dry mass, petiole length of the first true leaf, and leaf area of the first true leaf are shown in Table 2. There were significantly different between both PPFD conditions in dry mass and petiole length; it was not in leaf area. Data for the second true leaf are not shown because they were the same as those for the first true leaf. Under both PPFD conditions, dry mass was greater in the 0% coverage group than in the 75% coverage group; the difference increased as the seedlings grew and increased exponentially under each condition. It is a logical result that plant grows according to the amount of light. However, Petiole length and leaf area in the 0% coverage group were relatively low; it is especially true under high-PPFD conditions. In contrast, the third and fourth true leaves under low-PPFD conditions grew faster than usual. Under the specific light conditions in this experiment, such as leaf shading and low intensity light, it was assumed that limiting the light available for photosynthesis would elicit a seedling response such as greater and faster growth of the true leaves. Thus, the seedling would elongate because of the shortage of light. Seeding dry mass would be a suitable index of seedling growth according to the difference in light, because the influence of light conditions was clearly reflected in the results of the dry mass measurements.

3.2.

Growth rate

In this paper, the effective light calculated from the product of the non-overlap area and the PPFD value was defined. The

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Table 3 e Relative effective light calculated from leaf coverage and PPFD conditions. Coverage, %

Relative effective light, Qr

High-PPFD

Table 4 e Principal parameters in simulation model. Parameter

Low-PPFD

0

50

75

0

50

75

1.000

0.500

0.250

0.433

0.217

0.108

relative effective light normalised by the greatest light in the light-shading experiment was also defined. The relative effective light was obtained by the high- and low-intensity light conditions and the coverage, as shown in Table 3. The growth rate against the relative effective light plotted in Fig. 4 was calculated by fitting the growth data obtained in the lightshading experiment with the logistic function (Eq. (1)). The solid line in Fig. 4 indicates the equation (Eq. (5)) for growth rate in terms of relative effective light.

3.3. Comparison between cultivation experiment and simulated results The simulation parameters are shown in Table 4. The key statistics and a histogram of the experimental and simulated results are shown in the first and second rows of Table 5 and in Fig. 5. The horizontal axis of the histogram was divided according to Sturges’ formula and was based on the experimental results. At first, the growth potential of seedling dry mass, Kw, was determined based on the data obtained at 0% coverage in experiment I; however, the seedlings in experiment I that were grown alone grew better than the plug seedlings. Therefore, the Kw of the simulation was as adjusted so that the average of the experimental and simulated dry mass were equal. As a result, although each average of seedling dry mass was within the same range, the two heaviest categories of seedlings were not represented in the simulation. Thus, in this simulation, plug seedling growth, especially growth variation, would not be expressed by the regulation of Kw.

Fig. 4 e Relationship between effective light and growth rate. Plots indicate growth rate calculated from measurements, and line is growth rate predicted by Eq. (5).

Symbol

Days to germination, d

tg

Emergence date of first leaf, d Emergence date of second leaf, d Leaf direction, degree

t1 t2 q

Seedling dry mass Initial mass, mg Growth potential, mg Coefficient of growth rate Coefficient of growth rate First true leaf Petiole length potential, mm Stem growth rate Leaf radius potential, mm Leaf radius growth rate Second true leaf Petiole length potential, mm Stem growth rate Leaf radius potential, mm Leaf radius growth rate PPFD value, m mol m2 s1 Time step, d Number of seedlings a

Value Random from 3 to 5 tg þ 5 tg þ 8 Random from 0 to 360

Kw A B

Random from 1.0 to 5.0 270, 360a 0.267 0.103, 0.212a

KL1 gL1 KR1 gR1

32.6 0.343 19.3 0.461

KL2 gL2 KR2 gR2 Q Dt

26.8 0.4 19.5 0.484 386 0.417 128

Each value indicates before and after adjusting.

3.4.

Adjusting the simulation parameter

From the result of the preceding section, parameter B, which determined growth rate, was adjusted to express variation in seedling growth while maintaining an average of seedling dry mass calculated in the simulation. In the equation of growth rate (Eq. (5)), parameter A expresses the convergent value and parameter B expresses the slope of increasing growth rate. The growth rate against the relative effective light shown as a line in Fig. 4 was calculated from the results of the light-shading experiment. Each seedling in the lightshading experiment was grown alone, whereas each seedling in the plug tray was grown under restricted environmental conditions, such as shading by neighbouring seedlings and different temperature and humidity distributions. The growth rate of the plug seedlings was lower than that of the seedlings grown alone. Thus, coefficient B was changed while coefficient A was fixed, as shown in Fig. 6, so that the simulated dry mass corresponds to the measured dry mass at 14 d, when little interaction from neighbouring seedlings was observed. In addition, Kw was regulated in the same way as in the preceding section. Growth simulation of the cabbage plug seedlings was carried out again using Kw of 360 mg and coefficient B of 0.212, and with the other parameters remaining unchanged, as shown in Table 5. Key statistics and a histogram of simulation results with adjusted growth rate are shown in the third row of Table 5 and in Fig. 7. The adjusted parameters in this simulation gave positive results in growth variation and seedling mass; therefore, the growth variation of the cabbage plug seedlings was revealed.

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Table 5 e Key statistics of experimental and simulated results. Average

Maximum

Minimum

Standard deviation

203.6 207.0 205.5

298.0 242.0 276.0

109.0 125.0 104.7

44.8 28.2 42.8

Experimental seedling mass (experiment II), mg Simulated seedling mass before adjusting growth rate, mg Simulated seedling mass after adjusting growth rate, mg

Fig. 5 e Histogram of measured and simulated seedling dry mass. White bars indicate measured value and grey bars indicate simulation values.

Fig. 7 e Histogram of measured and simulated seedling dry mass. White bars indicate measured values, and black bars indicate simulation values with adjusted growth rate.

4.

cultivation experiment and assumed mutual shading of the seedlings. In particular, the growth rate varied with the relative effective light, defined as the standardised amount of light that the true leaf receives, according to the overlap area of true leaves. As a result, this simulation was able to express growth variation and seedling mass in the plug seedlings. In the future, this simulation will be used to identify cultivation methods, such as size of the plug tray and amount of light supplement, that would produce uniformity in plug seedlings.

Conclusion

Growth variation in cabbage plug seedlings after transplanting to the field is an issue in Japanese cabbage cultivation. In this paper, a simulation model to express growth variation in cabbage plug seedlings caused by mutual shading from high-density cultivation was proposed to reveal cultivation characteristics. The growth of each seedling is expressed with the growth model as represented by the logistic function. Its parameters were obtained from the

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Fig. 6 e Adjustment of the predicted growth rate. Line is the original growth rate and dash line is the adjusted growth rate.

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