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TUGAS TERSTRUKTUR ILMU HAMA TANAMAN OLEH : Nama : Tadzkiroh NIM : 115040213111047 Kelas : D Dosen Pengasuh : Dr.Ir.TOTO HIMAWAN, SU. JURUSAN HAMA DAN PENYAKIT TUMBUHAN PROGRAM STUDI AGROEKOTEKNOLOGI

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TUGAS TERSTRUKTUR ILMU HAMA TANAMAN

OLEH :Nama : TadzkirohNIM : 115040213111047Kelas : DDosen Pengasuh : Dr.Ir.TOTO HIMAWAN, SU.

JURUSAN HAMA DAN PENYAKIT TUMBUHANPROGRAM STUDI AGROEKOTEKNOLOGIFAKULTAS PERTANIANUNIVERSITAS BRAWIJAYAMALANG2014

1. Build a life table for an aphid population (aphids reproduce parthenogenetically). Estimate lx, dx, mx, Ro, T, and r.

Age, days (x)Number of survivals (ax)Mean number of offsprings per parent (mx) Average number alive from age interval (lx)Jumlah individu yg mati (dx)lx.mxx.lx.mx

010000 10.100

19000 0.90.0800

28200 0.820.0700

37500 0.750.0700

46800 0.680.0600

56200 0.620.0700

65501 0.550.055503300

75002 0.50.0510007000

84505 0.450.05225018000

940010 0.40.05400036000

1035012 0.350.05420042000

1130010 0.30.05300033000

122508 0.250.05200024000

132006 0.20.1120015600

141003 0.10.53004200

15501 0.050.550750

1600 0000

18550183850

Ro= 18550

T= 183850/18550= 9,911

r= ln18550/9,911= 1,078

2. Partial life-table. The European pine sawfly, Neodiprion sertifer, cocoons were collected at the beginning of August and dissected. Results of dissection of new (current year) cocoons are the following: Healthy sawfly eonymph144

Eaten by predators125

Exit hole of parasitoid Drino inconspicua15

Exit hole of parasitoid Pleolophus basizonus78

Larvae of parasitoid Exenterus abruptorius210

Exit hole or larvae of gregarious parasitoid Dahlbominus fuscipennis23

Fungus disease205

Total800

Life-cycle information: Excellent images of parasitoids are available from the PHERODIP homepage. Parasitoids D.inconspicua, P.basizonus and D.fuscipennis have several generations per year, whereas E.abruptorius has only 1 generation. D.inconspicua (Tachinidae) is an endoparasite and attacks larvae (4-5 instar). It emerges from the host immediately after host cocooning. It develops very fast and wins the competition with any other parasitoids. E.abruptorius is an ectoparasite, attacks host eonymphs a day prior to cocooning. Parasitoid larvae emerges inside the cocoon, eats the host and overwinters as larvae inside host cocoon. If the host was previously parasitized by D.inconspicua, then E.abruptorius dies. P.basizonus and D.fuscipennis attack host cocoons. They are ectoparasites. If another parasite (E.abruptorius) is already present in the cocoon, it will be eaten first. D. fuscipennis wins the competition with P.basizonus. Estimate mortality caused by each natural enemy, convert it into k-value. Check that the sum of all k-values is equal to the total k-value for sawfly cocoons. Write results in the table, putting mortality processes in the order of their operation.

Mortality processNumber of killed eggsMortalitySurvival (S)k-value

Eaten by predators1250.156250.843750.169

Exit hole of parasitoid Drino inconspicua150.018750.981250.019

Exit hole of parasitoid Pleolophus basizonus780.09750.90250.102

Larvae of parasitoid Exenterus abruptorius2100.26250.73750.304

Exit hole or larvae of gregarious parasitoid Dahlbominus fuscipennis230.028750.971250.029

Fungus disease2050.256250.743750.296

Total6560.820.181.715

k = -ln(s)

CARA PERHITUNGAN PENDUGAAN KEHILANGAN HASILUntuk memperoleh taksiran kehilangan hasil untuk suatu petak atau hamparan/sawah atau suatu daerah kita harus mempunyai data seperti:1. Luas serangan LSR (dalam ha)2. Intensitas serangan ISR (dalam % rumpun/tanaman terserang)aISR = --------------------- x 100% a+ b

a:jumlah rumpun/batang terserangb:jumlah rumpun/batang tak terserang3. Hubungan antara intensitas serangan dengan hasil tanaman yang diperoleh dari pengalaman petani atau dari hasil penelitian.Suatu contoh:Kita mengetahui dugaan hasil tanaman atau produksi tanaman dalam kondisi intensitas serangan (%) tertentu, katakan 55% intensitas serangan, produksi atau hasil tanaman adalah 14 ton/ha. Kita sebut Produksi Tanaman Terserang (PTT)4. Kita Mengetahui bahwa hasil tanaman yang tidak terserang hama atau produksi tanaman sehat (PTS) adalah 23 ton/ha.5. Harga dari produk/hasil tanaman pada tingkat petani katakan Rp 7500/kg atau Rp 7,5 juta/ton (HG)6. Kehilangan hasil (KH) dalam satuan berat (ton) = Luas serangan (LSR) x Produksi Tanaman Sehat (PTS) --- Luas serangan (LSR) x Produksi Tanaman Terserang (PTT)7. Nilai kehilangan hasil (NKH) dalam rupiah = Harga produk (HG) x KHSuatu contoh: Untuk hama padi di suatu kecamatan ternyata LSR 650 ha. PTT= 14 ton/ha. PTS = 23 ton/ha dan harga padi kering panen (HG) Rp 7500/kg.KH= (LSR x PTS) (LSR x PTT)= (650 x 23) (650 x 14)= 14950 9100 ton= 5850 ton atau 5850000 kgNKH= (HG X KH)= Rp 7500/kg x 5850000 kg= Rp 43875000000 BP = Biaya pengendalian dengan pestisida seluas 1 ha = Rp 130.000 jika pada 650 ha maka Rp 84500000 Nilai ambang pendapatan = biaya pengendalian / harga jual= 84,5 x 106 / 7,5 x 103= 11,27 x 103ALE= nilai ambang pendapatan / nilai kehilangan hasil= 11,27 x 103 / 43875 x 106= 25,7 x 10-6

(rumus ALE didapat dari jurnal berjudul AMBANG KENDALI HAMA Spodoptera exigua (LEPIDOPTERA : NOCTUIDAE) PADA BAWANG MERAH DI DATARAN TINGGI)

ASSIGMENT 1

1. Population numbers of cockroaches double every month (30 d). What is their intrinsic rate of increase (per day)? N1 = 2 N0 = 30N1 = N0 . R2= 30 . RR= 2/30 = 0.0672. What is the intrinsic rate of increase in a human population if every family has 3 children at parent's age of 30 (there are no singles, no divorces, sex ratio 1:1)? What would be the numbers of human population after 100 years if initial numbers are 4 billion? N (t+1)= Nt x R3= 10 x RR= 3/10 = 0.3 Setiap keluarga30 = 3100 = xX = 100 x 3/ 30X = 10Pada 4 miliyar keluarga berarti 4.000.000.000 x 10 = 40.000.000.000 populasi3. A new lake was created after building a dam. The number of fish censused after 2, 4, 6, 8 and 10 years since that time was 1000, 2000, 3500, 5000 and 6000. Estimate parameters of the logistic model using non-linear regression. Plot the data and the model on one graph.

TimeN(t)

21000

42000

63500

85000

106000

4. Use Excel to simulate population dynamics with the discrete-time logistic model (Ricker's model) for 60 generations. Use K=100; r = 0.1, 0.5, 1.0, 1.5, 1.9, 2.2; N0 = 10.

N(t+1) = N(t)*exp(r*(1-N(t)/K))

K = 100, r = 0.1

Tine, tN(t)

010

110.94174

211.9609

313.06168

414.24806

515.52377

616.89215

718.35601

819.91754

921.57819

1023.33852

1125.19805

1227.1552

1329.20714

1431.34975

1533.57751

1635.88355

1738.25963

1840.69624

1943.18268

2045.70724

2148.25742

2250.82011

2353.38192

2455.9294

2558.44936

2660.92913

2763.3568

2865.72145

2968.01335

3070.22403

3172.34646

3274.37502

3376.30551

3478.13512

3579.86235

3681.48689

3783.00952

3884.43194

3985.75666

4086.98686

4188.12623

4289.17886

4390.14912

4491.04156

4591.86081

4692.61153

4793.29832

4893.92568

4994.49795

5095.01932

5195.49376

5295.92505

5396.31673

5496.67215

5596.9944

5697.28636

5797.55072

5897.78994

5998.0063

6098.20189

K = 100, r = 0.5

Tine, tN(t)

010

115.68312

223.90696

334.97504

448.41257

562.65833

675.52056

785.35356

891.83875

995.66386

1097.76057

1198.86136

1299.4258

1399.71166

1499.85552

1599.92768

1699.96382

1799.98191

1899.99095

1999.99548

2099.99774

2199.99887

2299.99943

2399.99972

2499.99986

2599.99993

2699.99996

2799.99998

2899.99999

29100

30100

31100

32100

33100

34100

35100

36100

37100

38100

39100

40100

41100

42100

43100

44100

45100

46100

47100

48100

49100

50100

51100

52100

53100

54100

55100

56100

57100

58100

59100

60100

K = 100, r = 1.0Tine, tN(t)

010

124.59603

252.28057

384.25257

498.6219

599.99042

6100

7100

8100

9100

10100

11100

12100

13100

14100

15100

16100

17100

18100

19100

20100

21100

22100

23100

24100

25100

26100

27100

28100

29100

30100

31100

32100

33100

34100

35100

36100

37100

38100

39100

40100

41100

42100

43100

44100

45100

46100

47100

48100

49100

50100

51100

52100

53100

54100

55100

56100

57100

58100

59100

60100

K = 100, r = 1.5

Tine, tN(t)

010

138.57426

296.92827

3101.4988

499.24235

5100.3766

699.81115

7100.0943

899.95282

9100.0236

1099.98821

11100.0059

1299.99705

13100.0015

1499.99926

15100.0004

1699.99982

17100.0001

1899.99995

19100

2099.99999

21100

22100

23100

24100

25100

26100

27100

28100

29100

30100

31100

32100

33100

34100

35100

36100

37100

38100

39100

40100

41100

42100

43100

44100

45100

46100

47100

48100

49100

50100

51100

52100

53100

54100

55100

56100

57100

58100

59100

60100

K = 100, r = 1.9

Tine, tN(t)

010

155.28961

2129.2932

374.10717

4121.2041

581.01204

6116.2065

785.40845

8112.6949

988.54232

10110.0766

1190.89646

12108.0602

1392.71635

14106.4776

1594.14731

16105.2209

1795.2843

18104.2158

1996.1937

20103.4081

2196.92419

22102.7573

2397.5126

24102.2317

2597.98742

26101.8069

2798.37105

28101.4632

2998.68125

30101.1851

3198.93221

32100.9598

3399.13532

34100.7775

3599.29975

36100.6297

3799.43288

38100.5101

3999.54068

40100.4132

4199.62798

42100.3347

4399.69868

44100.2711

4599.75594

46100.2196

4799.80232

48100.1779

4999.83988

50100.1441

5199.87031

52100.1167

5399.89495

54100.0945

5599.91491

56100.0766

5799.93108

58100.062

5999.94417

60100.0502

K = 100, r = 2.2

Tine, tN(t)

010

172.42743

2132.8448

364.49552

4140.8498

557.33997

6146.5723

752.61118

8149.2291

950.5237

10150.0429

1149.89784

12150.2387

1349.7482

14150.2821

1549.7151

16150.2915

1749.70792

18150.2935

1949.70637

20150.2939

2149.70603

22150.294

2349.70596

24150.2941

2549.70595

26150.2941

2749.70594

28150.2941

2949.70594

30150.2941

3149.70594

32150.2941

3349.70594

34150.2941

3549.70594

36150.2941

3749.70594

38150.2941

3949.70594

40150.2941

4149.70594

42150.2941

4349.70594

44150.2941

4549.70594

46150.2941

4749.70594

48150.2941

4949.70594

50150.2941

5149.70594

52150.2941

5349.70594

54150.2941

5549.70594

56150.2941

5749.70594

58150.2941

5949.70594

60150.2941