Case Study: Tasikmalaya Rice Field

Transcription

1 Increasing The Result Of Rice Farming In SRI Method Case Study: Tasikmalaya Rice Field Adiyanti Firdausi, University of Indonesia Dian Putri Indah Mardika, Bandung Institute of Technology Nicky Ria Azizman, Bandung Institute of Technology

2 Abstract Rice is Indonesian primary food which always eaten with vegetables or meat. Nowadays conventional rice farming only cultivate 4 ton for each hectare land on average. With the newly found method of rice farming, the System of Rice Intensification for organic farming will improve the result of conventional farming system with less costs. This method can guarantee an increase of the rice harvested, around 7 ton each hectare, this significant result could help our country in maximizing rice produced. This paper will discuss modification in SRI method with mathematical modeling to get the most effective way of farming and produce maximum result even more than 7 ton/ha.

3 SRI (System of Rice Intensification) The development of the System of Rice Intensification (SRI) began 20 years ago in Madagascar by a Jesuit priest, Fr. Henri de Laulanié, S.J. (Uphoff, 2003a). SRI use organic fertilizer instead of chemical fertilizer and harmful pesticide. SRI use lower cost of maintenance and input cost. SRI provides more rice harvested

4 Tasikmalaya s Rice Field Data The rice that has been planted in Mekarwangi village, Tasikmalaya used the Ciherang rice variety that has the maximum amount of stems of 250, based on all Indonesian SRI planting experiment results recorded by Purwasasmita, Below is the sampled data from Mekarwangi village, Tasikmalaya SRI rice field. rr (distance between crops) KK (amount of stems) DD (yield) 27 cm 60 7 ton 30 cm ton 50 cm ton

5 Mathematical Model (I) This research used mathematics optimization formula and derivatives method to project numerous rice yields for certain distances and plantation system without the need of planting trial on the paddy field. Above figures: The Tegel method / square pattern in rice plantation (left figure) and the plantation system Jajar Legowo 3:1 type 2 (right figure)

6 Mathematical Model (II) Let the equation that defines the rice harvested from 1 hectare farm as DD, this equation is defined as below: DD = NN II cccccccc KK bb The definition for the differential equation of KK for rr is similar with the differential equations models of population growth: dddd = KK(aa cccc) dddd The solution of the differential equation above got the analytical solution as below: KK = aa/cc 1+( aa cckk 0 cckk0 )ee αααα aa/cc = maximum amount of stems that one seedling can produce KK 0 = initial value that is set with young seedlings condition KK > 0 thus KK 0 = KK 0 = 1.

7 Mathematical Model (III) By using sampled data from the Tasikmalaya s SRI rice field itself, constants aa and cc can be found by substituting the amount of stems with the corresponding distance between crops and solve them with Gauss elimination. KK = ( )ee rr The solution of the 3 unknowns are aa = , bb = , and αα =

8 Mathematical Model (IV) The models discussed in the previous chapters assumed for Tegel plantation system, the modification for the model to calculate the yield of Legowo plantation system only needs some adjustments in the amount of stems (KK) and the number of seedlings functions There are 3 variables in Legowo that replaced the distance between crops (rr) in Tegel system, which are JAK (the distance between columns), JAB (distance between rows), JL (the border width) Jajar Legowo 4:1 type 1 plantation system (left figure) and Jajar Legowo 4:1 type 2 plantation system (right figure).

9 Mathematical Model (V) Below are the area calculations Legowo type 1 to absorb nutrients for each seedling: Area of KK tttttttttttt = (JJJJJJ + 1 JJJJ) JJJJJJ 2 Area of KK tttttttttttt = JJJJJJ 2 The area calculations to absorb nutrients for Legowo type 2 were: Area of KK tttttttttttt = (JJJJJJ + 1 JJJJ) JJJJJJ 2 Area of KK tttttttttttt = JJJJJJ 3 2 JJJJJJ The border effect illustration from Jajar Legowo type 1 (top figure) and the border effect illustration from Jajar Legowo type 2 (bottom figure).

10 Optimization Objective Function: Maximize D Constraint: 10 rr 100 In order to maximize D, we are going to find the derivative of D towards r = 0 After finishing those equation then we will have the extreme points. rr 1 = rr 2 = By checking the second derivative for each points that satisfies the above equation, the maximum result for DD is when the distance between crops rr = 40 (rounded to nearest integer).

11 Result The yield of SRI farming at 1 hectare rice field for various distances between crops and plantation system. Description Tegel system with distance between crops rr = 27 cm Tegel system with distance between crops rr = 30 cm Tegel system with distance between crops rr = 40 cm Tegel system with distance between crops rr = 50 cm Jajar Legowo 2:1 Jajar Legowo 3:1 type 1 Jajar Legowo 3:1 type 2 Jajar Legowo 4:1 type 1 Jajar Legowo 4:1 type 2 DD (Yield) 7 ton 7.3 ton 9 ton 7.7 ton 9.29 ton 9.54 ton 8.37 ton 9.69 ton 7.82 ton

12 Conclusion In Tasikmalaya rice field, this mathematical model shows that the optimal distance between crops in SRI farming is 40 cm with Tegel plantation system. Based on the mathematical model in this research, Jajar Legowo 4:1 type 1 with JAB = 15 cm, JAK = 25 cm, JL = 50 cm is the optimal plantation system that produce the most yield than all other types from Legowo and Tegel with same distances. This SRI plantation system gained 9.69 ton per hectare from the simulation that could be applied in Mekarwangi village, Tasikmalaya To implement the model in another place in Indonesia, this model will need some adjustment for the conversion rate and variables.

13 Thank you