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Responses of three cucumber varieties (Cucumis sativus L.) in lowland humid tropics to planting season and NPK fertilization: gender expression, yield and relationship between yield and related traits

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https://www.eduzhai.net/ International Journal of Agriculture and Forestry 2015, 5(1): 30-37 DOI: 10.5923/j.ijaf.20150501.05 Response of Three Cucumber Varieties (Cucumis sativus L.) to Planting Season and NPK Fertilizer Rates in Lowland Humid Tropics: Sex Expression, Yield and Inter-Relationships between Yield and Associated Traits Nwofia G. E.*, Amajuoyi A. N., Mbah E. U. Department of Agronomy, Michael Okpara University of Agriculture, Umudike, Nigeria Abstract The response of three cucumber varieties (Ashley, Betalpha, and marketmore) to different rates of fertilizer (NPK 15:15:15) application were evaluated in two seasons (early and late) under rain-fed conditions in 2011 cropping season. The experiment was laid out in a split-split-plot in randomized complete block design with three replications. Seasons, (early and late rains) constituted the main plots, while cucumber varieties were fitted into the sub-plots with NPK fertilizer rates into sub-sub-plots. The results revealed significant increase in fruit yield of cucumber during the early planting season under rain-fed conditions in the humid tropics. During both cropping seasons, the application of N:P:K 15:15:15 fertilizer increased fruit yield of cucumber significantly up to 120 kg/ha. However, further increase did not affect fruit yield, which implies that 120 kg/ha fertilizer rate is the optimum quantity required for increased cucumber fruit yield. The interaction between cucumber variety and planting season significantly induced higher fruit yield in market-more compared to the other varieties tested. Principal component analysis showed that PC1, PC2 and PC3 with eigen-vector value loads greater than unity accounted for the cumulative variance of 70%, which exhibited the degree of influence the plant characters had on fruit yield. Pearson correlation indicated a highly significant (P<0.01) and positive correlation between fruit yield and weight of fruit (0.574**) as well as number of fruits per plant (0.574**). Cause and effect analysis revealed that maximum direct effect on fruit yield of cucumber was achieved through fruit weight (0.565) and number of fruits per plant (0.457). This implies that in selection for high yields, premium should be placed on these characters. Keywords Cucumis sativus, Yield attributes, Correlation, Principal component analysis, Path coefficient analysis 1. Introduction Cucumber (Cucumis sativus L.), which is one of the monocecious annual crops of the cool climates belongs to the cucurbitaceae family comprising of 70 genera and 750 species (Thoa, 1998; Best, 2000). According to Shetty and Wehner (2002a) as well as Arunkumar et al. (2011a) the fruit of cucumber, which is soft and succulent is consumed raw (salad) or cooked with other vegetables. The nutritional composition of cucumber fruit per 100 g edible portion is carbohydrate (3%), protein (1 %), total fat (0.5% and dietary fibre (1%) (USDA, National Nutrient Data Base, 2014). The fruit is a veritable source of vitamins such as vitamin A, C, K, E, among others; minerals such as magnesium, potassium, * Corresponding author: enwofia@yahoo.co.uk (Nwofia G. E.) Published online at https://www.eduzhai.net Copyright © 2015 Scientific & Academic Publishing. All Rights Reserved manganese, phosphorus, calcium and zinc as well as a number of phyto-nutrients (carotene-B, Xanthein-B and lutein) which add and enrich the diet of people living in the tropical regions (Vimale et al., 1999). The crop is grown worldwide and according to Tatlioglu (1993) and ranks fourth in the list of economic vegetables in Asia after tomato, cabbage and onion. Cucumber rarely grows luxuriantly in infertile soils, hence, its level of susceptibility to poor soil fertility manifests in the form of low fruit yield, bitter and misshapen fruits that have little marketability value. Belay et al. (2001), Eifediya and Remison (2010) in their various studies on nutrient requirements of cucumber reported that cucumber responds positively to organic, inorganic or combined nutrient applications for optimum growth and productivity. However, the nutrient requirements of the crop vary depending on soil type, native fertility, previous cropping and cultural practices. Crop varieties in different seasons or environments react International Journal of Agriculture and Forestry 2015, 5(1): 30-37 31 differently to a range of climate conditions, soil characteristics and technical practices (Makinde et al., 2009; Singh and Ram, 2012). In the humid tropics characterized by bimodal weather condition, cucumber production is gaining increased attention and its cultivation cuts across the seasons. However, details on the crop’s responses to the different seasons vary, hence demands attention aimed at improving its productivity. Generally, cucumber produces male and female flowers separately on the same individual plant (monocecious), though some may produce bisexual flowers (Perl-Treves, 1999). This implies that sex expression in the plant is subject to regulation by a number of environmental factors such as photoperiod, temperature and plant hormones (Yamasaki et al., 2005). According to Staub et al. (2005) as well as Wehner and Guner (2004) increase in cucumber yields can be achieved through breeding for disease resistance, use of improved cultural practices and improvements in gynecious sex expression which tend to promote the production of pistillate flowers. Critical studies on character responses of some cucumber varieties to planting season, rates of NPK fertilizer application and planting season are highly limited, especially in the lowland humid tropics. Therefore, the objectives of this study were to: determine the effects of NPK (15:15:15) fertilizer rates on sex expression of three cucumber varieties, determine the effect of early- and late-season planting and NPK fertilizer rates on the growth and yield of the cucumber varieties and to determine the inter-relationship between yield and yield components of cucumber as to identify areas that require breeding concentration and advancements. 2. Materials and Methods The field experiments with three varieties of cucumber (Ashley, Betalpha and Market-more) were conducted in two seasons [wet (early season) and dry (late season)] in 2011 at Umuafia, Ohokobe, Ndume, Abia State, Nigeria (05º 35´ N, 07º 51´ E, 122 masl); a community located about 5 km from Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria in the humid tropics. The location is characterized by a distinct wet and dry season with a bimodal pattern of rainfall distribution. According to Allaby (2002), the agro-ecological zone has a distinctive short dry spell in August which separates the two peaks of the rainy season in July and September. During the cropping seasons, (2011), the mean rainfall between March and May and between September and November was 223.8 mm and 219.40 mm, respectively while the mean minimum and maximum temperatures of the area were 23℃ and 32℃ (early season) and 22℃ and 30℃ (late season), respectively (Table 1). Prior to planting in early- and late-season cropping, soil samples were collected randomly form different locations in the site at a depth of 0-20 cm, bulked together and a composite sample collected, air-dried and sieved through a 2 mm sieve for laboratory soil analysis following standard procedures and the results are as shown in Table 2. Particle size distribution of the sampled soils was determined by Bouyoucos hydrometer method as outlined by Gee and Bander (1986) while the pH was determined using a suspension of soil and distilled water in the ratio of 2:5 soil water, which was stirred for 30 minutes and the pH value read with the aid of a glass electrode pH meter (Mclean, 1982). Available phosphorus was colorimetrically determined by Bray II method (Olsen and Sommers, 1982) while total nitrogen was determined following Kjeldahl digestion procedure (Bremner and Mulvaney, 1982). Soil exchangeable calcium (Ca), magnesium (Mg), sodium (Na), and potassium (K) were extracted with neutral ammonium acetate. The Ca and Mg in the extracted leachate were determined by ethylenediaminetetraacetic acid (EDTA) titration method (Lanyon and Heald, 1984) while Na and K were determined by flame photometric method (Kundsen et al., 1982). The experiments were conducted on a sandy loam soil that belongs to the order ultisol and classified as paleustult (FDALR, 1985). Table 1. Agro-meteorological data of the early and late planting season of the study area Month / Season Early season March April May Total Mean Late season September October November Total Mean Rainfall (mm) Amount Days 111.4 10 166.3 9 393.7 20 671.4 39 223.8 393.61 21 251.8 14 12.7 4 658.10 39 219.40 Temperature (ºC) Min Max 22 23 23 68 22.67 32 30 33 95 31.67 21 22 22 65 21.67 32 30 29 91 30.33 Relative humidity (%) 86 83 82 251 83.67 87 86 83 256 85.33 Table 2. Physico-chemical properties of the soils 0f the experimental sites for the early and late cropping seasons Attributes Sandy (%) Silt (%) Clay (%) Textural class pH (H2O) Available P (mg/kg) Total N (%) Organic matter (%) Mg (Cmol/kg) K (Cmol/kg) Na (Cmol/kg) Early season 92.33 1.09 6.58 Sandy loam 6.08 9.67 0.011 4.971 1.04 280.0 0.86 Late season 92.42 1.07 5.51 6.06 9.05 0.095 7.895 0.92 280 0.94 32 Nwofia G. E. et al.: Response of Three Cucumber Varieties (Cucumis sativus L.) to Planting Season and NPK Fertilizer Rates in Lowland Humid Tropics: Sex Expression, Yield and Inter-Relationships between Yield and Associated Traits Cucumber seeds obtained from the sub-station of National Institute of Horticultural Research, Mbato, Okigwe, Imo State, Nigeria were sown in flat beds at a spacing of 25 x 75 cm, which gave a plant population of 53,333 plants/ha. The experiment was laid out in split-split-plot in randomized complete block design with season (early and late) as the main plot, cucumber varieties (Ashley, Betalpha and Market-more) as the sub-plot and NPK fertilizer rates (0, 60, 120, 180, 240, 300 kg/ha) as the sub-sub-plot. There were three replications. All data measurements were taken on a sample of four plants randomly selected in each plot. Sex expression attributes such as male and female flowers were determined at two days intervals by counting and the ratio obtained at the end of the experiment by dividing the male flowers against the female flowers. Cucumber fruits were harvested at six days intervals as they mature. Number of fruits per plant was obtained by counting and each fruit from all sampled plants was weighed with a sensitive electronic scale. Fruit length was obtained by measuring the fruit with a graduated rule from the fruit stalk to the tip of the fruit while fruit girth was obtained by measuring the fruit diameter with mathematical dividers and then the reading taken on a meter rule. Fruit yield was obtained as the cumulative weight of the fruits per plot and the total yield converted to tons per hectare. All collected data were subjected to analysis of variance using Genstat Discovery Edition 3 Software (Genstat, 2003). Mean separation was done according to Obi and Obi (2002) using least significant difference (LSD) at 5% probability level. Principal component analysis (PCA), which is a multivariate technique used in the analyses of series of data which observations are explained by several inter-correlated quantitative dependent variables was used to measure the genetic diversity in the selected cucumber varieties (Abdi and Williams, 2010). Principal components of plant characters are known to be orthogonal and normally independent of each other. According to Mohammadi and Prasanna (2003), the total variation obtained in the original data may be broken down into components that are cumulative in nature. PCA also, helps us to identify the genetic distance between crop genotypes. Our data was therefore analyzed according to PRINCOMP procedure using SAS software (SAS Institute Inc., 2002). Multiple correlation coefficients were obtained between all possible combinations of traits using Pearson correlation coefficients analysis with the help of SPSS for windows version 17.0 software (2010) following the procedure outlined by Miller et al. (1958) and the significance tested by referring to the biometrical standard table (Steel et al., 1997). Path coefficients analysis was done based on Dewey and Lu (1959) and Wright (1960; 1934) to partition the correlation coefficients of the traits into direct and indirect effects. It was achieved by generating standardized partial regression coefficients (path coefficients) that were independent of the original units of measurement. A large path coefficients is an indication that the resultant change will show a proportional (or inversely proportional) change in another correlated trait, whereas weak path coefficients is an indication that the resultant change will have insignificant effect on the second trait. 3. Results and Discussion The yield and yield attributes of three cucumber varieties as influenced by planting season and NPK fertilizer rates are shown in Table 3. The results revealed that planting season significantly (P<0.01) affected fresh fruit yield of cucumber while variety, NPK rate and the interaction effects were not significant (P>0.05). Early planting had better yield (2.00 kg/ha) than late planting (0.94 t/ha), which indicated 112.8% increase in yield compared to the late planting season. This implied that in this agro-ecological zone (humid tropics), cucumber is best cultivated during the early planting season when the rains are relatively stable with less cloudiness. Contrarily, Makinde et al. (2009) in their studies on maize/cucumber intercrop in the guinea savanna reported higher cucumber fruit yields under late planting season relative to early planting season. Furthermore, Singh and Ram (2012) indicated that cucumber genotypes grown in multi-environmental structures react differently to a range of climatic conditions, soil characteristics and even technical practices. Among the varieties evaluated (Ashley, Betalpha and Market-more), Ashley had higher yields relative to Betalpha and market-more. However, there was no significant (P>0.05) difference between them. Furthermore, irrespective of the season and cucumber varieties, there was an increase in the yield of cucumber from 0 kg/ha NPK up to 120 kg/ha NPK, and thereafter, there was a progressive yield reduction with further increase in fertilizer application up to 300 NPK kg/ha, suggesting that 120 kg/ha NPK is the optimum NPK (15:15:15) fertilizer rate for the cucumber varieties evaluated in this agro-ecological zone. However, the effect of different rates of fertilizer on yield of the cucumber varieties did not show any significant (P>0.05) difference. The systematic increase in NPK fertilizer rate enhanced the release of essential nutrients, which invariably increased cucumber growth and productivity. The findings are in consonance with studies by Adekiya and Ojeniyi (2002) as well as John et al. (2004). The interaction of planting season and cucumber variety on fruit weight of the evaluated varieties (Table 4) showed that early season planting significantly (P<0.05) gave higher fresh fruit weight (180.13 g/plant) than late season planting (152.0 g/plant), irrespective of the cucumber variety. Among the cucumber varieties, Market-more produced fruit weight that was higher by 14.8% and 24.3% compared to Ashley and Betalpha, respectively, regardless of the planting season. As shown in Table 5, the influence of planting season, variety and N:P:K fertilizer rates on fruit number per plot revealed that there was significant (P<0.05) interaction between planting season, variety and N:P:K fertilizer rate as well as between planting season and N:P:K fertilizer rates. Irrespective of cucumber variety, the application of 240 t/ha N:P:K fertilizer during early season planting gave the highest International Journal of Agriculture and Forestry 2015, 5(1): 30-37 33 number of fruits per plot (15.13) compared with the other N:P:K fertilizer rates studied while 0 t/ha NPK fertilizer gave the lowest (9.22). Similarly, Mahmond et al. (2009), Eifediye and Remison (2010) as well as Shehatal et al. (2012) in their various investigations indicated increased fresh fruit yield of cucumber with the application of inorganic fertilizers, however, they remarked that a combination of inorganic and organic fertilizers induced higher and better quality fruits. Early season planting gave significantly (P<0.05) higher fruit weight per plot compared to late season planting regardless of cucumber variety and N:P:K fertilizer rates used in the study. Principal component analysis (PCA), which is an important multivariate technique employed to examine associations between characters, and measure the genetic diversity in the selected cucumber varieties according to Solanki and Shah, (1989) as well as Abdi and Williams (2010) revealed that only the first three principal component axes (PC1, PC2 and PC3) in the PCA analysis had eigen-vector values whose loads were more than unity (Table 6) while the four principal components altogether accounted for the cumulative variance of 82.60%. The results further showed that PC1, PC2, PC3 and PC4 with eigen-values of 2.3699, 1.4741, 1.0544 and 0.8842, respectively, accounted for 33.9%, 21.1%, 15.1% and 12.6%, respectively of the total variability observed among the three cucumber varieties. In PC1 and PC2, the characters that accounted for most of the variability include number of female flowers, male-female flower ratio, fruit girth and fruit length. PC3 was particularly high in male flowers (0.6592), fruit number (0.5029) and male-female flower ratio (0.4423). Furthermore, PC3 and PC4 with percentage variation ranging from 12.60 to 15.10 showed high loading for fruit weight. The cumulative variance of 70.0% by the first three axes with eigen-vector values > 1.0 indicated that the identified characters within them exhibited great influence on the cucumber varieties, hence, could effectively be employed for selection in cucumber studies. The findings corroborate results reported by Cui et al. (1995) in their investigation on traits selection in cucumber breeding expressing the efficacy of principal component analysis in enhancing cucumber improvement strategies and Staub et al. (1997) on their studies on problems associated with the selection of determinant cucumber plant types in a multiple lateral background as well as Shetty and Wehner (2002b) in their studies on fruit yield of cucumber. Table 3. Effect of seasons and NPK rates on the yield and yield components of three cucumber varieties Attributes Treatment Yield (t/ha) Fruit weight (g) No. of Fruit Fruit Length (cm) Fruit girth (cm) Male Male-female flower flower ratio Female flower Season Early 2.00 180.1 11.98 16.77 14.71 123.1 0.145 17.1 Late 0.94 152.0 10.50 13.57 10.40 225.3 0.104 35.0 LSD0.05 0.08 48.77 - - 3.13 39.71 - - Sig. ** ** ns ns * * ns ns Varieties Ashley 1.70 162.7 11.33 14.69 12.83 176.8 0.162 27.8 Betalpha 1.11 144.5 11.11 15.48 12.25 177.5 0.147 23.2 Marketmore 1.60 191.0 11.28 15.33 12.58 168.3 0.154 26.0 LSD0.05 - - - - - - 0.035 - Sig. ns ns ns ns ns ns * ns NPK rates 0 0.92 129.0 9.89 14.45 12.24 161.6 0.157 16.3 60 1.23 153.6 10.44 13.15 10.89 190.1 0.159 28.5 120 1.96 196.2 10.11 15.12 11.89 181.7 0.175 34.0 180 1.61 169.1 10.78 15.37 14.26 162.1 0.146 22.1 240 1.70 191.9 11.83 16.44 12.49 185.1 0.141 23.3 300 1.40 157.5 14.39 16.46 10.89 164.6 0.149 23.7 LSD0.05 - - 2.808 - - - - - Sig ns ns * ns ns ns ns ns 34 Nwofia G. E. et al.: Response of Three Cucumber Varieties (Cucumis sativus L.) to Planting Season and NPK Fertilizer Rates in Lowland Humid Tropics: Sex Expression, Yield and Inter-Relationships between Yield and Associated Traits Table 4. Influence of planting season and variety on fruit weight of three cucumbers (g/plant) Season Ashley Early 201.3 Late 124.1 Mean 162.2 LSD0.05 = season x variety = 48.77 Betalpha 176.1 112.9 144.5 Attributes Marketmore 163.0 219.0 191.0 Mean 180.13 152.0 Table 5. Influence of planting season, variety and NPK rates on fruit number per plot Season Variety 0 Early 11.98 Ashley 7.67 Betalpha 8.00 Marketmore 12.00 9.22 Late 10.50 Ashley 11.33 Betalpha 9.33 Marketmore 11.33 LSD0.05: season x variety x NPK rates = 9.667 Season x NPK rates = 4.784 60 13.33 10.00 9.67 11.00 8.33 10.33 11.33 120 12.60 13.33 11.67 12.53 10.00 5.00 8.67 180 11.33 13.67 10.67 11.89 13.00 4.67 11.33 240 18.00 11.69 15.69 15.13 4.67 12.67 8.33 300 13.33 12.00 11.67 12.33 13.00 22.67 13.67 Mean 12.61 11.45 11.89 10.60 10.74 10.67 Table 6. Eigen vector values of the principal components of the yield and associated traits Attributes Female flowers Male-female flower rates Male flowers Fruit girth Fruit length Fruit number Fruit weight Eigen vector value Percentage variation contribution Cumulative variance contribution PC1 0.5267 0.3620 0.3707 -0.4349 -0.4398 0.0902 0.2519 2.36985 33.90 33.90 PC2 0.4042 0.5405 -0.1061 0.4293 0.4368 0.3849 0.0997 1.47410 21.10 54.90 PC3 0.0380 0.4423 0.6592 0.0660 0.0911 0.5029 0.3208 1.05439 15.10 70.00 PC4 -0.0541 -0.1995 0.1774 0.2622 0.1953 0.1040 0.8885 0.88422 12.60 82.60 Table 7. Pearson correlation coefficients of yield and yield components of three cucumber varieties grown under different planting seasons fand NPK fertilizer rates Male flower Male flower 1.00 Female flower No. of Fruits / plant Fruit Fruit length Fruit girth Male–female Yield weight (g) (cm) (cm) flower ratio (kg/ha) Female flower 0.573** 1.00 Fruit ns 0.102ns 0.167ns 1.00 Fruit weight (g) 10.113ns -0.173ns 0.021ns 1.00 Fruit length (cm) -0.270** -0.235* 0.061ns 0.213* 1.00 Fruit girth (cm) -0.269** -0.233* 0.050ns 0.171ns 0.670** 1.00 Male–female flower ratio -0.096ns 0.742** 0.139ns -0.131ns -0.109ns -0.110ns 1.00 Yield (kg/ha) -0.137ns -0.036ns 0.471** 0.574** 0.178ns 0.181ns 0.052ns 1.00 *, ** = significant at 5%, and 1% level, respectively, ns = non significant International Journal of Agriculture and Forestry 2015, 5(1): 30-37 35 Table 8. Cause and effect analysis showing direct and indirect effects of yield components on fresh fruit yield of three varieties of cucumber Attributes Direct effect No. of fruits/ plant Fruit weight (g) Fruit length (cm) Fruit girth (cm) Residual effect 0.457 0.565 -0.019 0.076 No. of fruits/ plant 0.010 0.028 0.023 Fruit weight (g) 0.0121 - 0.118 0.095 Indirect effect Fruit length (cm) Fruit girth (cm) -0.001 0.004 -0.004 0.013 - 0.051 -0.013 - Pearson correlation with fruit yield 0.471** 0.013** 0.178ns 0.818ns 0.456 **, ns = significant at 1% level and non significant, respectively. Pearson correlation analysis among cucumber fruit yield and its contributing attributes (Table 5) showed that correlation of fresh fruit yield per hectare was found to be highly significant (P≤0.01) and positive for number of fruits per plant and weight of fruits per plant with correlation coefficients (r) of 0.471 and 0.574, respectively. The findings are in line with that of Ogbodo et al (2010) in their multi-locational trial on cucumber in the derived savanna agro-ecological zone as well as Afangideh et al. (2005) in the forest agro-ecological zone of Southeastern Nigeria. Highly significant (P≤0.01) and positive correlation was obtained between male-female flower ratio and number of female flowers per plant (0.742) and between fruit girth and fruit length (0.670). However, number of male flowers per plant showed negative and significant correlation with number of female flowers per plant (-0.233). Fruit length was significantly and positively correlated with fruit weight with (r = 0.213) but showed significant and negative correlation with number of male flowers per plant and number of female flowers per plant with (r = -0.270 and -0.235), respectively. The relationship between number of female flowers and number of male flowers was highly significant (P≤0.01) and positive (r = 0.513). Number of fruits per plant and fruit weight showed significant and positive correlation with total fruit yield. The findings are in consonance with results of Golabadi et al. (2013) in their studies on determining relationships between different horticultural traits in Cucumis sativus genotypes. Cause and effect analysis means partitioning of Pearson correlation coefficients into direct and indirect effects (Table 7) and the maximum direct effect on fruit yield of cucumber was shown by fruit weight (0.565) followed by number of fruits per plant (0.457) and fruit girth (0.076). Fruit weight also exerted positive indirect effect via number of fruits per plant and fruit girth while number of fruits per plant exerted positive indirect effect only through fruit weight. The results from the study corroborates similar reports by Roa et al. (2004) and Arunkumar et al. (2011b) in India as well as Golabadi et al. (2013) in Iran in their separate investigations in which they indicated that number of cucumber fruits per plant projected the greatest positive effect on total fruit yield of cucumber, an indication that the trait is one of the most reliable component for selecting high fruit yielding cucumber genotypes. However, Cramer and Wehner (2000) in their studies on eight distinctive cucumber populations reported strong positive interaction between number of branches per cucumber plant and total number of fruits per plant and stressed the importance of number of branches per plant in selection for improved total fruit yield. Indirect and positive effect of fruit girth was achieved via number of fruits per plant and fruit weight. Fruit weight and number of fruits per plant had high direct effect along with genotypic correlation. The contribution of other characters, viz.; fruit girth and fruit length was negligible. A low residual effect (0.456) was obtained from the analysis. 4. Conclusions Our findings indicated significant increase in fruit yield of cucumber planted during the early rainfall season in the humid tropics. Market-more cucumber variety gave better fruit yield at 120 kg/ha N:P:K fertilizer rate compared to the rates used in the trial. Principal component analysis, correlations and path coefficients analysis revealed that plant characters such as number of female flowers per plant, male-female flower ratio, fruit weight per plant and number of fruits per plant significantly influenced fruit yield of cucumber in both seasons, hence, in breeding and selection for high yield, these characters demand prime attention. REFERENCES [1] Abdi, H. and Williams, L.J. (2010). Principle Component Analysis. Wiley Interdisciplinary, Reviews Computational Statistics. 2: 433-459. [2] Adekiya, A.O. and Ojeniyi, S.O. 2002. 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