1 .Title: Statistical Analyses of Crop-Cut Data

2. Trainees: Joseph Philip B. Conlu

Sandy B. Bobier

3. Rationale and Objectives

Rice is one of the major crops cultivated in the country. In order to achieve an outstanding yield, the need for sufficient irrigation is in high consideration.

Hoek et. al. (2001), stated that due to increasing scarcity of freshwater resources that are available for irrigated agriculture. More irrigated land is devoted to rice than any other crop. One method to save water in irrigated rice cultivation is the intermittent drying of the rice fields instead of keeping them continuously flooded. This method is referred to as alternate wetting and drying (AWD) irrigation technology.

The practice of AWD is based on experiments on the moisture threshold that the rice crop can withstand. The technology is implemented after the rice crop is fully established, usually 20-30 days after direct seeding or transplanting. At this stage, the leaves are fully developed, crop canopy is already formed.

On-farm experiments on AWD revealed that water level can be allowed to drop below the ground surface by as much as 15 cm during the dry season and 20 cm during the wet season. It is necessary though to apply irrigation water immediately after this condition is reached to avoid significant reduction in yield.

By applying AWD in the farms, we do not know if there are effects on the vegetative, reproductive, ripening stage, whitehead damage and yield of the rice as compared with the continuously flooded rice field.

Generally, the data analyses aim to determine the effects of AWD on the vegetative, reproductive, ripening stage, whitehead damage and yield of the rice PSB Rc18 variety. Specifically, the data analyses aim to determine the %whitehead damage, moisture content, grain counts(filled and unfilled), and panicle count.

4. Conceptual Framework

In order to achieve the objective of the study, the procedure of implementation was technically formulated. Below is the conceptual framework of the data analyses:

DATA ANALYSES

DATA COMPARISON

DATA GATHERING

SAMPLE CLEANING

SAMPLE GATHERING

4-Hill and 5-m2 samples were taken

Samples were threshed, chaffs were separated, weighed, and moisture content was determined

Data were recorded prior to analysis

Data were analyzed using the Analysis of Variance(ANOVA) and DMRT

Data were compared so as to determine which AWD is applicable for farm irrigation

5. Results and Discussions

A. Vegetative Stage

Table 1.0 Plant Height and No. of tillers Under Continuously Flooded Condition and AWD

Water Threshold Level	Plant Height	No. of tillers
Continuously flooded	48.69	10.66
Saturated	50.66	11.12
AWD at -5	50.89	11.9
AWD at -10	49.98	10.91
AWD at -15	49.47	11.13
AWD at -20	48.58	11.5

Table 1.0 shows the plant height and number of tillers of rice during the vegetative stage. On the plant height, results of ANOVA indicated no significant difference among the varying threshold levels of water having computed F- values less than the 5% level of significance. Likewise, the no. of tillers on AWD did not yield a significant advantage over the control at level of significance. Yet, AWD at -5 both for plant height and no. of recorded higher values compared with the control (Continuously Flooded).

B. Reproductive Stage

Table 2.0 Plant Height, No. of tillers, and Whiteheads under Continuously Flooded Condition and AWD

Water Threshold Level	Plant Height	No. of tillers	Whiteheads
Continuously flooded	96.44	14.93	0.52
Saturated	97.44	14.77	0.44
AWD at -5	97.81	15.71	0.54
AWD at -10	94.71	14.79	0.45
AWD at -15	92.63	14.78	0.35
AWD at -20	93.03	14.14	0.42

Table 2.0 shows the reproductive stage of the rice. It indicates plant height, no. of tillers and whiteheads. Both the plant height and no. of tillers post no significant difference as their computed F- values are less than the 5% level of significance. Moreover, the treatments of whiteheads at 5% level of significance did not have any difference over the control but its block is highly significant at 5% level of significance.

C. Ripening Stage

Table 3.0 Plant Height, No. of tillers, and Whiteheads under Continuously Flooded Condition and AWD

Water Threshold Level	Plant Height	No. of Tillers	Whiteheads
Continuously flooded	96.42	14.96	1.35
Saturated	94.4	14.83	1.19
AWD at -5	96.18	16.18	1.71
AWD at -10	94.43	15.10	0.81
AWD at -15	93.45	14.96	1.23
AWD at -20	91.91	14.65	4.36

Table 3 shows the ripening stage of the rice with its plant height, number of tillers, and whiteheads. ANOVA results showed that there is no significant difference on the plant height and whiteheads at 5% level of significance. However, the number of tillers posted a highly significant remarks on its treatments while not significant on block as source of variation.

D. Fresh Weight of 4-hill sample

Table 4.0 1000-grain Weight, Filled Weight, and Unfilled Weight of 4-hill Sample

Basis of Comparison	1000-grain Weight(grams)	Basis of Comparison	Filled Weight(grams)	Basis of Comparison	Unfilled Weight(grams)
Continuously flooded	24.5	Continuously flooded	126.4	Continuously flooded	4.8
AWD at -15 cm	25.65	AWD at -20 cm	160.05	AWD at -5 cm	5.78
AWD at -10 cm	25.05	AWD at -10 cm	151.25	AWD at -20 cm	5.35
Saturated	24.75	Saturated	139.28	AWD at -10 cm	5.30
AWD at -20 cm	24.48	AWD at -5 cm	134.1	AWD at -15 cm	5.18
AWD at -5 cm	24.03	AWD at -15 cm	128.53	Saturated	4.9

Table 4.0 shows the filled, unfilled and 1000- grain weight of 4- hill samples. ANOVA results showed that the parameters indicated no significant difference among threshold levels of water at 5% level of significance.

E. Grain Count

Table 5.0 Filled and Unfilled Grain Count

Basis of Comparison	No. of Filled Grains	Basis of Comparison	No. of Unfilled Grains	Basis of Comparison	% Filled Spikelets
Continuously flooded	5039.75	Continuously flooded	891.50	Continuously flooded	70.44
AWD at -20 cm	6424.25	AWD at -5 cm	1183	Saturated	88.28
AWD at -10 cm	5944.50	AWD at -10 cm	901	AWD at -20 cm	76.53
AWD at -5 cm	5533.50	AWD at -15 cm	879	AWD at -10 cm	73.98
Saturated	5348.25	Saturated	878	AWD at -15 cm	70.87
AWD at -15 cm	5147.50	AWD at -20 cm	876.25	AWD at -10 cm	63.42

Table 5.0 shows the no. of filled, unfilled grains and % filled spikelets of 4- hill sample. ANOVA results of each parameter indicated no significant difference at 5% level of significance.

F. Panicle count

Table 6.0 Panicle Count of 4-hill Sample

Basis of Comparison	Panicle count
Continuously flooded	60.50
AWD at -5 cm	75.75
AWD at -20 cm	73.75
Saturated	72
AWD at -15 cm	69.5
AWD at -10 cm	69

Table 6.0 shows the panicle count for 4-hill sample. The ANOVA revealed of no significant difference among the threshold water levels at 5% level of significance.

G. Percent Whitehead Damage

Table 7.0 % Whitehead Damage of the 4-hill Sample

Basis of Comparison	% Whitehead Damage
Continuously flooded	9.02
AWD at -5 cm	10.58
Saturated	8.28
AWD at -15 cm	8.22
AWD at -20 cm	7.38
AWD at -10 cm	5.43

Table 7.0 shows the % whitehead damage of the 4-hill samples. There is no significant difference among the levels of water at 5% level of significance.

H. Moisture Content

Table 8.0 Moisture Content of the 5-m² sample

Basis of Comparison	MC(%)
Continuously flooded	14.32
AWD at -5 cm	14.18
AWD at -5 cm	14.11
Saturated	13.88
AWD at -15 cm	13.74
AWD at -20 cm	13.74

Table 8.0 shows the % MC of 5m² sample. Results of ANOVA indicated that there is no significant difference among the varying threshold levels water having computed F- values less than the 5% level of significance.

I. Grain Yield

Table 9.0 Grain Yield of the 4-hill and 5-m² sample

Basis of Comparison	Grain Yield of 4-hill sample (tons/ha)	Basis of Comparison	Grain Yield of 5-m2 sample (tons/ha)
Continuously flooded	6.40	Continuously flooded	5.84
AWD at -20 cm	8.64	AWD at -5 cm	7.52
AWD at -10 cm	7.93	Saturated	6.97
Saturated	6.90	AWD at -20 cm	6.84
AWD at -15 cm	6.80	AWD at -10 cm	6.83
AWD at -5 cm	6.30	AWD at -15 cm	5.68

Table 9.0 shows the Grain Yield from the 4-hill sample and 5m² sample. Both the 4-hill and 5m² sample ANOVA results indicated no significant difference over the control at 5% level of significance.

6. Analysis of Variance (ANOVA) Tables

A. Vegetative Stage

Table 10.0 Plant Height’s ANOVA

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	18.97	3.79	0.40ns	2.90	4.56
Block	3	46.86	12.29	1.30ns	3.29	5.42
Error	15	141.92	9.46
Total	23	207.75

cv- 6.19%

ns-not significant

Table 11.0 Number of Tillers’ ANOVA

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	3.46	0.69	0.55ns	2.90	4.56
Block	3	1.53	0.51	0.40ns	3.29	5.42
Error	15	18.96	1.26
Total	23	23.95

cv- 10.08%

ns-not significant

B. Reproductive Stage

Table 13.0 Plant Height

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	89.42	17.88	1.28ns	2.90	4.56
Block	3	25.54	8.51	0.61ns	3.29	5.42
Error	15	209.69	13.98
Total	23	324.65

cv- 3.94%

ns-not significant

Table 14.0 Number of Tillers

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	5.10	1.02	0.98ns	2.90	4.56
Block	3	1.62	0.54	0.52ns	3.29	5.42
Error	15	15.57	1.04
Total	23	22.29

cv- 6.60%

ns-not significant

Table 15.0 Whiteheads

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	0.09	0.02	0.30ns	2.90	4.56
Block	3	0.98	0.33	5.50ns	3.29	5.42
Error	15	0.90	0.06
Total	23	1.97

cv- 54.18%

ns-not significant

C. Ripening Stage

Table 16.0 Plant Height

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	57.38	11.48	1.24ns	2.90	4.56
Block	3	24.46	8.15	0.87ns	3.29	5.42
Error	15	138.37	9.22
Total	23	220.21

cv- 3.94%

ns-not significant

Table 16.0 Number of Tillers

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	10.78	2.16	2.92*	2.90	4.56
Block	3	0.43	0.14	0.19ns	3.29	5.42
Error	15	11.14	0.74
Total	23	22.35

cv- 5.66%

*-significant

ns-not significant

Table 17.0 Whiteheads

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	1.78	0.36	1.57ns	2.90	4.56
Block	3	1.26	0.42	1.83ns	3.29	5.42
Error	15	3.44	0.23
Total	23	6.48

cv- 39%

ns-not significant

D. Fresh Weight of 4-hill Samples

Table 18.0 Weight of Filled Grains

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	3522.04	704.41	0.94ns	2.90	4.56
Block	3	1833.28	611.09	0.82ns	3.29	5.42
Error	15	11234.41	748.96
Total	23	16589.73

cv- 19.56%

ns-not significant

Table 19.0 Weight of Unfilled Grains

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	2.45	0.49	0.12ns	2.90	4.56
Block	3	5.40	1.80	0.42ns	3.29	5.42
Error	15	63.16	4.21
Total	23	71.01

cv- 39.33%

ns-not significant

Table 20.0 Weight of 1000-Grains

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	6.26	1.25	2.32ns	2.90	4.56
Block	3	1.20	0.40	0.71ns	3.29	5.42
Error	15	8.34	0.56
Total	23	15.80

cv- 3.02%

ns-not significant

E. Grain Count

Table 21.0 Number of Filled Grains

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	5520469.25	1104093.25	0.86ns	2.90	4.56
Block	3	4230095.50	1410031.83	1.09ns	3.29	5.42
Error	15	19365937.75	1291062.52
Total	23	19392938.25

cv- 20.39%

ns-not significant

Table 22.0 Number of Unfilled Grains

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	297554.21	59 510.84	0.60ns	2.90	4.56
Block	3	18637.13	6 122.38	0.06ns	3.29	5.42
Error	15	1478992.62	98 599.51
Total	23	1794913.96

cv- 33.59%

ns-not significant

Table 23.0 % Filled Spikelets

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	1377.90	275.58	9.73**	2.90	4.56
Block	3	37.12	12.37	0.44ns	3.29	5.42
Error	15	424.96	28.33
Total	23	1939.98

cv- 33.59%

**-highly significant

ns-not significant

F. Panicle Count

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	570.33	114.06	0.91ns	2.90	4.56
Block	3	181.83	60.61	0.02ns	3.29	5.42
Error	15	2131.60	125.38
Total	23	2883.83

cv- 15.98%

ns-not significant

G. Percent Whitehead Damage

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	98.62	19.72	1.23ns	2.90	4.56
Block	3	42.59	14.20	0.90ns	3.29	5.42
Error	15	236.67	15.78
Total	23	377.78

cv- 46%

ns-not significant

H. Moisture Content

sv	df	SS	MS	Computed F	Tabulated F
					0.05	0.01
Treatment	5	1.17	0.23	0.23ns	2.90	4.56
Block	3	1.19	0.40	2.35ns	3.29	5.42
Error	15	2.62	0.17
Total	23	4.98

cv- 11.57%

ns-not significant