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Agromet

agromet
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Published by Institut Pertanian Bogor

ISSN : 01263633 EISSN : 2655660X DOI : -

Core Subject : Agriculture,

Agriculture, Biological Sciences & Forestry

Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication includes agricultural meteorology/climatology (the relationships between a wide range of agriculture and meteorology/climatology aspects). Articles related to meteorology/climatology and environment (pollution and atmospheric conditions) may be selectively accepted for publication. This journal is published twice a year by Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University.

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Articles 5 Documents

Search results for , issue "Vol. 31 No. 1 (2017): JUNE 2017" : 5 Documents clear

Analysis of Climate Index with Historical Burn Analysis Method for Climate Change Adaptation (A Case Study in Pacitan District, East Java) Yon Sugiarto; Woro Estiningtyas; Wahyu Sukmana Dewi
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Drought recurrently occurs in Indonesia, and it is one of the climate-related hazards that has a major impact on agriculture and food security. However, there is no a scheme, which allows any damages in agriculture associated with drought event will get an insurance. This study aims to analyze the climate index based on the potency of drought in Pacitan District, East Java to support the development of climate index insurance as an effort to climate change adaptation. This study used a climate index derived from monthly rainfall data, which was calculated based on the historical burn analysis (HBA) method. We examined climate index and measured exit value as representing of the lowest value which payment of insurance should be fully paid. Our results showed that the value varies among sub-districts in Pacitan. Kebonagung sub-district revealed the highest exit value (89 mm), which means the insurance company should pay the full insurance coverage if the rainfall in the period insured below 89 mm. The lowest exit value (18 mm) was in Pringkuku sub-district. Our finding revealed that the index HBA is suitable to be applied in regions with limited climate data. Furthermore, our approach could be one of the strategies to cope with drought to stabilize rice production during the dry season. For wide implementation, supports from government through regulation is needed.

Rainfall Prediction Using Artificial Neural Network Resti Salmayenti; Rahmat Hidayat; Aris Pramudia
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Artificial neural network (ANN) is widely used for modelling in environmental science including climate, especially in rainfall prediction. Current knowledge has used several predictors consisting of historical rainfall data and El Niño Southern Oscillation (ENSO). However, rainfall variability of Indonesian is not only driven by ENSO, but Indian Ocean Dipole (IOD) could also influence variability of rainfall. Here, we proposed to use Dipole Mode Index (DMI) as index of IOD as complementary for ENSO. We found that rainfall variability in region with a monsoonal pattern has a strong correlation with ENSO and DMI. This strong correlation occurred during June-November, but a weak correlation was found for region with rainfall’s equatorial pattern. Based on statistical criteria, our model has R2 0.59 to 0.82, and RMSE 0.04-0.09 for monsoonal region. This finding revealed that our model is suitable to be applied in monsoonal region. In addition, ANN based model likely shows a low accuracy when it uses for long period prediction.

Ability of Ornamental Plants in Adsorbing Dust from Vehicles (Case Study: Bumi Serpong Damai) Sobri Effendy; Nadita Zairina Suchesdian; Ibnul Qayim
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

This research measured several vegetations that were planted in Bumi Serpong Damai, South Tangerang to absorb dust pollutions produced by vehicles. The locations for monitoring were divided based on traffic levels: high, medium and low. We measured the pollution based on two approaches i.e. measuring every four hours and a daily measurement. Based on our monitoring, each species will have different feedbacks to dust pollution at various traffic conditions. We found that species of Heliconia was able to absorb the dust at the top for high traffic condition, whereas Kaca Piring is effective for medium traffic. Our findings revealed that monitoring dust should be frequent at least four hours/day, and selection of species for reducing dust pollution should consider the leave structure.

Micro Climate Humidity in Nursery and Production Various Varieties Melon (Cucumis melo L.) in PKHT Tajur II Dirgha A. S. Adinegara; Rini Hidayati; . Perdinan
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Micro-climatic conditions may affect the growth and productivity of different genotypes of melon farm. This study aims to assess the effect of different moisture conditions in the melon’s nursery to the growth and production of different melon’s genotypes. To observe the effect of moisture, we monitored agronomical (leaf-area index, plant height, fruit weight) and micro-meteorological (transpiration, radiation interception) parameters for two treatments i.e. without modification of moisture (control) and with modification of moisture for period August-November 2015 at the Experimental Garden of IPB in Tajur II-Bogor. Totally, twelve genotypes of melon were used in the study. We found that a transpiration rate was reduced under the control treatment. It appears that the humidity treatment has a greater effect on both measured parameters. The plant height during the germination phased was affected by the humidity treatment, which was confirmed by the two statistical tests (ANOVA and t-test). In addition, our results showed that the treatment had influenced the harvesting time. Under the control treatment, melon seems to have a shorter time to harvest (about 61-63 days after planting), but a lower fruit weight. On the other hand, the modified humidity resulted in a longer time to harvest (68-71 days after planting) and a higher fruit weight. Further, with the treatment we found some genotypes that were potentially able to produce high yield, and some genotypes that were more resistant to dry conditions but they produced a relatively high yield.

Dynamics of Intercepted Solar Radiation to Simulate Dry Matter of Soybean (Glycine Max (L.) Merrill) Pono Ngatui; . Handoko; Bregas Budianto; Marliana Tri Widyastuti
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Solar radiation greatly affects the development of plant biomass. The process of plant development is complex. Here, we simplified this complexity through modeling experiment by integrating climate variables. This study aims to determine the dynamics of canopy intercepted solar radiation under soybean (Glycine Max (L.) Merrill). We employed the shierary-rice model to calculate plant biomass. The results showed that intercepted radiation continuosly increased during vegetative phase, whereas the radiation remains constant during generative phase. Our observation confirmed that the pattern of intercepted radiation followed the angular pattern of sunlight. The intercepted radiation was optimum at 10:00 to 14:00 pm, and it was used to form the plant dry matter. We found that the intercepted radiation contributed until 12%. Based on this contribution, we built our crop model of soybean biomass. Our model performed well in simulating dry biomass with high R2 (0.9), and as indicated by the plot 1:1 between dry matter of model and field observations. Further, the result of t test between model and observed data confirm this strong corelation (p-value 0.07).

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