Testing and Evaluation of Mini Rice Combine Harvester
The combine harvester cuts the standing grain, threshes, and cleans it as it moves over the field. It takes the place of a rice reaper and a stationary thresher. It eliminates the tiresome piling of rice stalks prior to threshing. With the combine harvester, post-harvest losses are minimized.
The combine is adopted for harvesting small grains such as soybeans, sorghum, rice and other crops.
Principles of Operation
Harvesting refers to all operations performed in the field, which includes cutting of the rice stalks (reaping), laying out the paddy on the stubble to dry, stocking and threshing.
The basic operations performed by a combine are cutting the standing grain, feeding the cut grain into the cylinder, threshing the grain from the stalk or stem, separating the grain from the straws, cleaning the grain by removing the chaff and other foreign matters and bagging the threshed grains.
Outstanding Features
The Phil Rice B&S Mini Combine Harvester is used for reaping, threshing, cleaning, and bagging of grains in just one operation. It is suitable to small paddy field for dry and wet season harvesting with minimum grain losses of 1-2%. It allows harvesting even at night, lightweight, allow use of reliable 16-hp B&S cast iron engine locally designed and manufactured. Only two persons are needed to operate the machine.
Instrumentation
During the conduct of performance evaluation of the combine harvester, the following were used:
Digital Weighing Scale
Field Markers
Stop Watch
Steel Meter
Tachometer
Methodology
The combine harvester was operated to a 4-plot ready to harvest rice field. The field dimensions were measured using the push rule meter to get the area. Before the combine started the reaping, the crop standing condition and height were determined. RPM of the engine was also recorded using tachometer.
At the start of operation, downtime was recorded. To determine the speed of the combine, a 10-meter distance was measured. Reference points or field markers were set-up to guide where to start and stop the time recordings.
Four (4) different rice hills on the field were identified to determine the cutting height of the combine. It was measured from the ground surface to the tip of the cut rice tiller. Also, four (4) 1-m2 representative areas were measured. Fallen filled grains during harvesting were counted on these areas prior to grain loss computation.
At the end of the operation, four (4) 100-gram paddy samples were taken. These were used to determine the percent purity.
Data Gathering
In order to evaluate the performance of the Mini Rice Combine Harvester, several parameters were used.
Efficient Working Time, min
T_E = To - T_L
Where T_E=efficient working time ,min
To= total operating time,min
T_L=time loss,min
Forward Speed, km/h
s=d/t
Where s= forward speed, km/h
d=distance, 10-m
t=time, sec
Fuel Consumption1, L/hr
F_c1= V/T_o
Where F_c1= fuel consumption, L/ha
V= volume of gasoline used, L
T_o= total operating time,min
Fuel Consumption2, L/ha
F_c2= V/A
Where F_c2= fuel consumption, L/ha
V= volume of gasoline used, L
A= area, m2
Theoretical Field Capacity, ha/day
C_T=(s)(w)
Where C_T= theoretical field capacity, ha/day
s = forward speed, m/s
w = width of cut, 1.21-m
Actual Field Capacity, ha/day
C_A= A/T_o
Where C_A= actual field capacity, ha/day
A= area, m2
T_o=total operating time
Field Efficiency, %
E_f= C_T/C_A
Where E_f= field efficiency
C_T= Theoretical field capacity, ha/day
C_A= Actual field capacity, ha/day
% Grain Loss
% G.L.= (W/A_c)/(Y/A_T ) X 100
Where G.L= Grain Loss, %
W= weight of the grains expressed in a 1000 grain weight
A_c= area ofcollection
Y= net yield
A_T= total area
Grain Purity, %
P=(1- (W_u- W_c)/W_c ) x 100
Where P= grain purity, %
W_u=weight of uncleaned grain,g
W_c =weight of cleaned grain,g

Results and Discussion
Four rice field plots were selected for the performance evaluation of the Mini Rice Combine Harvester. Based from the results, the average cutting height of the machine was 44.69cm. It is 13.63 cm lower compared to the AMTEC’s result. However, it is recommended that reaping should be done below the panicle level.
Based from the tests done, it was observed that the machine was difficult to shift its speed from first (1st) gear to second (2nd) gear to reverse and vice versa. The brake did not function. Only the clutch was used to stop the machine from running. The speed recorded had an average of 1.84kph. It is slower compared to the 2.05 kph speed result of AMTEC.
During the testing, the average fuel consumed by the machine was 19.98 L/ha, which is nearer to the 19.62 L/ha of AMTEC.
On the four tests conducted, actual field capacity did not vary much. Likewise, the average actual field capacity result showed a little difference of 0.18 ha/day from the AMTEC’s result.
The average field efficiency of the combine was 64.44% which is less than the 86.6% result of AMTEC. The efficiency was affected by the total operating time and forward speed of the combine. The faster the machine and the shorter the operating time to finish the harvesting, the higher is the efficiency.
The average grain loss percentage was 2.02%. It is higher by 0.34% as compared to the AMTEC’s findings. However, the result is still outstanding. In most cases, harvesting incurs 1-3% loss while threshing adds 2-6% grain loss. These losses range from 3-6%. With the use of the machine, a 4% grain recovery is manifested.
Test resul t for average percent purity was 90.67% from the student’s evaluation while 90.3% from AMTEC. The high percentage of purity means that the blower worked efficiently in separating the unfilled grains, straws and other foreign matters.
Computations:
Forward Speed
To get the speed, make an average of the time recorded traveled at a distance of 20 m
Time Average
Plot 1
Time Average = (70+49+60)/3=56.67 sec
Plot 2
Time Average = (30+25.6+44.6)/3=33.4 sec
Plot 3
Time Average = (28+29+32.53)/3=29.84sec
Plot 4
Time Average = (38.48 +41.66+30.69)/3=36.94 sec


Forward Speed

Plot 1
s =((20 m)/(59.67 sec))( (3 600 sec)/(1 hr)) ( 1km/(1000 m)) = 1.21 km/hr

Plot 2
s= 2.16 km/hr
Plot 3
s=((20 m)/(29.84 sec))( (3 600 sec)/(1 hr)) ( 1km/(1000 m)) = 2.41 km/hr
Plot 4
s=((20 m)/(36.94 sec))( (3 600 sec)/(1 hr)) ( 1km/(1000 m)) = 1.95 km/hr
Average
s= (1.21+2.16+2.41+1.95)/4= 1.93 km/hr
Fuel Consumption
Plot 1
F_c1= V/T_o
= (0.75 L)/(0.30 hr)=2.5L/hr
Plot 2
F_c1= V/T_o
= (0.75 L)/(0.22 hr)=3.41L/hr
Plot 3
F_c1= V/T_o
= (0.75 L)/(0.26 hr)=2.88L/hr

Plot 4
F_c1= V/T_o
= (0.75 L)/(0.24 hr)=3 L/hr
Average
F_c1= V/T_o
= (2.5+3.41+2.88+3)/4=2.95 L/hr

Actual Field Capacity
Plot 1
C_A= ((360 m^2)/0.3hr)((1 ha)/(10000 m^2 ))((8 hr )/(1 day))= 0.96 ha/day
Plot 2
C_A= ((392 m^2)/0.22hr)((1 ha)/(10000 m^2 ))((8 hr )/(1 day))=1.43 ha/day
Plot 3
C_A= ((360 m^2)/0.26hr)((1 ha)/(10000 m^2 ))((8 hr )/(1 day))=1.11 ha/day
Plot 4
C_A= ((392 m^2)/0.24hr)((1 ha)/(10000 m^2 ))((8 hr )/(1 day))=1.31 ha/day
Average
C_A= (0.96+1.43+1.11+1.31)/4=1.31 ha/day


Theoretical Field Capacity
Plot 1
C_T = (1.21 km/hr) (1.21 m) ((1 ha)/(10 000 m^2 )) ((1 000 m)/(1 km))((8 hr)/day)= 1.17 ha/day
Plot 2
C_T= (2.16 km/hr) (1.21 m) ((1 ha)/(10 000 m^2 )) ((1 000 m)/(1 km))((8 hr)/day)= 2.09 ha/day
Plot 3
C_T= (2.3 km/hr) (1.21 m) ((1 ha)/(10 000 m^2 )) ((1 000 m)/(1 km))((8 hr)/day)= 2.23ha/day
Plot 4
C_T= (1.98 km/hr) (1.21 m) ((1 ha)/(10 000 m^2 )) ((1 000 m)/(1 km))((8 hr)/day)= 1.92 ha/day
Average
C_T=(.1.17+2.09+2.23+1.92)/4=1.85 ha/day

Field Efficiency
Plot 1
E_f = 0.96/(1.17 ) x 100=82.05%

Plot 2
E_f= 1.43/(2.09 ) x 100=68.02%
Plot 3
E_f= 1.11/(2.23 ) x 100=49.78%
Plot 4
E_f= 1.18/1.92 x 100=61.46%
Average
E_f= (82.05%+ 68.02%+49.78%+ 61.46% )/4=65.44%

Grain Purity
Plot 1
P=(1- (100- 91)/91) x 100 = 90.11%
Plot 2
P=(1- (100- 94)/94) x 100 = 93.62 %
Plot 3
P=(1- (100- 89)/89) x 100 = 87.64%
Plot 4
P=(1- (100- 92)/92) x 100 = 91.30%
Average
P = ( 90.11+ 93.62+ 87.64+91.30 )/4 = 90.66%
% Grain Loss
Plot 1
% G.L. = ((734 grains)(26grams/1000grams)(1kg/1000grams))/((4.75 bags )(50)/360m^2 ) x 100=2.89%
Plot 2
% G.L.= ((535 grains)(26grams/1000grams)(1kg/1000grams))/((4 bags )(50)/392m^2 ) x 100= 2.73%
Plot 3
% G.L.= ((350 grains)(26grams/1000grams)(1kg/1000grams))/((4.5 bags )(50)/360m^2 ) x 100= 1.46%
Plot 4
% G.L.= ((257 grains)(26grams/1000grams)(1kg/1000grams))/((4.75 bags )(50)/392m^2 ) x 100= 1.01%
Average
% G.L.= (2.89%+ 2.73%+ 1.46%+ 1.01% )/4=2.02 %





Table 1.0 Testing and Evaluation for Mini Rice Combine Harvester

Parameters Plot 1 Plot 2 Plot 3 Plot 4 Average AMTEC Evaluation
April 22, 2010 April 22, 2010 April 22, 2010 April 22,2010
Phil Rice Field Area Phil Rice Field Area Phil Rice Field Area Phil Rice Field Area
Crop Stand Nearly lodged Nearly lodged Nearly lodged Nearly lodged
Variety NSIC RC 160 NSIC RC 160 PSB RC 82 PSB RC 82
Height, cm. 79. 27 82. 3 78.03 80.0 78.4
Field Condition Area, m2 360 392 360 392 376
Soil condition Dry Dry Dry Dry
Cutting Height, cm. 53. 17 44.9 39.83 40.3 44.69 54.3
Total Operating Time, hr. 0.3 0.22 0.26 0.24 0.26
Total Operating Time, min 18 13.2 15.6 14.4 15.3
Down Time, sec 47 34
Eff. Working time, min 11.33 10 12 10.2 10.88
Actual Field capacity, ha./day 0.96 1.43 1.02 1.31 1.18 1.0
Theoretical Field capacity, ha./day 1.17 2.09 2.23 1.92 1.85
Field efficiency, % 82.05 68.42 49.78 61.46 65.44 86.6
Forward Speed, kph 1.21 2.16 2.41 1.95 1.93 2.05
Engine RPM 800-900 800-900 800-900 800-900 800-900
Fuel consumption Liters 0.75 0.75 0.75 0.75 0.75
Hours used 0.56 0.39 0.39 0.41 0.44
li./hr. 2.5 3.41 2.88 3 2.95
li./ha 20.83 19.13 20.83 19.13 19.98 19.62
Yield in bags @ 45kg/bag 4.75 4 4.5 4.75 4.5
Grain losses
(average) # of grains/m2 734 535 350 257
469
% 2.89 2.73 1.46 1.01 2.02 1.68%
Purity, % 90.11 93.62 87.64 91.30 90.66 90.3

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