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Functional Relationship Between Grain Yield and Spikes Per Square Meter of Wheat as Influenced by Seed Rate Under Late Sown Condition

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An experiment was conducted at Agronomy Research Field of Bangladesh Agricultural Research Institute, Gazipur for five consecutive years (2014-2015 to 2018-2019) to establish a functional relationship between grain yield and spikes/m2 of wheat at late sown condition. Variation of spikes/m2 was created by five seed rates (90, 120, 150, 180 and 210 kg/ha). Pooled average value of spikes / m2 was observed the highest (479-506) in 180-210 kg seed /ha. From the structural treatment, the highest grain yield (pooled average of 3876-4153 kg/ha ranged 3295-5028 kg/ha) of wheat was produced in the seed rate of 150-180 kg/ha. The estimated optimum seed rate was found 162.29 kg/ha with the estimated grain yield 3989 kg/ha of wheat at late sown condition through the developed function model of Y=485.91+43.17X-0.133X2 (R2=0.87). Again, the estimate optimum spikes/m2 was noticed 423 when the estimated grain yield of wheat was 4135 kg/ha at late sown condition through the developed functional model of Y=-2837+32.98X-0.039X2 (R2=0.83). The grain yield would be increased about 13% as compared to recommended seed rate (120 kg/ha) of wheat. Spikes / m2 had significant positive correlation with seed rate (r=0.79 at p=0.05) of wheat. Relationship between observed grain yield and predicted grain yield (when relationship between spikes/m2 and grain yield) showed a good consistency (Y=1.0006X, R2=0.94 and r = 0.97 at p<0.01). From the results of the study it is concluded that 162 kg/ha of seed rate and 423 spikes / m2 would be optimum for maximum yield) 4135 kg/ha) of wheat at late sown condition. Bangladesh Agron. J. 2019, 22(1): 105-113
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Bangladesh Agron. J. 2019, 22 (1): 105-113
FUNCTIONAL RELATIONSHIP BETWEEN GRAIN YIELD AND
SPIKES PER SQUARE METER OF WHEAT AS INFLUENCED BY
SEED RATE UNDER LATE SOWN CONDITION
M.A.K. Mian*, A.A. Begum and R.R. Saha
Agronomy Division, BARI, Gazipur 1701
Corresponding E-mail: mianmd.abulkhayer@yahoo.com
(Received: 29 August 2019, Accepted: 16 October 2019)
Keywords: Functional model, grain yield, spikes/m2, wheat, late sown
Abstract
An experiment was conducted at Agronomy Research Field of Bangladesh
Agricultural Research Institute, Gazipur for five consecutive years (2014-
2015 to 2018-2019) to establish a functional relationship between grain
yield and spikes/m2 of wheat at late sown condition. Variation of
spikes/m2 was created by five seed rates (90, 120, 150, 180 and 210
kg/ha). Pooled average value of spikes / m2 was observed the highest
(479-506) in 180-210 kg seed /ha. From the structural treatment, the
highest grain yield (pooled average of 3876-4153 kg/ha ranged 3295-
5028 kg/ha) of wheat was produced in the seed rate of 150-180 kg/ha.
The estimated optimum seed rate was found 162.29 kg/ha with the
estimated grain yield 3989 kg/ha of wheat at late sown condition
through the developed function model of Y=485.91+43.17X-0.133X2
(R2=0.87). Again, the estimate optimum spikes/m2 was noticed 423 when
the estimated grain yield of wheat was 4135 kg/ha at late sown
condition through the developed functional model of Y=-2837+32.98X-
0.039X2 (R2=0.83). The grain yield would be increased about 13% as
compared to recommended seed rate (120 kg/ha) of wheat. Spikes / m2
had significant positive correlation with seed rate (r=0.79 at p=0.05) of
wheat. Relationship between observed grain yield and predicted grain yield
(when relationship between spikes/m2 and grain yield) showed a good
consistency (Y=1.0006X, R2=0.94 and r = 0.97 at p<0.01). From the
results of the study it is concluded that 162 kg/ha of seed rate and 423
spikes / m2 would be optimum for maximum yield) 4135 gk/ah) of wheat
at late sown condition.
Introduction
Wheat is an important cereal food grain after rice in Bangladesh. Wheat
cultivation increased (4.29 times) after independence of Bangladesh (1971) due to
development of high yielding varieties along with improved production technology
(BARI, 2011; BARI, 2017; AIS, 2018). In Bangladesh, area coverage of wheat
is 428800 hectares with an annual production of 1423600 tons (AIS, 2018).
Optimum sowing time of wheat is 15 November to 30 November in Bangladesh
(BARI, 2017). The majority farmers usually grow wheat in the same land after
harvesting of T.
aman
rice and thus, sowing of wheat is often delayed (BARC,
2013). Sowing of wheat in Bangladesh may extend upto 20 December
depending on the weather, topography and harvesting of the preceding rice crop
(BARC, 2013). Grain yield of wheat is reduced @ 82-87 kg/ha/day (32-36%)
after 30 November sowing (Begum and Mian, 2019). Spikes/m2 is a major yield
component which has a significant effect on the grain yield of wheat
(Kadum
et al
., 2019). The increase of spikes/m2 increased the grain yield of
112
Mian et al.
wheat (Mian, 2008; Shankarrao
et al
., 2010). Spikes/m2 is mainly influenced by
seed rate and yield is the function of spikes/m2 of wheat (Bolton, 2018; Sokoto
et al
., 2012). More number of tillers as well as more number of spikes/m2 is
generally noticed in higher seed rate (BARI, 2018; Nimat
et al
., 2013). Proper
growth environment also enhances tillering as well as spikes/m2 of wheat (Mian,
2008; Njuguna
et al
., 2010). Again, the excess seed rate would create more
competition among the tillers producing lower effective spikes/m2 and grain yield
of wheat (Seleiman
et al
., 2016). On the other hand, lower seed rate produces
higher number of tillers per plant up to a level if proper growth environment is
provided. Delayed sowing due to late harvesting of T.
aman
rice and excess
soil moisture in southern part of the country reduce grain yield of wheat (BARC,
2013). At late sown condition, crop growth is retarded with reduced tillering of
wheat producing lower grain yield. Moreover, only main tiller (stem) produces
effective spikes but lateral or tender tiller fail to produce effective tiller or spike
at late sown condition. In modeling concept scientists are trying to establish
relationship between yield and spikes/m2 of wheat for estimating the optimum
spikes/m2 for maximum yield (Mian
et al
., 2012; Moucheshi
et al
., 2013;
Bolton, 2018). Therefore, the experiment was undertaken to establish a functional
relationship between grain yield and spikes/m2 of wheat and to estimate the
optimum spikes / m2 for maximum grain yield at late sown condition.
Materials and Methods
An experiment was conducted at Agronomy Research Field of Bangladesh
Agricultural Research Institute, Gazipur to establish a functional relationship
between grain yield and spikes / m2 of wheat at late sown condition. The
experiment was conducted for five consecutive years of 2014-2015 to 2018-
2019. Variation of spikes /m2 was created by five seed rates (90, 120, 150,
180 and 210 kg/ha). The wheat var. BARI Gom-30 was sown on 15-20
December (late sown condition) in 2014 - 2019. But the optimum sowing time
of wheat is 15-30 November in Bangladesh (BARI, 2017). The experiment was
laid out in a RCB design with four replications. Unit plot size was 8 5 m.
The crop was fertilized with 100-36-25-20-1.8-1.0 kg/ha of N-P-K-S-Zn-B (BARI,
2011). All the nutrients including two third of N were applied as basal. Rest
one third of N was top dressed at CRI stage. Three irrigations were applied at
20 days after emergence (DAE), 60 DAE and 80 DAE. Crop field was weeded
at 25 DAE by spading. The crop was harvested on 27-31 March in 2014--
2019. Data on crop yield and yield components of wheat were recorded. There
was no blast infection in the experimental field. Attempt was made to establish
functional relationship between grain yield and spikes /m2 of wheat using the
quadratic equation like Y= a + bx - cx2. Optimum seed rate and spikes /
m2could be estimated with the following formula from the developed functional
model (Mian
et al
., 2012).
Optimum seed rate and spikes / m2=-b/2c (where b and c are the coefficients).
The experiment was repeated for the consecutive five years to get sufficient data
for establishing the functional relationship. Five years’ data on spikes/m2 and
grain yield of wheat from 2014-2015 to 2018-2019 were used to develop
functional relationship. Some important yield components of wheat were recorded
and presented on the basis of year wise and combined analysis (only combined
effect). The data was subjected to statistical analysis (year wise and combined)
and mean values were compared by LSD (0.05).
Results and Discussion
Functional Relationship of Wheat
113
Yield component and yield
Spikes/m2 was significantly influenced by seed rate (Table 1). The maximum
number of spikes/m2 was produced of 210 kg seed /ha (533) followed 180 kg
seed / ha (505) while the lowest in 90 kg seed /ha (395) in 2014-2015.
Similar trend of spikes / m2 (the highest value ranged 444-573and the lowest
value ranged 348-457) was noticed in the subsequent growing season of 2015-
2016 to 2018-2019. The highest pooled value of spikes/m2 was observed in
210 kg seed /ha (506) followed by 180 kg seed /ha (479) while the lowest in
90 kg seed /ha (398) (Table 1). The results expressed that increasing seed rate
increased spikes/m2gradually. Similarly, higher spikes/m2 in higher seed rate (160
kg/ha as compared to 120 kg/ha) was also reported by BARI (2018). Seed rate
had significant effect on grains / spike (Table 2). The highest grains/ spike was
obtained in 90 kg seed /ha (42) followed by 120 kg seed /ha (41) but the
lowest in 210 kg seed /ha (34) in 2014-2015 (Table 2). Similar trend of grains
/ spike (the highest value ranged 38-52 and the lowest value ranged 26-39) was
noticed in the following growing seasons of 2015-2016 to 2018-2019. The
highest pooled value of grains/ spike was noticed in 90 kg seed /ha (43)
followed by 120 kg seed /ha (40). On the other hand, the lowest value was
found in 210 kg seed /ha (32) (Table 2). The results reveal that grains/spike
was reduced gradually with the increase of seed rate. Higher seed rate possibly
exerted inter tiller competition resulting less number of grains/pike. Less number
of grains/spike in higher seed rate was also reported by Seleiman
et al.
(2016)
and BARI (2018). The weight of 1000-grain was found the highest in 90 kg
seed /ha (45 g) followed by 120 kg seed /ha (44 g) while the lowest in 210
kg seed /ha (39 g) in 2014-2015 (Table 3). Similar trend of 1000-grain weight
(the highest value ranged 42-58 g and the lowest value ranged 32-45 g) was
observed in the growing season of 2015-2016 to 2018-2019. Pooled value of
1000-grain weight was recorded the highest in 90 kg seed /ha (48 g) followed
by 120 kg seed /ha (46 g) giving the lowest in 210 kg seed /ha (38 g) (Table
3). Higher seed rate possibly exerted inter tiller competition reducing individual
grain size and weight as well as lower 1000-grain weight. Reduced 1000-grain
weight of wheat at higher seed rate (160 kg/ha) was also reported by Seleiman
et al
. (2016) and BARI (2018). The grain yield of wheat was significantly
influenced by seed rate (Table 4). The highest grain yield (3803-3858 kg/ha) was
produced in 150-180 kg seed /ha but the lowest (3652 kg/ha) in 90 kg seed
/ha in 2014-2015. On the other hand, the highest grain yield (5028 kg/ha)
was observed in 180 kg seed /ha followed by the 210 kg seed /ha (4839
kg/ha) while the lowest (3652 kg/ha) in 90 kg seed /ha in 2015-2016 (Table
4). Similar trend of grain yield (the highest grain yield ranged 3738-4376 kg/ha
and the lowest value ranged 2436-3225 kg/ha) was noticed in the subsequent
growing season of 2016-2017 to 2018-2019. Pooled grain yield was obtained
the highest in 180 kg seed /ha (4153 kg/ha) followed by 150 kg seed /ha
(3876 kg/ha) producing the lowest in 90 kg seed /ha (3418 kg/ha) (Table 4).
Grain yield was mainly contributed by spikes/m2. Similar results have also been
described by other investigators (Nemat
et al.,
2013; Sherwan
et al
., 2015).
Grain yield increased about 6-14% in 150-180 kg seed /ha as compared to
recommended seed rate (120 kg/ha). The results expressed that higher seed rate
up to 180 kg/ha increased grain yield, afterwards the grain yield declined as the
increase of seed rate (210 kg/ha). Higher seed rate (210 kg/ha) might have
exerted more inter tiller competition resulting poorer yield component and grain
yield of wheat. Moreover, higher seed rate leads the crop to lodging producing
lower grain yield. Higher seed rates (200 kg/ha) resulted in higher lodging of
wheat was also reported by (Laghari
et al
., 2011). The results are in agreement
with the observation of Seleiman
et al
. (2016).
112
Mian et al.
Table 1. Spikes/m2 (no.) of wheat as influenced by seed rate under late sown
condition
Seed rate
(kg/ha)
2014-
2015
2015-
2016
2016-
2017
2017-
2018
2018-
2019
Pooled
90
395
457
383
408
398
120
447
480
412
428
426
150
483
493
443
468
455
180
505
523
464
478
479
210
533
573
493
485
506
LSD (0.05)
41
34
24
32
33
CV (%)
5.66
4.33
4.69
4.91
4.89
Table 2. Grains/spike (no.) of wheat as influenced by seed rate under late sown
condition
Seed rate
(kg/ha)
2014-2015
2015-2016
2016-2017
2017-2018
2018-2019
Pooled
90
42
52
40
41
38
43
120
41
48
39
37
36
40
150
38
45
38
34
35
38
180
37
44
35
30
31
35
210
34
39
33
28
26
32
LSD(0.05)
2.69
2.45
2.07
3.37
2.96
2.48
CV (%)
4.55
3.49
3.22
4.11
5.79
4.29
Table 3. Weight of 1000-grain (g) of wheat as influenced by seed rate under
late sown condition
Seed rate
(kg/ha)
2014-2015
2015-2016
2016-2017
2017-2018
2018-2019
Pooled
90
45
58
43
42
50
48
120
44
57
41
41
49
46
150
43
48
36
38
47
42
180
40
46
34
35
46
40
210
39
43
32
32
45
38
L SD (0.05)
2.89
4.03
3.65
2.05
2.11
2.89
CV (%)
4.46
5.92
4.86
2.54
2.87
4.37
Table 4. Seed yield (kg/ha) of wheat as influenced by seed rate under late sown
condition
Seed rate
(kg/ha)
2014-2015
2015-2016
2016-2017
2017-2018
2018-2019
Pooled
90
3652
4520
3225
3187
2436
3418
120
3781
4592
3743
3405
2804
3651
150
3858
4633
4061
3532
3295
3876
180
3803
5028
4376
3738
3822
4153
210
3586
4839
4065
3584
2464
3708
LSD (0.05)
287
378
373
318
313
328
CV (%)
4.98
5.21
6.22
5.93
5.59
5.66
Functional relationship
Functional Relationship of Wheat
113
Functional relationship between seed rate and spikes/m2 indicates that the effect
of seed rate on spikes/m2 of wheat can be explained 72% by functional model
of Y=2.8613X (R2=0.72) (Table 5 and Fig.1). The coefficient value of 2.8613
indicates that the number of spikes/m2 would be increased @ 2.8613 with the
increase of 1 kg/ha of seed rate. Spikes/m2 showed significant positive
correlation with the seed rate (r=0.79 at p=0.05). Functional relationship between
seed rate and grain yield of wheat shows that the effect of seed rate on grain
yield can be explained 87% by functional model of Y=485.91+43.17X-0.133X2
(R2=0.87) (Table 5 and Fig.2). Number of spikes/m2 had a great impact on the
grain yield of wheat as described by Moucheshi
et al
. (2013). The optimum seed
rate was estimated at 162.29 kg/ha by the functional model of
Y=485.91+43.17X-0.133X2 (R2=0.87). Then the grain yield would be 3989
kg/ha at the estimated seed rate of 162.29 kg/ha. Again, functional relationship
between spikes/m2 and grain yield of wheat indicates that the effect of spikes/m2
on grain yield can be explained 83% by functional model of Y=-2837+32.98X-
0.039X2 (R2=0.83) (Table 5 and Fig. 3). The estimated optimum spikes/m2 was
found 423 by the functional model of Y=-2837+32.98X-0.039X2(R2=0.83).
Table 5. Relationship between different parameters of wheat as influenced by
seed rate
Fig.
no.
Variable
Functional relationship
R2
1.
Seed rate and spikes/m2
Y =2.8613X
R² = 0.72
2.
Seed rate and grain yield
Y =485.91+43.17X-
0.133X2
R² = 0.87
3.
Spike/m2 and grain yield
Y= -2837+ 32.98 X-
0.039X2
R² = 0.83
4.
Observed and predicted grain
yield
Y= 1.0006X
R² = 0.94
-
Seed rate and spikes/m2
correlation coefficient
r=0.79 at
p=0.05
-
Observed grain yield and
predicted grain yield
correlation coefficient
r=0.97 at
p<0.01
Then the grain yield would be 4135 kg/ha at the estimated spikes/m2 of 423
giving 13% higher grain yield as compared to recommended seed rate (120
kg/ha) of wheat. Kadum
et al
. (2019) reported that 481-492 spikes/m2 gave the
highest grain yield (6.46-6.62 t/ha) of wheat. Sokoto
et al.
(2012) also found
that spikes/m2 had significant positive correlation with grain yield of wheat.
Relationship between observed grain yield and predicted grain yield (when
relationship between spikes/m2 and grain yield by the functional model of Y=-
2837+32.98X-0.039X2, R2=0.83) showed a good consistency (Y=1.0006X,
R2=0.94 and r=0.97 at p<0.01) (Table 5 and Fig. 4).
112
Mian et al.
Fig. 1. Functional relationship between seed rate and spikes/m2 of wheat
Fig. 2. Functional relationship between seed rate and grain yield of wheat
Y =2.8613X
R² = 0.72
0
100
200
300
400
500
600
60 90 120 150 180 210 240
Spikes/m2
Seed rate (kg/ha)
Y =485.91+43.17X-0.133X2
R² = 0.87
0
1000
2000
3000
4000
5000
6000
60 90 120 150 180 210 240
Grain yield (kg/ha)
Seed rate (kg/ha)
Functional Relationship of Wheat
113
Fig. 3. Functional relationship between spike/m2 and grain yield of wheat
Fig. 4. Relationship between observed and predicted grain yield of wheat
(Functional model of spike/m2 and grain yield of wheat; Y= -2837+
32.98X-0.039X2, R² = 0.83)
Conclusion
Y= -2837+ 32.98 X-0.039X2
R² = 0.83
0
1000
2000
3000
4000
5000
6000
200 300 400 500 600
Grain yield (kg/ha)
Spikes/m2
Y= 1.0006X
R² = 0.94
r=0.97
0
1000
2000
3000
4000
5000
6000
0 1000 2000 3000 4000 5000 6000
Predicted grain yield (kg/ha)
Observed grain yield (kg/ha)
112
Mian et al.
From the structural treatment, the highest grain yield (pooled of 3876-4153
kg/ha ranged 3295-5028 kg/ha) of wheat was produced with 150-180 kg seed
/ ha. The estimated optimum seed rate was 162.29 kg/ha when the estimated
grain yield was 3989 kg/ha of wheat at late sown condition through the
developed function. Furthermore, the estimated optimum spikes / m2was 423
with the estimated grain yield of 4135 kg/ha of wheat at late sown condition
through the developed function. Then the grain yield would be increased about
13% as compared to recommended seed rate (120 kg/ha) of wheat. About 162
kg/ha of seed rate may be recommended for late sown wheat.
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... The average of 200 seeds/m 2 had the highest average of 366.013% with a significant difference from the two others, and the seeding average of 300 seeds/m 2 had the lowest average of 290,396%. This is in agreement with Al-Hamdani (2020) and Mian et al. (2019) who found significant differences between the seeding average for the harvest index, through the results revealed significant Table 8. Averages of cultivars, seed rates and interaction (cultivars x seed rates) for a trait of 1000-seed weight (g). ...
Article
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This study was conducted in the Tel Kaif area, north of Mosul in 2019-2020. First, five cultivars of bread wheat viz. Aba 99, Tammuz 2, Adnaniya, Abu Ghraib 3, Sham 6 were obtained from the Salah al-Din Seed Examination and Certification Department and then three seeding average (200, 250, 300 seeds/m 2), were planted on lines with a length of 2.5m and a distance of 30cm using the Randomized Complete Block Design with three replicas to study changes on the plant growth traits. The results showed significant differences between all cultivars for all traits as well all the studied traits except for plant height. The interaction between cultivars and seeding rates showed significant differences for the traits (P<0.01). The spike length (cm), the number of spikes/m 2 , the biological yield (g/m 2), and the harvest index % were significant (P<0.05) for the two trait of plant height (cm). The trait of grain yield also showed a positive and significant phenotypic correlation (P<0.01) with all the studied traits except for the trait of plant height.
... g) for cultivar Sham 6, cultivar IPA 99 gave the highest average weight of 1000 seeds (g) with a value of (43.333 g), while cultivar Sham 6 gave the lowest average (32,000 g). It is clear from the comparison of the averages of Harvest Index trait for the cultivar ranged between (456.371%) for the cultivar Aba 99 and (276,748%) for the cultivar Sham 6 [ Al-Hamdani (2020), Mian et al. (2019)], Mamta and Roopkishore (2019)] obtained differences between the cultivars tested by them. It is clear from the foregoing that the cultivar IPA 99 excelled on the rest of the cultivars in all the studied character and thus this father can be used to improve the studied character, followed by the Abu Ghraib 3 cultivar for the characteristics of the number of spikes/m 2 , spike length (cm), plant height (cm) and weight of 1000 seed (g) and grain yield gm/m 2 , followed by Tammuz 2, which was characterized by the trait of spike length (cm), number of grains/spike, harvest index %, weight of 1000 seeds (gm) and grain yield g/m 2 . ...
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This study was conducted in the waterfalls area to the north of Mosul for the season (2019-2020), where the experiment included two factors, the first of which included five cultivars of bread wheat obtained from the Salah al-Din Seed Examination and Certification Department (IPA 99, July 2, Adnaniya, Abu Ghraib 3, Sham 6). The second has three seeding rates, which are (200, 250, 300) seeds/m 2 and the planting was done on lines with a length of 2.5 m and the distance between one line and another is 30 cm using the Randomized complete block design (RCBD) with three replications to study the changes in the nature of plant growth for yield and its components. The components of genetic, phenotypic, environmental and broad sense heritability and the expected genetic improvement among the character were estimated. The results showed significant differences between all cultivars and for all studied characters at the level of 1%. The values of genetic variance were higher than the values of environmental variance for all the studied characters, while the values of the coefficients of genetic and phenotypic variation for the studied character varied. The values of heritability in the broad sense were high for all characters and the expected genetic improvement was low for plant height (cm) and spike length (cm).
... Therefore, it is imperative to adjust optimum plant population accordingly to achieve maximum grain yield. Recently, scientist attempted to qualify the optimum plant population/ears/cobs of cereal crops through functional modeling [18]. The traditional growth analysis model expresses crop growth over time with some assumptions and limitations [19,20]. ...
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... Under climate change situation winter is becoming shorter and temperature is rising Mian, et al. [5]. Generally wheat grows after T.aman rice following T.aman-Wheat cropping pattern in Bangladesh Mian, et al. [6]. Consequently, high temperature stress at the terminal of growing season usually constrains crop yield potential as the stress coincides with the grain filling period of wheat Tahir, et al. [2]. ...
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A field experiment was carried out at Abu Ghraib Research Station-Agricultural Research Department for the growing seasons 2014-2015 and 2015-2016 in order to evaluate the performance of eight introduced bread wheat genotypes from the University of Perth/ Australia Research Station and compare them with the two local varieties IPA 99 and Abu Ghraib 3. The experiment was implemented in randomized completely block design with (R.C.B.D.) with three replicates. The results indicate statistically differences between genotypes for all studied characters. The introduced genotype M7 was superior to other genotypes for kernals.m 2 (492 kernals.m 2), 1000 seed weight (35.50 gm), grain yield (6.62 ton.ha-1) and harvest index (41.68%), while the genotype M2 was superior in grain per spike (62 grain.spike-1) and genotype M4 in total dry weight yield (17.78 ton.ha-1).
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Introduction Model serves to find an optimal solution for planning or decision making. Models allow researchers and decision makers to predict and prescribe management strategies to improve outcomes (Quayyum, 2001). A wide variety of models have been used to relate crop production to management factors (Allen et al. 1994). The effect of such management strategies is evaluated without conducting a new set of long term experiments or waiting for productivity/yield. In statistics, model represents the relationship among the variables and is used to predict the value of one variable to the given values of other variables. At present, model is widely used to predict yield potential and to estimate nutrient requirements of crop. Simple yield models have been developed to predict yield of wheat and pea in America by Panye et al. (2001). A functional relationship between independent and dependent variables is established using a log term experimental data. From this functional model nutrient requirement as well as yield of 1 Abstract The experiment was conducted during six consecutive years of 1998−2004 at six locations of Bangladesh to assess simple functional yield model for the cropping pattern of Mustard-Boro rice-T. aman rice under nutrient management. Models of N, P, K and S for mustard, boro rice and T. aman rice in the cropping pattern showed quadratic polynomial functions with different coefficients of determination. Response of seed yield of mustard to N (R 2 =0.68 at p=0.05) was found more favourable as compared to P, K and S (R 2 =0.52-0.56 at p=0.05). Functional relationship of grain yield of boro rice with N, P, K and S was found significant (R 2 = 0.54-0.79 at p= 0.05-0.01). Further, functional relationship of grain yield of T.aman with N, P, K and S was observed significant (R 2 = 0.52-0.80 at p=0.05-0.01). Optimum nutrient levels for mustard (123-22-49-26 kg ha-1 of N-P-K-S), boro rice (145-26-91-21 kg ha-1 of N-P-K-S) and T.aman rice (136-19-72-15 kg ha-1 of N-P-K-S) were determined by using the developed models. Again, economic nutrient levels for mustard (118-16-46-25 kg ha-1 of N-P-K-S), boro rice (140-25-84-21 kg ha-1 of N-P-K-S) and T.aman rice (131-18-65-15 kg ha-1 of N-P-K-S) were also predicted by using the developed models. Yield of crops in Mustard-boro rice-T.aman rice cropping pattern can also be predicted against assumed nutrient levels by using the functional models. Overall, the model predictions of mustard, boro rice and T.aman rice yields were reasonable and showed consistency between observed and predicted yield.
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The aim of this investigation was to determine the effect of different sowing dates (i.e., 1 st November, 15 th November, 1 st December and 15 th December) on growth, grain filling traits and yield and it components as well as grain quality and rheological properties of bread wheat (Triticum aestivum L.) cultivar Gemmeiza 9 during two growing seasons in Nile Delta region, Egypt. The experiment was carried out in a randomized complete block design with four replications. The results revealed that sowing date on 15 th November surpassed the other sowing dates in all of yield studied parameters, grain filling rate, flour percentage. However, sowing date on 15 th December caused an increase in most of technological properties (protein and wet and dry gluten percentages), milling characteristics (fine and coarse bran percentages) and rheological properties (water absorption percentage, dough stability time and resistance to extension).
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Hand Book of Agricultural Technology. BARC. Farmgate, Dhaka 1215
BARC (Bangladesh Agril. Res. Council). 2013. Hand Book of Agricultural Technology. BARC. Farmgate, Dhaka 1215. pp.21-22.