Friday, November 16, 2012

ASSESSING AGRO-CLIMATOLOGICAL MODEL OF SUMMER MUNGBEAN

Dr. Md. Abul Khayer Mian is presenting the paper at the Conference of Bangladesh Society of Agronomy  at BARI held on 6 October 2012.







ASSESSING AGRO-CLIMATOLOGICAL MODEL OF SUMMER MUNGBEAN

M. A. K. Mian1, M. R. Islam1, J. Hossain1 and M. S. Alam2
1RARS and 2PRC, Ishurdi 6620

Key word: Agro-climate, model, summer mungbean and yield 

Abstract

The experiment was conducted at the Regional Agricultural Research station, Ishurdi during 2007 to 2012 to assess the agro-climatic effect on summer mungbean. Three mungbean cv. BARI mug 5, BARI mug 6 and BU mug 4 were sown on 15 March, 25 March and 4 April in each year. Average yield of six years was the highest (1306 kg/ha) in BARI mug 6 at 25 March sowing. Developed functional yield model was Y=4645.56 + 2.42 HDDS + 6.37 Rainfall – 106.91 Tem. – 16.45 TDM + 0.33 TSSH – 63.78 RH (R2=0.67). The effect of agro-climate can be explained about 67% by this functional model. The co-efficients indicate the rate of change of yield due to change of one unit of input variables. The model can be used to predict the yield of summer mungbean or to verify the experimental results at prevailing agro-climatic condition of a particular year.  

Introduction 
Climatic factors have significant effect on crop production. Temperature, rainfall, sunshine hours, relative humidity etc. are the main weather elements that greatly affect the growth and development of crop plant. A good genotype can not exploit its full yield potentially without proper growth environment (Mian et al., 2002) since yield is the function of interaction of genotype and environment (Ullah et al., 2002). Summer mungbean is an important pulse crop in Bangladesh. It covers an area of 41000 ha with an annual production of 49000 tons (AIS, 2012). Its area and production is increasing day by day due to some convenience of short duration varieties, favourable environment and fallowing of lands between winter crops and T. aman rice (Hossain et al., 2010; BARI, 2011).  Temperature is high and rainfall is unpredictable in summer in Bangladesh. The suitable temperature for mungbean is 25-30 0C (Afzal et al., 2008). High temperature is harmful for proper growth and development of crop plant. High temperature, precipitation and desiccating wind increased flower shading in mungbean (Rainey and Griffiths, 2005). Excess rainfall exerted vigorous growth and retarded pod formation (Mian, 2008). Sunshine hours and relative humidity also affect the crop plant as the change of growing time. Recently, environmental scientists and agronomists are interested to quantify the effect of weather elements on growth and yield of crops. In this regard, functional model can help to predict the yield and prescribe the management options to improve yield of crops. Regression analysis is usually deals with the functional relationship for explanation and prediction of a given variable based on one or more variables. Long term experimental data is required to develop a functional model (Allen et al., 1994; Panye et al., 2001). Multiple regression analysis of yield (dependent variable) with weather elements (independent variable) can establish a functional relationship for assessing the effect of agro-climate on the yield of summer mungbean. Therefore, the study was undertaken to assess the effect of agro-climate on summer munbean through developing a functional model.

Materials and Methods
Field experiment was conducted at the Regional Agricultural Research station, Ishurdi during 2007 to 2012. The experiment was conducted in a RCB design with three replications. Three mungbean cv. BARI mug 5, BARI mug 6 and BU mug 4 were sown on 15 March, 25 March and 4 April in each year. Unit plot size was 5 m ´ 4.5 m. Seed was sown at 30 cm apart line following continuous seeding technique. The soil of the experimental plot was sandy loam with PH value of 7.16. Nutrient, 20-40-20 kg ha-1 of N-P-K was applied as basal for the crop (BARI, 2011). Cultural management was done as and when necessary. Crop yield and weather data during 2007 to 2012 was computed and summarized for developing functional yield model (Table 1 and Table 3). Heat degree day sum (HDDS), total rainfall (rainfall), average daily air temperature (Temperature), total sunshine hours (TSSH) and average relative humidity (RH) during total crop growing period, and total dry matter of crop (TDM) were regressed against yield of summer mungbean. Attempt was made for assessing agro-climatological model of summer mungbean following the basic principle of multiple regressions after Payne et al. (2001). 
Y=a+ b1x1+b2x2+b3x3+b4x4+ b5x5+b6x6
Y=Yield (output variable)
a=constant (intercept)
x1............x6 are the input variables (HDDS, Rainfall, Temperature, TDM, TSSH and RH )
b1--------b6 are the coefficients.
HDDS=Heat degree day sum was calculated as follows:  
HDDS=∑(Ta-Bt)

Where
Ta = Daily air temperature
Bt = Base temperature (100C for mungbean, Fyfield and Grerory, 2011). 
 
Results and Discussion
Crop yield
Seed yield variation was noticed among the sowing times over the years (Table 1). The highest seed yield (1485 kg ha-1) was observed in BARI mug 6 at 25 March sowing in 2007. Similar trend of seed yield was followed in 2008, 2010 and 2012. But seed yield was the highest (1464 kg ha-1) in BARI mug 6 at 15 March sowing in 2009. Similar trend of seed yield was observed in 2011. The highest seed yield at 25 March and 15 March sowing in different years possibly happened due to variation of prevailing weather condition especially of temperature and rainfall. Seed yield was lower in 2008 as compared to other years due to unfavourable weather condition (Table 3). Drought weather prevailed in March (8.9 mm rainfall) and April (40.76 mm rainfall) in this year (data was presented in table). Seed yield variation of summer mungbean in different years was also observed by Mian (2008). Average seed yield of six years was the highest (1306 kg ha-1) in BARI mug 6 at 25 March sowing while the lowest in BU mug 4 at 4 April sowing (Table 1). The results indicated that 15 March to 25 March is suitable sowing time for summer mungbean for Ishurdi region. 

Crop model
Developed functional yield model was Y=4645.56 + 2.42 HDDS + 6.37 Rainfall – 106.91 Tem. – 16.45 TDM + 0.33 TSSH – 63.78 RH (R2=0.67) (Table 2). The effect of agro-climate can be explained about 67% by this functional model. Similarly, models using monthly rainfall and HDDS for wheat (R2= 0.62) and pea (R2=0.65) predicted yields well (Payne et al., 2001). The co-efficients of developed model indicate the rate of change of yield due to change of one unit of input variables. HDDS, rainfall, TSSH had positive effect on seed yield of mungbean (Table 2). The coefficient, 2.42 of HDDS indicated that seed yield increased 2.42 kg ha-1 with the increase of one unit of HDDS during the total growing period. Similarly, seed yield increased 6.37 kg ha-1 with the increase of one mili meter rainfall. Seed also increased 0.33 kg ha-1 with increase of one sun shine hour during the growing period. On the contrary, air temperature, total dry matter and relative humidity had shown negative influence on seed yield of mungbean (Table 2). Seed yield decreased 106.91 kg ha-1 with the increase of one degree air temperature (0C) (Table 2). Again, seed yield decreased 16.45 kg ha-1 with the increase of one ton of dry matter of mungbean. Similarly, seed yield decreased 63.78 kg ha-1 with increase of one per cent of relative humidity. Thus the developed model could explain the effect of weather elements on seed yield of summer mungben. Similar functional yield model on wheat and pea was developed by Payne et al. (2001). Prevailing agro-climatic data of another field experimental during 2012 was inserted in the developed model for validation test. Then the predicted seed yield was 921 kg ha-1 which was closer to experimental yield of 998 kg ha-1. Yield variation between predicted yield and observed yield was about 7%. Therefore, the predicted yield is consisted with the experimental yield. Similar consistency in model validation test in corn was also described by Smart et el. (1993). However, the developed model could be able to predict seed yield of summer mungbean satisfactorily under a particular agro-climatic condition.   

Conclusion
The developed model could explain the effect of weather elements on seed yield of summer mungben and it can be used to predict the seed yield of summer mungbean at prevailing agro-climatic condition of a particular year. It also can be use to verify the results of other similar experiments. Sowing time, 15-25 March was suitable for higher seed yield of mungbean for Ishurdi region.   
 

Treatment


Seed yield (kg ha-1)
2007
2008
2009
2010
2011
2012
Mean
S1V1
1279
831
1370
1125
1548
938
1182
S1V2
1321
909
1464
1290
1573
977
1256
S1V3
1102
747
1296
1146
1555
797
1107
S2V1
1288
900
1101
1374
1364
961
1165
S2V2
1485
912
1296
1713
1431
996
1306
S2V3
1125
764
972
1195
1406
908
1062
S3V1
1105
812
781
1093
574
577
824
S3V2
1149
853
985
1259
648
616
918
S3V3
975
727
588
857
420
549
686
LS
**
**
**
**
**
**
-
LSD (0.05)
211
125
172
276
149
154
-
CV (%)
9.34
6.23
5.14
12.66
7.22
10.90
-



** indicates significant at 0.01 level of probability 

S1=15 March
V1=BARI mug 5
S2=25 March
V2=BARI mug 6
S3=4 April
V3=BU mug 4



 Table 2. Intercept, coefficients of input variables and co-efficient of determination of the functional model.

Input variables
Co-efficient of input variables
Intercept (constant)
Co-efficient of determination (R2)
HDDS
2.42


4645.56


0.67
Rainfall
6.37
Temperature
-106.91
TDM
-16.45
TSSH
0.33
RH
-63.78


Table 3.  Summery of weather elements during 2007 to 2012

 Sowing time
Weather element
HDDS


Air Temperature
(0C)
Rainfall (mm)
TSSH


RH (%)


2007
S1
1344
28.67
219
583
79.33


S2
1283
29.74
238
539
79.69


S3
1258
29.96
261
478
81.23
2008
S1
1279
29.54
189
563
79.61


S2
1289
29.96
211
530
80.06


S3
1234
30.28
252
491
80.46
2009
S1
1430
29.33
224
477
81.75


S2
1353
29.61
233
448
81.92


S3
1372
29.88
246
442
81.99
2010
S1
1486
29.81
124
466
73.72


S2
1568
30.36
166
435
76.72


S3
1481
30.57
204
350
78.52
2011
S1
1255
27.42
235
368
76.17


S2
1196
27.59
235
342
77.47


S3
1135
28.02
226
340
77.22
2012
S1
1377
29.12
91
471
68.43


S2
1356
29.94
91
437
69.75


S3
1278
30.28
110
374
71.93


S1=15 March, S2=25 March, S3=4 April


T             Table 4.  Pods plant-1 of summer mungbean as influenced by sowing time (2007-2012)

Treatment
Number of pods plant-1
2007
2008
2009
2010
2011
2012
Mean
16.80


16.02


19.93
16.40
18.13
13.50
16.80


S1V2
17.13


18.01
20.53
15.73
18.10
13.29
17.13


S1V3
15.87


16.23
18.47
14.13
18.06
12.48
15.87


S2V1
16.03


16.32
19.00
14.93
17.76
12.12
16.03


S2V2
17.96


17.39
20.60
19.67
18.83
13.32
17.96


S2V3
15.34


15.32
15.68
16.80
17.46
11.45
15.34


S3V1
13.14


13.36
10.73
18.87
11.83
10.89
13.14


S3V2
14.67


15.39
12.27
20.27
12.90
12.54
14.67


S3V3
10.67


12.92
7.27
12.53
10.76
9.87
10.67


LS
**


**


**
**
**
**
-


LSD (0.05)
2.62


3.21


4.53
3.09
0.45
1.82
-


CV (%)
10.82


11.81


19.87
10.55
3.20
8.66
-




              ** indicates significant at 0.01 level of probability 

S1=15 March
V1=BARI mug 5
S2=25 March
V2=BARI mug 6
S3=4 April
V3=BU mug 4





Reference

Allen, R. O.; D.M. Wilson and E. J. Kamprath. 1994. Estimation of yield and nitrogen removal by corn. Agron. J. 86:1012-1015.
Afzal M. A., M. A. Baker, A. Hamid, M. J. Uddin and M. M. Haque. 2008. Bangladesy Mugdaler Chas (Cultivation of mungbean in Bangladesh). BARI (Bangladesh Agricultural Research Institute), Joydebpur, Gazipur 1701. p. 30. (In Bangla).
AIS (Agricultural Information Service). 2012. Krishi Diary (Agricultural Diary). Agril. Infor. Service, Khamarbari, Farmgate, Dhaka 1215. pp.13-14. (In Bangla).
BARI. 2011. Krishi Projukti Hatboi, Khonda-1 (Handbook of Agro-technology Part-I). Bangladesh Agril. Res. Inst., Gazipur 1701. pp. 158-165. (In Bangla).
Fyfield T. P. and P. J. Grerory. 2011. Effect of temperature and water potential on germination, radicle elongation and emergence of mungbean. J. Experimental Botany. 62:667-374.  
Hossain M. B., M.W. Rahman, M. N. Rahman, A. H. M. N. Anwar and A. K. M. M. Hossen. 2010. Effects of water stress on yield attributes and yield of different mungbean genotypes. Int. J. Sustain. Crop Prod. 5(1):19-24.
Smart J. R., A. Weiss and D. A. Mortensen. 1993. Modeling the influence of posdirected sethoxydim on corn yields. Agron. J. 85:1204-1208.   
Mian M. A. K., A. Ahmed and A. Matin. 2002. Growth, yield and economics of hybrid maize as affected by rate and time of nitrogen application. Bangladesh J. Agril. Res. 27(1):41-46.   
Mian M. A. K. 2008. Performance of maize oriented cropping patterns under different nutrient management. Ph.D. Dissertation. Dept. Agron. Bangladesh Agril. Univ., Mymensingh. pp. 58-59.
Payne W. A., P. E. Ramussen, C. Chen and R. E. Raming. 2001.  Assessing simple wheat and pea models using data from a long-term tillage experiment. Agron. J. 93:250-260.   
Ullah M. J., M. F. Karim, M. S. U. Bhuiya and M. H. Ali. 2002. Fasal utpadon poribesh o babosthapana (Crop production environment and management).  Haji Mohammad Shahidullah, 281/10, Pirerbug, Mirpur, Dhaka 1216. pp.20-31. (In Bangla).


1 comment:

  1. This is a good paper. The learners will be benefited by this paper.It can be used to asses the ago-climate on summer mungbean. It can be used to predict yield at prevailing weather condition of a particular year.

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