Effect of Hormones (IBA &amp; IAA) on the Propagation of Himalayan Yew in Pakistan: A Conservation Approach

doi:10.21203/rs.3.rs-27841/v1

Background

Himalayan yew (Taxus wallichiana) is one of the endangered medicinal plants species having great importance due to the presence of anticancer drug Taxol. This metabolite is mainly used for the treatment of ovarian, breast, AIDS-related cancers, and other indications. The study being reported here was conducted for the propagation of Himalayan yew by using two different trials of Indole Butyric acid (IBA) and Indole acetic acid (IAA) hormones treatments (2000–7000 ppm) through stem cuttings (140 each). In the same way, 3840 cuttings were treated with IBA and IAA from November 2016 to November 2017 at Lalku valley, Swat, Khyber Pakhtunkhwa (KP), Pakistan.

Results

The influence of IBA treatment (7000 ppm) showed a survival of 85.22% (average number of roots = 10.4, average length of roots = 15.5 cm, average number of leaves = 92.4 and average number of sprouts = 3.3) while that of IAA treatment (7000 ppm) the survival of 81.11% (average number of roots = 9.1, average length of roots = 14.6 cm, average number of leaves = 84.0 and average number of sprout = 3.0) were more significant followed by 2000–6000 ppm (IBA and IAA). Lowest survival 40–45% (average number of roots = 4.2, average length of roots = 8.0 cm, average number of leaves = 32.2, average number of sprouts = 1.7) was noticed for controlled cuttings.

Conclusion

The present study enhanced the potential of conservation and propagation of T. wallichiana. Hence our study suggests and recommends the application of IBA (7000 ppm) as a better hormone for the conservation and propagation of Himalayan yew.

Plant Physiology and Morphology

Plant Molecular Biology and Genetics

Hormone

propagation

endangered

Taxus wallichiana

survival

conservation

T. wallichianais one of the threatened medicinal plants of Himalayan Region (1) commonly known as Himalayan yew and belongs to family Taxaceae (2).Other names given to the species are Banrya in Pushto, Barmi in Hindi and Urdu, Common yew and Himalayan yew in English (3). It is a coniferous, evergreen and a slow-growing tree having needle-like leaves and bright red fruit (Fig. 1) (4) with lengthy seed dormancy period of about 1.5 to 2.0 years and shows growth rate (increase in its circumference) of 0.4 to 1.3 cm per year (5, 6). The species survive for an average life of approximately 600 years (7). It is found in Pakistan, Afghanistan, Bhutan, Indonesia, Nepal, China, Malaysia, Philippines Vietnam, Myanmar, and India (8, 3). In Pakistan, it is present in moist temperate forests of Murree, Galliat, Kaghan, Kurram, Chitral, Kashmir, Swat and Hazara (9). Unlike other common coniferous species, the population of Taxus occurs in patches not continuous. Its habitat ismainly characterized by moist, mixed coniferous tree forests or cool broad-leaved forests. Due to shade demanding nature, Taxus is usually found in association with large tree species such as Abiespindrow, Betula utilizes Pinus wallichiana, Acer cesium, Rhododendron arboreuand, Quercus semecarpifolia (10).

Taxus is very important to treat cancer and many other diseases like bronchitis, snake bites, epilepsy, asthma, aphrodisiac, internal injuries, scorpion, diabetes, and for the diseases of lungs (10, 11).

In Pakistan, lack of awareness, slow growth rate, agriculture, construction, habitat loss, forest fires, transformation, grazing, over-harvesting, decoration purposes, medicinal use, accidental mortality, lack of management policies, illicit cutting etc. are major threats to the species (10, 12, 13). Approximately 10 genera of Taxus are now declining at the Northern Hemisphere in temperate zones (14). During 2001–2005, Technology, Information, Forecasting and Assessment Council (TIFAC) has reported 45 threatened medicinal plants with specific recommendation for 7 plants including Taxus enlisted in Convention for International Trade in Endangered Species (CITES) (Appendix II) in 1995 (15, 16, 17, 18, 19, 20, 21). Recently the existence of Yew is receiving high conservation attention due to the high exploitation rate which has reduced its population by 87% (22, 23, 24, 25). Poor regeneration process, slow growth rate and lengthy seed dormancy period of the species (26) significantly contribute to hurdles in its conservation. Vegetative propagation, therefore, could be one of the practical options to enhance its natural regeneration. The Taxus species has high regeneration potential by adventitious rooting of fresh stem cuttings (27). Unlike other Taxus species, T. wallichiana is difficult to root and requires longer time (28). Rooting of Taxus stem cuttings is well documented (29, 30). The present experiment was aimed to enhance the potential of conservation and propagation of T. wallichiana using the stem cuttings of mature trees with the application of various doses of IBA and IAA.

Test for normality

Results of Kolmogorov-Smirnov and Shapiro-Wilktests are not significant therefore the data fulfill the normally assumption (Table 2)

Table 1

Experimental Design of Hormones applications.
Trials	No. of Rows	No. of Cuttings in each Row	Total Cuttings	Length of each cutting (inches)	Nos of Replications
1st _IBA	7	20	140	7–8	3
2nd _IAA	7	20	140	7–8	3

Table 2

Tests of Normality
Parameters	Kolmogorov-Smirnov^a			Shapiro-Wilk
Parameters	Statistic	df	Sig.	Statistic	df	Sig.
IAA Number of Roots	.089	140	.008	.971	140	.004
IAA Root Length(cm)	.109	140	.000	.896	140	.000
IAA Number of Leaves	.150	140	.000	.933	140	.000
IAA Number of Sprouts	.209	140	.000	.898	140	.000
a. Lilliefors Significance Correction

The Q-Q plots was used to test the assumptions of normality for all the expected and observed values for the four parameters (number of roots, length of root, number of leaves, and number of sprouts). All the values were plotted on the Q-Q plots on a graph which shows that the data is normal (Fig. 4–7).

Multicollinearity

Table 3 shows that Correlation is significant at the 0.01 level (2-tailed). Correlations were done between the growth parameters (number of roots, root length (cm), number of leaves, and number of sprouts). There is strong to moderate correlation was found among number of roots-root length (0.736), number of roots-number of leaves (0.800), number of roots-number of sprouts (0.519). Significant correlation was also found among root length-number of leaves (0.718), root length-number of sprouts (0.421). Similarly, there is significant correlation among number of leaves-number of sprouts (0.541). Hence data contain no multicollinearity.

Table 3

Pearson Correlations for the Parameters i.e. number of roots, length of roots, number of leaves, and number of sprouts of *T. wallichiana* stems cuttings.
Parameters		Number of Roots	Root Length(cm)	Number of Leaves	Number of Sprouts
Number of Roots	Pearson Correlation	1	.736^**	.800^**	.519^**
	Sig. (2-tailed)		.000	.000	.000
	N	140	140	140	140
Root Length (cm)	Pearson Correlation	.736^**	1	.718^**	.421^**
	Sig. (2-tailed)	.000		.000	.000
	N	140	140	140	140
Number of Leaves	Pearson Correlation	.800^**	.718^**	1	.541^**
	Sig. (2-tailed)	.000	.000		.000
	N	140	140	140	140
Number of Sprouts	Pearson Correlation	.519^**	.421^**	.541^**	1
	Sig. (2-tailed)	.000	.000	.000
	N	140	140	140	140
**. Correlation is significant at the 0.01 level (2-tailed).

Since the data fulfil all the assumption to apply MONOVA technique for further analysis.

Since the p value is < 0.05 (Table 4) which means different treatment at different level are significant to each other. Now to check the performance of different combination, which one performs better than the other, for that post hoc test was applied.

Table 4

Multivariate Analysis of Variance
Multivariate Tests^a
Effect		Value	F	Hypothesis df	Error df	Sig.
Intercept	Pillai's Trace	.988	2574.650^b	4.000	123.000	.000
	Wilks' Lambda	.012	2574.650^b	4.000	123.000	.000
	Hotelling's Trace	83.728	2574.650^b	4.000	123.000	.000
	Roy's Largest Root	83.728	2574.650^b	4.000	123.000	.000
Harmons	Pillai's Trace	.126	4.448^b	4.000	123.000	.002
	Wilks' Lambda	.874	4.448^b	4.000	123.000	.002
	Hotelling's Trace	.145	4.448^b	4.000	123.000	.002
	Roy's Largest Root	.145	4.448^b	4.000	123.000	.002
Concentration	Pillai's Trace	1.082	7.785	24.000	504.000	.000
	Wilks' Lambda	.109	15.905	24.000	430.306	.000
	Hotelling's Trace	6.468	32.742	24.000	486.000	.000
	Roy's Largest Root	6.204	130.275^c	6.000	126.000	.000
Harmons * Concentration	Pillai's Trace	.025	.130	24.000	504.000	1.000
	Wilks' Lambda	.976	.128	24.000	430.306	1.000
	Hotelling's Trace	.025	.126	24.000	486.000	1.000
	Roy's Largest Root	.017	.353^c	6.000	126.000	.907
a. Design: Intercept + Harmons + Concentration + Harmons * Concentration
b. Exact statistic
c. The statistic is an upper bound on F that yields a lower bound on the significance level.

For concentration levels (2000 PPM-7000 PPM), Post Hoc test was applied. As by having the same numbers of replications/concentrations of hormones/number of plant cuttings Tukey Test (HSD) (Table 5) and correlation analysis (Table 4) have been done.

Table 5

Post Hoc Tests (Tukey HSD) applied showed the concentration 7000 ppm is more significant for similar number of cases in each treatment
Multiple Comparisons
Tukey HSD
Dependent Variable	(I) Quantity (PPM)	(J) Quantity (PPM)	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
Dependent Variable	(I) Quantity (PPM)	(J) Quantity (PPM)	Mean Difference (I-J)	Std. Error	Sig.	Lower Bound	Upper Bound
Number of Roots	Control	2000	-1.7000^*	.44042	.003	-3.0197	− .3803
		3000	-2.3000^*	.44042	.000	-3.6197	− .9803
		4000	-3.0500^*	.44042	.000	-4.3697	-1.7303
		5000	-3.7000^*	.44042	.000	-5.0197	-2.3803
		6000	-4.8000^*	.44042	.000	-6.1197	-3.4803
		7000	-6.5000^*	.44042	.000	-7.8197	-5.1803
	2000	Control	1.7000^*	.44042	.003	.3803	3.0197
		3000	− .6000	.44042	.821	-1.9197	.7197
		4000	-1.3500^*	.44042	.041	-2.6697	− .0303
		5000	-2.0000^*	.44042	.000	-3.3197	− .6803
		6000	-3.1000^*	.44042	.000	-4.4197	-1.7803
		7000	-4.8000^*	.44042	.000	-6.1197	-3.4803
	3000	Control	2.3000^*	.44042	.000	.9803	3.6197
		2000	.6000	.44042	.821	− .7197	1.9197
		4000	− .7500	.44042	.615	-2.0697	.5697
		5000	-1.4000^*	.44042	.030	-2.7197	− .0803
		6000	-2.5000^*	.44042	.000	-3.8197	-1.1803
		7000	-4.2000^*	.44042	.000	-5.5197	-2.8803
	4000	Control	3.0500^*	.44042	.000	1.7303	4.3697
		2000	1.3500^*	.44042	.041	.0303	2.6697
		3000	.7500	.44042	.615	− .5697	2.0697
		5000	− .6500	.44042	.759	-1.9697	.6697
		6000	-1.7500^*	.44042	.002	-3.0697	− .4303
		7000	-3.4500^*	.44042	.000	-4.7697	-2.1303
	5000	Control	3.7000^*	.44042	.000	2.3803	5.0197
		2000	2.0000^*	.44042	.000	.6803	3.3197
		3000	1.4000^*	.44042	.030	.0803	2.7197
		4000	.6500	.44042	.759	− .6697	1.9697
		6000	-1.1000	.44042	.169	-2.4197	.2197
		7000	-2.8000^*	.44042	.000	-4.1197	-1.4803
	6000	Control	4.8000^*	.44042	.000	3.4803	6.1197
		2000	3.1000^*	.44042	.000	1.7803	4.4197
		3000	2.5000^*	.44042	.000	1.1803	3.8197
		4000	1.7500^*	.44042	.002	.4303	3.0697
		5000	1.1000	.44042	.169	− .2197	2.4197
		7000	-1.7000^*	.44042	.003	-3.0197	− .3803
	7000	Control	6.5000^*	.44042	.000	5.1803	7.8197
		2000	4.8000^*	.44042	.000	3.4803	6.1197
		3000	4.2000^*	.44042	.000	2.8803	5.5197
		4000	3.4500^*	.44042	.000	2.1303	4.7697
		5000	2.8000^*	.44042	.000	1.4803	4.1197
		6000	1.7000^*	.44042	.003	.3803	3.0197
Root Length (cm)	Control	2000	-2.0550^*	.56146	.007	-3.7374	− .3726
		3000	-2.4700^*	.56146	.000	-4.1524	− .7876
		4000	-2.7450^*	.56146	.000	-4.4274	-1.0626
		5000	-2.9850^*	.56146	.000	-4.6674	-1.3026
		6000	-4.1550^*	.56146	.000	-5.8374	-2.4726
		7000	-4.5300^*	.56146	.000	-6.2124	-2.8476
	2000	Control	2.0550^*	.56146	.007	.3726	3.7374
		3000	− .4150	.56146	.990	-2.0974	1.2674
		4000	− .6900	.56146	.882	-2.3724	.9924
		5000	− .9300	.56146	.646	-2.6124	.7524
		6000	-2.1000^*	.56146	.005	-3.7824	− .4176
		7000	-2.4750^*	.56146	.000	-4.1574	− .7926
	3000	Control	2.4700^*	.56146	.000	.7876	4.1524
		2000	.4150	.56146	.990	-1.2674	2.0974
		4000	− .2750	.56146	.999	-1.9574	1.4074
		5000	− .5150	.56146	.969	-2.1974	1.1674
		6000	-1.6850^*	.56146	.049	-3.3674	− .0026
		7000	-2.0600^*	.56146	.006	-3.7424	− .3776
	4000	Control	2.7450^*	.56146	.000	1.0626	4.4274
		2000	.6900	.56146	.882	− .9924	2.3724
		3000	.2750	.56146	.999	-1.4074	1.9574
		5000	− .2400	.56146	1.000	-1.9224	1.4424
		6000	-1.4100	.56146	.164	-3.0924	.2724
		7000	-1.7850^*	.56146	.030	-3.4674	− .1026
	5000	Control	2.9850^*	.56146	.000	1.3026	4.6674
		2000	.9300	.56146	.646	− .7524	2.6124
		3000	.5150	.56146	.969	-1.1674	2.1974
		4000	.2400	.56146	1.000	-1.4424	1.9224
		6000	-1.1700	.56146	.369	-2.8524	.5124
		7000	-1.5450	.56146	.094	-3.2274	.1374
	6000	Control	4.1550^*	.56146	.000	2.4726	5.8374
		2000	2.1000^*	.56146	.005	.4176	3.7824
		3000	1.6850^*	.56146	.049	.0026	3.3674
		4000	1.4100	.56146	.164	− .2724	3.0924
		5000	1.1700	.56146	.369	− .5124	2.8524
		7000	− .3750	.56146	.994	-2.0574	1.3074
	7000	Control	4.5300^*	.56146	.000	2.8476	6.2124
		2000	2.4750^*	.56146	.000	.7926	4.1574
		3000	2.0600^*	.56146	.006	.3776	3.7424
		4000	1.7850^*	.56146	.030	.1026	3.4674
		5000	1.5450	.56146	.094	− .1374	3.2274
		6000	.3750	.56146	.994	-1.3074	2.0574
Number of Leaves	Control	2000	-30.5500^*	2.49479	.000	-38.0257	-23.0743
		3000	-32.3000^*	2.49479	.000	-39.7757	-24.8243
		4000	-33.8000^*	2.49479	.000	-41.2757	-26.3243
		5000	-39.6000^*	2.49479	.000	-47.0757	-32.1243
		6000	-47.8000^*	2.49479	.000	-55.2757	-40.3243
		7000	-59.2500^*	2.49479	.000	-66.7257	-51.7743
	2000	Control	30.5500^*	2.49479	.000	23.0743	38.0257
		3000	-1.7500	2.49479	.992	-9.2257	5.7257
		4000	-3.2500	2.49479	.850	-10.7257	4.2257
		5000	-9.0500^*	2.49479	.007	-16.5257	-1.5743
		6000	-17.2500^*	2.49479	.000	-24.7257	-9.7743
		7000	-28.7000^*	2.49479	.000	-36.1757	-21.2243
	3000	Control	32.3000^*	2.49479	.000	24.8243	39.7757
		2000	1.7500	2.49479	.992	-5.7257	9.2257
		4000	-1.5000	2.49479	.997	-8.9757	5.9757
		5000	-7.3000	2.49479	.060	-14.7757	.1757
		6000	-15.5000^*	2.49479	.000	-22.9757	-8.0243
		7000	-26.9500^*	2.49479	.000	-34.4257	-19.4743
	4000	Control	33.8000^*	2.49479	.000	26.3243	41.2757
		2000	3.2500	2.49479	.850	-4.2257	10.7257
		3000	1.5000	2.49479	.997	-5.9757	8.9757
		5000	-5.8000	2.49479	.241	-13.2757	1.6757
		6000	-14.0000^*	2.49479	.000	-21.4757	-6.5243
		7000	-25.4500^*	2.49479	.000	-32.9257	-17.9743
	5000	Control	39.6000^*	2.49479	.000	32.1243	47.0757
		2000	9.0500^*	2.49479	.007	1.5743	16.5257
		3000	7.3000	2.49479	.060	− .1757	14.7757
		4000	5.8000	2.49479	.241	-1.6757	13.2757
		6000	-8.2000^*	2.49479	.022	-15.6757	− .7243
		7000	-19.6500^*	2.49479	.000	-27.1257	-12.1743
	6000	Control	47.8000^*	2.49479	.000	40.3243	55.2757
		2000	17.2500^*	2.49479	.000	9.7743	24.7257
		3000	15.5000^*	2.49479	.000	8.0243	22.9757
		4000	14.0000^*	2.49479	.000	6.5243	21.4757
		5000	8.2000^*	2.49479	.022	.7243	15.6757
		7000	-11.4500^*	2.49479	.000	-18.9257	-3.9743
	7000	Control	59.2500^*	2.49479	.000	51.7743	66.7257
		2000	28.7000^*	2.49479	.000	21.2243	36.1757
		3000	26.9500^*	2.49479	.000	19.4743	34.4257
		4000	25.4500^*	2.49479	.000	17.9743	32.9257
		5000	19.6500^*	2.49479	.000	12.1743	27.1257
		6000	11.4500^*	2.49479	.000	3.9743	18.9257
Number of Sprouts	Control	2000	− .3500	.25820	.824	-1.1237	.4237
		3000	− .5500	.25820	.342	-1.3237	.2237
		4000	− .8500^*	.25820	.021	-1.6237	− .0763
		5000	-1.1000^*	.25820	.001	-1.8737	− .3263
		6000	-1.4000^*	.25820	.000	-2.1737	− .6263
		7000	-1.5500^*	.25820	.000	-2.3237	− .7763
	2000	Control	.3500	.25820	.824	− .4237	1.1237
		3000	− .2000	.25820	.987	− .9737	.5737
		4000	− .5000	.25820	.460	-1.2737	.2737
		5000	− .7500	.25820	.064	-1.5237	.0237
		6000	-1.0500^*	.25820	.002	-1.8237	− .2763
		7000	-1.2000^*	.25820	.000	-1.9737	− .4263
	3000	Control	.5500	.25820	.342	− .2237	1.3237
		2000	.2000	.25820	.987	− .5737	.9737
		4000	− .3000	.25820	.907	-1.0737	.4737
		5000	− .5500	.25820	.342	-1.3237	.2237
		6000	− .8500^*	.25820	.021	-1.6237	− .0763
		7000	-1.0000^*	.25820	.003	-1.7737	− .2263
	4000	Control	.8500^*	.25820	.021	.0763	1.6237
		2000	.5000	.25820	.460	− .2737	1.2737
		3000	.3000	.25820	.907	− .4737	1.0737
		5000	− .2500	.25820	.960	-1.0237	.5237
		6000	− .5500	.25820	.342	-1.3237	.2237
		7000	− .7000	.25820	.104	-1.4737	.0737
	5000	Control	1.1000^*	.25820	.001	.3263	1.8737
		2000	.7500	.25820	.064	− .0237	1.5237
		3000	.5500	.25820	.342	− .2237	1.3237
		4000	.2500	.25820	.960	− .5237	1.0237
		6000	− .3000	.25820	.907	-1.0737	.4737
		7000	− .4500	.25820	.589	-1.2237	.3237
	6000	Control	1.4000^*	.25820	.000	.6263	2.1737
		2000	1.0500^*	.25820	.002	.2763	1.8237
		3000	.8500^*	.25820	.021	.0763	1.6237
		4000	.5500	.25820	.342	− .2237	1.3237
		5000	.3000	.25820	.907	− .4737	1.0737
		7000	− .1500	.25820	.997	− .9237	.6237
	7000	Control	1.5500^*	.25820	.000	.7763	2.3237
		2000	1.2000^*	.25820	.000	.4263	1.9737
		3000	1.0000^*	.25820	.003	.2263	1.7737
		4000	.7000	.25820	.104	− .0737	1.4737
		5000	.4500	.25820	.589	− .3237	1.2237
		6000	.1500	.25820	.997	− .6237	.9237
Based on observed means. The error term is Mean Square (Error) = .667.
*. The mean difference is significant at the .05 level.

Since two different hormones IAA and IBA are being used, therefore we interpret the differences by simply looking at their mean values. The results revealed that in both trials for the regeneration of Himalayan yew (T. wallichiana) cuttings, by the treatment of hormones (IBA and IAA) with 2000–7000 ppm were applied. Out of all the applied concentrations of hormone (2000–7000 ppm), 7000 ppm shows maximum marginal means for number of roots (10.4, 9.1), roots length (11.82 cm, 10.27 cm), and number of leaves (92.40, 88.30), sprout numbers (3.30, 3.0) and survival percentage (85.22%, 81.11%) throughout the experiment. The next best dozes were 6000 ppm followed by 5000 ppm, 4000 ppm, 3000 ppm, and 2000 ppm. The lowest growth was noticed in control cuttings (Table 6) (Fig. 8 to 12).

Table 6

General Linear Model (Descriptive Statistics), showing the estimated marginal means of the Parameter (number of roots, roots length (cm), number of leaves, and number of sprouts) of *T. wallichiana* cuttings by the application of various concentration of hormones (2000 PPM- 7000 PPM) of IBA, and IAA.
Parameters	Treatment	Quantity in PPM	Mean ± SD	N
Number of Roots	IAA	Control	2.8000 ± 1.54919	10
		2000PPM	4.8000 ± 1.03280	10
		3000PPM	5.2000 ± 1.39841	10
		4000PPM	5.9000 ± 1.19722	10
		5000PPM	6.6000 ± 1.17379	10
		6000PPM	7.6000 ± 1.07497	10
		7000PPM	9.1000 ± 1.19722	10
		Total	6.0000 ± 2.23931	70
	IBA	Control	3.7000 ± 1.63639	10
		2000PPM	5.1000 ± 1.19722	10
		3000PPM	5.9000 ± 1.19722	10
		4000PPM	6.7000 ± 1.56702	10
		5000PPM	7.3000 ± 1.33749	10
		6000PPM	8.5000 ± 1.26930	10
		7000PPM	10.4000 ± 2.22111	10
		Total	6.8000 ± 2.52868	70
	Total	Control	3.2500 ± 1.61815	20
		2000PPM	4.9500 ± 1.09904	20
		3000PPM	5.5500 ± 1.31689	20
		4000PPM	6.3000 ± 1.41793	20
		5000PPM	6.9500 ± 1.27630	20
		6000PPM	8.0500 ± 1.23438	20
		7000PPM	9.7500 ± 1.86025	20
		Total	6.4000 ± 2.41339	140
Root Length (cm)	IAA	Control	5.8600 ± 3.25958	10
		2000PPM	8.2000 ± 1.04243	10
		3000PPM	8.6400 ± 1.24383	10
		4000PPM	8.8800 ± 1.40063	10
		5000PPM	9.1300 ± 0.97985	10
		6000PPM	10.1100 ± 1.19019	10
		7000PPM	10.2700 ± 1.51441	10
		Total	8.7271 ± 2.11571	70
	IBA	Control	7.1700 ± 3.01517	10
		2000PPM	8.9400 ± 1.73666	10
		3000PPM	9.3300 ± 1.49596	10
		4000PPM	9.6400 ± 1.55863	10
		5000PPM	9.8700 ± 1.76638	10
		6000PPM	11.2300 ± 1.71856	10
		7000PPM	11.8200 ± 1.18115	10
		Total	9.7143 ± 2.27783	70
	Total	Control	6.5150 ± 3.12903	20
		2000PPM	8.5700 ± 1.44481	20
		3000PPM	8.9850 ± 1.38499	20
		4000PPM	9.2600 ± 1.49399	20
		5000PPM	9.5000 ± 1.44113	20
		6000PPM	10.6700 ± 1.54923	20
		7000PPM	11.0450 ± 1.54255	20
		Total	9.2207 ± 2.24565	140
Number of Leaves	IAA	Control	30.1000 ± 16.25799	10
		2000PPM	60.8000 ± 5.11642	10
		3000PPM	62.1000 ± 7.48999	10
		4000PPM	64.0000 ± 6.97615	10
		5000PPM	69.7000 ± 4.71522	10
		6000PPM	77.7000 ± 6.91295	10
		7000PPM	88.3000 ± 5.01221	10
		Total	64.6714 ± 18.69645	70
	IBA	Control	32.1000 ± 11.87387	10
		2000PPM	62.5000 ± 6.32895	10
		3000PPM	64.7000 ± 7.45431	10
		4000PPM	65.8000 ± 7.19259	10
		5000PPM	71.7000 ± 3.83116	10
		6000PPM	80.1000 ± 6.08185	10
		7000PPM	92.4000 ± 6.39792	10
		Total	67.0429 ± 18.75350	70
	Total	Control	31.1000 ± 13.89396	20
		2000PPM	61.6500 ± 5.66870	20
		3000PPM	63.4000 ± 7.39417	20
		4000PPM	64.9000 ± 6.95777	20
		5000PPM	70.7000 ± 4.30544	20
		6000PPM	78.9000 ± 6.45552	20
		7000PPM	90.3500 ± 5.97605	20
		Total	65.8571 ± 18.69543	140
Number of Sprouts	IAA	Control	1.5000 ± 1.08012	10
		2000PPM	1.7000 ± 0.67495	10
		3000PPM	1.9000 ± 0.56765	10
		4000PPM	2.3000 ± 0.94868	10
		5000PPM	2.6000 ± 0.96609	10
		6000PPM	2.9000 ± .73786	10
		7000PPM	3.0000 ± .66667	10
		Total	2.2714 ± .96190	70
	IBA	Control	1.7000 ± .94868	10
		2000PPM	2.2000 ± .63246	10
		3000PPM	2.4000 ± .51640	10
		4000PPM	2.6000 ± .96609	10
		5000PPM	2.8000 ± 1.03280	10
		6000PPM	3.1000 ± .87560	10
		7000PPM	3.3000 ± .48305	10
		Total	2.5857 ± .92459	70
	Total	Control	1.6000 ± .99472	20
		2000PPM	1.9500 ± .68633	20
		3000PPM	2.1500 ± .58714	20
		4000PPM	2.4500 ± .94451	20
		5000PPM	2.7000 ± .97872	20
		6000PPM	3.0000 ± .79472	20
		7000PPM	3.1500 ± .58714	20
		Total	2.4286 ± .95317	140

The results depict that the cutting responded differently to various levels of concentration of hormones (2000 ppm-7000 ppm) and the modes of application. Table 4.5 shows the multiple comparisons of all the parameters (number of roots, length of roots cm, number of leaves, number of sprouts) marginal mean values by the applied various concentrations of hormones (2000 ppm-7000 ppm) to the cuttings of T. wallichiana for the significant. Therefore, Post Hoc test (Tukey HSD) has been applied to check the significance on different levels among the growth parameters (number of roots, length of roots cm, number of leaves, number of sprouts) by applied hormones various concentrations (2000 ppm–7000 ppm). The multiple comparison (Tukey HSD) shows that based on observed means the error term is Mean Square (Error) = 0.667 and (*) the mean difference is significant at the 0.05 level (p < 0.05) (Table 5).

The current study indicates that hormone treatment (IBA & IAA) is the favourable and best option for the conservation and vegetative propagation of Himalayan yew. As our study depicts and recommends IBA the best rooting hormones in comparison to the Indole acitic acid ( IAA). In fact, the auxins application is important to produce roots in fresh stem cuttings as they have been experienced for stimulating secondary plant growth that results in the reserve food material mobilization to the root initiation site (31). Auxins application increases rooting and quality of roots in various tree species (32). It is a well-documented that the auxins application is important for the roots formation in the cuttings of plant stem as they have been found in stimulating the cambial activity which results in reserve food mobilization to the root initiation site (31; 33).

Also, a successful rooting in juvenile shoot cuttings of T. wallichiana with different auxins has been documented from the other temperate areas as well (34, 35, 36, 38, 39)

Our results are also similar with Nautiyal et al. (1991) (40), who treated hormones on stem cutting of teak for roots induction and concluded that IBA is the favourable and best auxins. Other scientists (41, 44, 37, 42, 45, 46, 43) also documented that the IBA application play a vital role in the propagation of stem cuttings of Taxus. Their results clearly mentioned that vegetative propagation (in-situ conservation) can improve the number of juvenile’s plants of genus Taxus.

Several primary root formations under the influence of IBA application have been obtained in the present trials (7000 ppm). It must be accepted that a higher root to shoot is satisfactory for achieving a higher survival rate after transplantation of field. It has also been reported that more than optimums concentration of auxins is toxic to the root regeneration, while theoptimum concentration of hormones is favorable (47, 48). In our study we had applied the maximum concentration of 7000 ppm of both the auxins (IBA and IAA) which shows favourable response to the growth of T. wallichiana cuttings.

The differential response to changing concentrations of hormones for survivals of T. wallichiana were noted in the present study could be like the action of increasing Auxins (2000 ppm – 7000 ppm). The IBA application may have an indirect effect by increasing the translocation speed and the movement of sugar to the cuttings base which in result stimulate rooting (31).

IBA application in the current study significantly increased the survival percentage (number of roots, length of roots, number of leaves, and number of sprouts). Same results were obtained in another study by applying different hormones, for the initiation of a maximum rooting percentage in the juvenile fresh stem cuttings of T. wallichiana; IBA is the effective and best hormone (50). It is now decided that IBA is the best rooting auxins for Taxus species and it was confirmed by many workers (36, 29). The time duration of our study was kept 20 weeks after the plantation of the cutting of T. wallichiana. Similarly, the auxins effect on growth and induction of adventitious roots of T. wallichiana cuttings after 4 and ½ months of application/treatment and plant growing. In general, it has been found that among various auxins IBA was the more active for root germination showed the maximum percentage of survival, rooting percentage, percentage of callusing roots per cutting, and length of root per cutting (37, 41, 42, 43, 45, 46). The researcher studied the application of 1000 ppm and 500 ppm of IBA on the T. wallichiana cuttings and found, IBA 500 ppm showed slightly less response than IBA 1000 ppm. IBA 1000 ppm showed the best rooting response on shoot cuttings of T. wallichiana in the spring season with a rooting percentage (95%) compared to other treatments in other seasons (51). In our study the best response was given by 7000 ppm in case of both IBA and IAA. By looking into other studies, it clears that by increasing the concentration up to 7000 ppm the growth will be high.

By using IBA, with some other cultivar of yew (49) that showed that treatment of hormone was very important for successful conservation and propagation of T. wallichiana. By the treatment of hormones, stem cuttings of some other species were also published (55), their research showed that the best response for rooting due to IBA followed by IAA and NAA in rooting percentage, the cuttings heights, number of roots per cutting in Sage, Rosemary, and Elderberry. Similarly, the treatments of auxins (IBA, IAA, and NAA) on the root development were studied in species like Melissa officinalis (52), Ficus Benjamina (53), and Oryza sativa (54).

Auxins are involved in the formation of root, cambial cells activation, and lateral bud inhibition. They have been found as naturally existing compounds that promotes the formation of root and synthetic auxins also stimulating the emergence of root on cuttings. It is well documented and verified maximum time that auxins applied (naturally or artificially) is needed for adventitious root initiation on stem cuttings. Initial cells division of roots is dependent on either endogenous or applied auxins (56).

Our findings are also in similarity with (57) that showed that root development in stem cuttings of T. wallichiana using IBA followed by IAA and NAA and in control where no auxins treatment was given, less root formation was observed in those cuttings, and the lowest survival was found during the observation of cuttings. In this case further the survival becomes very difficult and ultimately the cuttings died. In this respect, our results are similar as obtained by (58).

Thus, our study suggests the utilization of auxins mainly IBA for regeneration of T. wallichiana under natural conditions. The results of our research will be beneficial for developing propagation protocol of T. wallichiana species especially for the moist temperate climate of the Himalayan Region.

This study was aimed to conserve and propagate the Himalayan yew (T. wallichiana) by finding out the best rooting hormone (IBA and IAA) with suitable concentration applied (2000 ppm-7000 ppm) for the regeneration of the fresh stem cuttings. Out of the two different trial, it has been found that 7000 ppm shows higher survival percentage (IBA 85.22% and IAA 81.11%) irrespective of the mode of application and results were highly significant followed bytheir corresponding. Hormones with concentration 6000 ppm was the next best suitable dose that shows maximum survival (IBA 66.67%, IAA 63.33%) followed by 5000ppm > 4000ppm > 3000ppm > 2000 ppm. Therefore, among all the treatments of auxins (IBA and IAA), IBA shows maximum growth (number of roots, root length (cm), number of leaves, and number of sprouts) and survival (IBA > IAA) (Fig. 8–12). The lowest survival percentages were noticed by control cuttings in both the trials.

Study Area

Our study was carried out with the aim to enhance the potential of conservation and propagation of the valuable and endangered medicinal plant T. wallichiana species in Lalku valley of District Swat, KP, Pakistan. Lalku valley has more Taxus density and offers a rich forest cover of pine and oak trees. It lies at an altitude of 1963 meters above sea level, latitude of 35°.1375 and longitude of 72°.38639. Forest area of Lalku forest range is 8580 ha with a Forest cover of 59.3%. In this region,temperature ranges from − 2ºC to 34ºC. The average annual precipitation ranges from 1000–1200 mm. The study period was during November 2016 to November 2017.

Collection, Preparation, and Planting of Cuttings

The formal identification of the T. wallichiana’s plant materials was undertaken by the Directorate of Non-Timber Forest Produce (NTFP), Forest Department, Peshawar; Department of Environmental Sciences, University of Peshawar. Proper permission was granted by the University of Peshawar, Ethical review board. Voucher specimens no. Bot. 20156 (PUP) were deposited in the herbarium of Department of Botany, University of Peshawar.

Cuttings were collected from various mature patches of Himalayan yew. The cuttings were brought to the nursery, raised in Lalku Forest Research Station. The length ofthefinal cuttings were kept 7 to 8 inches and 3 to 4 nodes were retained in each cutting. The needles at the basal portion (about 2 cm) of the stem cuttings were removed and sterilized using 2% benlate (fungicide) before planting. The cuttings were dipped in fungicidal solution for 5 minutesand dried for 20 to 25 minutes in an open environment. The dried cuttings were treated with 50% (Water: Ethanol) concentrated solution of the IBA and IAA (2000–7000 ppm) for 5 minutes and planted in the polythene bags containing soil. The soil was prepared by mixing forest soil, sand and agriculture soil ofthe area in1:1:1 and sieved properly before filling into polythene bags (Fig. 2).

Experimental Design

The experiment was carried out in a randomized block design with a factorial treatment’s arrangement. First trial treatment was carried out with 7 rows and each row containing 20 cuttings. Total of 140 cuttings were taken in the first trial of the experiment (n = 140; x 20 cuttings x 1 type of cuttings x 7 IBA treatments, 3 replications) (Fig. 3). Same was repeated for the second trial of IAA treatments 7 rows with 20 cuttings each, so a total of 140 cuttings were used (n = 140; x 20 cuttings x 1 type of cuttings x 7 IAA treatments, 3 replications) as shown in (Table 1). The trials were evaluated for the number of roots, length of roots, number of leaves, sprouts and survival percentages of cuttings after 20 weeks in 2016-17of planting.

Statistical Analysis

A Statistical software SPSS version 25.0 was used for the analysis. Mean values of all the parameters (number of roots, length of roots (cm), number of leaves, number of sprouts) were calculated to determine the highest growth of each trial for every applied concentrations of hormones (2000 ppm- 7000 ppm).

To compare the average effect of treatment at different level Multivariate Analysis of Variance (MANOVA) technique have been applied. The results of different assumptions which are acquired for applying MANOVA are discussed briefly.

IBA: Indole Butyric acid; IAA: Indole acetic acid; KP: Khyber Pakhtunkhwa; TIFAC: Forecasting and Assessment Council; CITES: Convention for International Trade in Endangered Species; MANOVA: Multivariate Analysis of Variance; IAA: Indole acitic acid.

Ethics approval and consent to participate:

There are no ethical guidelines for research on the conservation of T. wallichiana.

Consent for publication:

Not applicable.

Availability of data and materials:

The additional data regarding the T. wallichiana’s in-situ conservation (relationship between the species growth through hormones (IBA, IAA) applied) by looking into each mentioned parameters (Word docs 40 kb).

In current research study the datasets analysed are available from the corresponding author on reasonable request.

Competing interests:

The authors declare that they have no competing interests.

Funding:

This project was financially supported by the National Research Project for Universities (NRPU), Higher Education Commission (HEC) Pakistan. The project details are: No: 20-3690/NRPU/R&D/HEC/2014/816. The funding bodies have no role in the design and colllection, analysis, interpretation of the data and in writing of the manuscript.

Author’s contribution:

BK designed the research project plan ; JI did field and laboratory work, also wrote the manuscript; SK review and contributed in the writing; NG presented the concept idea; IAM hepled in field work of this study; NY review the manuscript also helped in the laboratory work; IA provide the field design for In-situ experiment at the forest nursery; SM helped to statistically analyse the results. Final manuscript is read and approved by all of the authors.

Acknowledgement:

The co-authors are very thankful to all of the organization (Department of Environmental Sciences, University of Peshawar; Pakistan Forest Institute (PFI); Directorate of Non-Timber Forest Produce, Forest Department, Peshawar; and Higher Education Commission Pakistan (HEC)) who contributed positively in the completion of this project.

Authors details:

¹Department of Environmental Sciences, University of Peshawar, 25120, Khyber Pakhtunkhwa, Pakistan

²Department of Soil and Environmental Sciences, The University of Agricultural Peshawar, 25000, Khyber Pakhtunkhwa, Pakistan

³Directorate of Non-Timber Forest Produce, Forest Department, Peshawar, Khyber Pakhtunkhwa, 25000, Pakistan

⁴Department of Statistic, Islamia College Peshawar, 25120, Khyber Pakhtunkhwa, Pakistan

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Effect of Hormones (IBA & IAA) on the Propagation of Himalayan Yew in Pakistan: A Conservation Approach

Status:

Version 1

Abstract

Background

Results

Conclusion

Figures

Background

Results

Test for normality

Multicollinearity

Discussion

Conclusion

Methods

Study Area

Collection, Preparation, and Planting of Cuttings

Experimental Design

Statistical Analysis

Abbreviations

Declarations

Ethics approval and consent to participate:

Competing interests:

Funding:

Author’s contribution:

Acknowledgement:

References

Supplementary Files

Status:

Version 1