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The growth of the Indonesian population has led to an increase in the demand for rice, which the country has yet to satisfy. Indonesia needs a comprehensive strategy that integrates meaningful efforts to increase its agricultural production. This study aims to review the examined trends in rice yield in Indonesia for 70 years after Indonesia’s independence (1945–2016) followed by the identification of the application technology and factors that contribute to increasing rice yields to forecast sustainable food security scenarios up to 2030. This article reviews the results of research on rice production technology in Indonesia from 1945 to 2016, and the outlook for 2030. This paper examines the main points of the Indonesian transformation of rice technology: improvement of rice varieties, integrated crop management, innovations in agricultural machinery, and the Integrated Cropping Calendar Information System (ICCIS). We found that transformation has helped Indonesia increased its rice yields from 3 t ha−1 prior to 1961 to 4.6 t ha−1 in 1985, stagnated in 1990, and increased again in 2017 to 5.46 t ha−1. The increase in yield was sustained by an increase in the harvested area owing to cropping index (CI) innovation. Food security and sustainable development remain the primary goals of Indonesia’s agricultural sector. The application of appropriate technologies and institutional innovations can assist Indonesia in achieving its food security. Therefore, the transformation of technological innovations will continue to be an essential driver of future agricultural growth, including greater use of crop varieties, machinery, and land/institutional reforms.

Climate change has been affecting agricultural water resources dynamics spatially and temporally. This article presents analysis results of climate change impact on agricultural water availability in Cimanuk Watershed, Indonesia. STREAM was utilized to model agricultural water availability through FAO MOSAICC web application. Climate spatial data time-series were generated using 3 Global Climate Model (GCM), i.e.,: CanESM2, CNRM-CM5, and MPI-ESM-MR following two climate change scenarios of RCP4.5 and 8.5. Model inputs were split into three periods of 1981–2010 (historical), 2010–2039 (near-future), and 2040–2069 (far-future). Historical data model validation showed the efficiency coefficient of the observed and simulated discharge data ratio was 0.68. The results showed a decreasing volumetric water availability from all generated climate data and scenarios, identified by comparing the discharge normal distribution of the historical and future data periods. Whereas, trend analysis of RCP4.5 scenario showed increasing maximum discharge of Cimanuk river using CanESM2 and MPI-ESM-MR GCM’s data, with a Mann–Kendall coefficient of 3.23 and 3.57. These results indicate a different agricultural water balance status within the watershed area, particularly a “very critical” water balance in Indramayu and Majalengka, “critical” in Garut, and “close to critical” in Sumedang Regency.

Kajian hidrologis yang terintegrasi dengan analisis waktu tanam di daerah irigasi diperlukan untuk mendukung sistem produksi tanaman pangan khususnya padi. Kajian dilakukan melalui (1) Identifikasi Karakteristik distribusi spasial Daerah Irigasi Kewenangan Pusat (2) Analisis distribusi temporal ketersediaan air irigasi pada tingkat Kecamatan berdasarkan sebaran daerah irigasi kewenangan pusat (3) Penentuan waktu tanam terbaik dan menghitung luas panen berdasarkan analisis neraca ketersediaan-kebutuhan air lahan sawah. Hasil penelitian menunjukkan Ketersediaan air di Daerah Irigasi (DI) Way Rarem Lampung dan Daerah Irigasi Colo Jawa Tengah dapat memenuhi pasokan irigasi pada MT I dan MT II bahkan di beberapa wilayah dapat digunakan hingga MT III. Ketersediaan air di DI Way Rarem meningkat pada Oktober minggu pertama (Oktober I) dan mencapai puncaknya pada Januari I selanjutnya mengalami penurunan sampai mencapai ketersediaan air terendah pada Agustus I. Ketersediaan air di DI Colo relatif konstan yang dapat dipenuhi dari pasokan irigasi dan curah hujan, kecuali pada Oktober II -November I karena jadwal rutin perawatan dan perbaikan bangunan dan saluran irigasi. Hasil penetapan waktu tanam tingkat kecamatan pada DI Way Rarem untuk MT I pada Oktober II sampai dengan Februari I, untuk MT II pada Februari II sampai dengan Juni I dan MT III dari Juli I sampai dengan Oktober I. Untuk DI Colo pada MT I pada November minggu ke satu/dua sampai dengan Februari minggu ke tiga/ Maret I, untuk MT II pada Maret minggu ke I/II sampai dengan April I/Juni III dan MT III dari Juli I/II sampai dengan September III

In the future, Indonesia will become increasingly dependent on dryland agriculture. New adaptive technology innovations able to transform drylands into arable land throughout almost the entire year have been developed to anticipate global climate change in tropical areas. This article reviews the results of research on the importance of climate and water management technology to increase the crop index and productivity in Indonesia. We found that irrigation treatment at 80% of the FAO-recommended rate resulted in the highest maize stover yield (around 13.65–14.10 t h−1). Irrigation treatment at 60% of the FAO-recommended rate for soybeans (at 0.24 L s−1 h−1) produced good-quality soybean seeds. The use of existing water resources can increase the planted area from 1.25 to 1.67 and increase the cropping index during the second planting season in the same area. Agricultural systems based on water management can improve their crop index and productivity, and anticipate climate change to increase farmers’ incomes and wellbeing. Support measures in the form of regulations, legislation, acts, programmes, and policies from central and local governments for land use and management are crucial. The development of infrastructure by establishing water management institutions at the village/farmers’ group levels to allocate irrigation water is a leverage point to develop dryland agricultural systems appropriately and judiciously to assist in sustainable development.

Integrated Cropping Calendar Information System (ICCIS) is an application used to convey innovative research results related to cropping patterns, varieties, fertilization, pest attacks, agricultural tools and machinery. This study aims to identify the influencing factors and communication models in the implementation of ICCIS in the North Sumatra region. Data analysis uses the Partial Least Squares Structural Equation Modelling (PLS-SEM) method. The result showed that the ICCIS Task Force Team (TGT Katam), characteristics of farmers, and characteristics of ICCIS have positive effects on the level of implementation of ICCIS by farmers, with variable significance values of 3.902, 3.851, and 8,296, respectively. In related to the level of application of ICCIS by farmers, the analysis results have a positive effect on the added value of the use of ICCIS with a significance value of 6.509. TGT Katam received ICCIS information from the central cropping calendar team and the technical implementation unit that oversees it. TGT Katam in the North Sumatra region delivered ICCIS information to farmers through socialization and demonstration plots. Interpersonal communication and the demonstration plot media encouraged farmers to implement ICCIS recommendations. Satisfy the local wisdom, compatibility, data accuracy, trialability, observability, and relative advantage are indicators that farmers can implement ICCIS.

Apriyana Y, Sarvina Y, Dewi ER, Pramudia A. 2017. Farmer adaptation strategy in paddy field affected by climate variability in monsoon regions. Asian J Agric 1: 9-16. Adaptation of agriculture cultivation to climate variability and climate anomalies both in paddy field especially in monsoon regions is one of the strategies to minimize the impact of these two phenomena to reduce the economic loss, particularly for food security in Indonesia. The objectives of this study are: (i) to identify onset and cropping pattern in irrigated land, rainfed and dry land in affected area due to climate anomalies, (ii) to collect information on carrying capacity water resources and adaptation practices applied by farmers and, (iii) to identify strategies for farmers on irrigated land, rainfed and dry land in the region affected by climate variability. The desk work analysis and field survey were conducted in Serang District, Banten Province, Subang District, West Java Province and Pati District, Central Jawa Province, Indonesia. The study was undertaken in three cluster activities i.e. (i) correlation analysis of climate anomalies and rainfall, (ii) field survey and, (iii) analysis of onset planting season, cropping pattern, water availability, the best planting time and irrigation schedule. The results showed that the farmers in affected area due to climate variability could adapt by shifting the onset of planting season. Farmers in irrigated lands changed their onset around 2-4 ten-days period to October II - December II. Furthermore, in rainfed areas, the onset around 4-6 ten-days period was shifted to November I - January III. For dry land their onset around 6-8 ten-days period was moved to November II - February I. The cropping pattern rice-rice-palawija/fallow was applied on irrigated land. Furthermore, the pattern of rice-rice/palawija/fallow-fallow was carried out in rainfed. Finally, the pattern of palawija-palawija/fallow-dormant was performed on the dry land. Adaptation programs dealing with climate variability in Serang and Pati Districts varied more than in Subang District. In Serang and Pati, during the first planting season, farmers applied irrigation roughly 20%-30% of water pump from the river and during second planting season, farmers in Pati District used water from well-pump, as well as in Serang that can reach 100% of the application.

Peta Sumberdaya Agroklimat yang dihasilkan dari analisis ini menyajikan klasifikasi iklim Indonesia yang merupakan pemutakhiran dari Atlas Sumber Daya Iklim Pertanian Indonesia tahun 2003. Kebaruan klasifikasi ini adalah periode data 1981-2010 (mengikuti periode normal Badan Meterologi Klimatologi dan Geofisika, disusun dari 4.032 stasiun hujan yang lolos kualiti kontrol data dan pendapat pakar, dianalisis dengan metode geostatistik terpilih, yaitu teknik interpolasi co-kriging dengan parameter pendukung ketinggian tempat. Klasifikasi Peta Sumberdaya Agroklimat didasarkan pada klasifikasi curah hujan tahunan, jumlah bulan basah dan bulan kering berturut-turut sesuai kriteria Oldeman, serta ketinggian tempat untuk pilihan komoditas. Peta Sumberdaya Agroklimat Indonesia memberikan 18 Tipe Agroklimat dengan 3 tipe iklim (basah, sedang, kering), 3 kelas curah hujan, 3 kelas bulan basah bertutut-turut dan 3 bulan kering berturut-turut, dengan informasi potensi tanam dan alternatif pola tanam. Informasi potensi Indeks Pertanaman (IP) dan alternatif pola tanam dapat digunakan sebagai pedoman perencanaan tanam sehingga dapat memaksimalkan IP di suatu wilayah dan pemilihan komoditas yang sesuai. Wilayah yang IP-nya dibawah potensi IP, dapat ditingkatkan IP-nya dengan memanfaatkan potensi air yang ada, sedangkan untuk wilayah yang IP nya ingin ditingkatkan tetapi potensi IP nya tidak mendukung disarankan dapat menggunakan teknologi penyediaan air. Abstract . The Agro-climate Resource Map, resulted from this analysis, is a classification of Indonesia's climate which is a revised version of the Atlas of Indonesian Agricultural Climate Resources (2003). The novelty of this classification is the inclusion of 1981-2010 data period (following the normal MCGA period), compiled from 4.032 rainfall stations that passed the quality control data and expert judgement, analyzed by geostatistical method through co-kriging interpolation technique with the altitude used as a supporting parameter. The classification of the Agro-climate Resource Map is based on the classification of annual rainfall, the number of consecutive wet and dry months according to Oldeman's criteria, and altitude for the choice of commodities. The Agro-climate Resource Map provides 18 classifications of Agro-climate Types with 3 types of climates (wet, moderate, dry), 3 rainfall classes, 3 consecutive wet month classes and 3 consecutive dry months, with information on planting potential and alternative cropping patterns. Information on the potential for cropping index (IP) can be used as a guideline for planting planning so as to maximize the IP in an area. Areas whose IP is below the potential IP, their IP can be increased by utilizing the existing water potential, while for areas whose IP needs to be increased but is not supported by the IP potential, IP increase can be achieved by improving water availability through implementation of water engineering technology.

Climate change is a crucial issue concern in this century. The increase in temperature and changes in rainfall has a substantial effect on the agricultural sector. This study investigates the impact of climate change on water availability and crop evapotranspiration (ETc) in seven locations. The historical data (1981-2005) and The GCM data (ACCESS1-0) for the CMIP5 project for 45 years (2006-2050) under RCP 4.5 and RCP 8.5 scenarios were used to analyze the trend of temperature, rainfall, crop evapotranspiration, and changes in water availability using The Mann-Kendall test. In this study, crop evapotranspiration is calculated to assess monthly crop water requirement, while deficit rainfall is using to calculate the water deficit on paddy rice. This study shows that the temperature and crop evapotranspiration have a significant positive trend under historical, RCP 4.5, and RCP 8.5 scenarios. Otherwise, rainfall shows a relatively decreasing trend for historical RCP 4.5 and RCP 8.5 scenarios. Crop water requirement is projected to increase in the future. Rainwater would insufficient to crop water requirements in a certain month. Shifting the planting time and adjusting the cropping pattern is a strategy to adapt and mitigate climate change.

The information system of integrated cropping calendar (KATAM) has been broadly applied in Indonesia and become a guideline for the users entering the next planting season, however, it allows limited options of planting time of one season. The aim of this study was to evaluate planting time scenarios to improve rice productivity using the crop simulation model Agricultural Production System Simulator (APSIM) in Bogor. Options evaluated considered three planting times, the growing season and water treatment. The simulated productivity values between 3 planting times were compared and analyzed. Result showed that APSIM could simulate productivity with a reasonably good accuracy (EF=0.74) across the different planting times following the season. For the irrigated rice, the late planting resulted similar productivity to the KATAM planting within the rainy (5.1 to 5.5 t ha−1) and dry season (5.6 to 5.8 t ha−1), whereas the early planting resulted the lowest productivity (3 to 5 t ha−1). For the rainfed rice, the early planting presented the same productivity as the KATAM planting within the rainy (2.9 to 3.2 t ha−1) and dry season (4.0 to 4.3 t ha−1), respectively. This study confirmed simulation modeling is a useful tool in providing options for rice cropping systems and that a planting time based on the prevailing season conditions will ensure the acceptable rice productivity.

The rice monitoring based on Sentinel-2 (SC-S2) has been developed for over nine months. It has been observed as the first and only system which generate rice growth stages maps in 10 m spatial resolution using machine learning in Indonesia. However, the SC-S2 use Support Vector Machine to separate the rice growth stages, which may have poor performances. The objective of this study is to investigate the performance of other classifiers to increase the performance of SC-S2. We used survey data from the field campaign in 2018 and synchronized with Sentinel-2 bands. The model dataset was trained using 61 machine learning algorithms to create 61 rice growth stages models. The models were applied to the Sentinel-2 image of part of Indramayu area. The accuracy, computational time and visual inspection score were collected, and the final score was calculated. The results are the highest final score is Shrinkage Discriminant Analysis, with overall accuracy 88.1% (pp

The relevance of climate extreme events, such as droughts, is well recognized as one of the impacts of climate change. The serious paddy droughts that occur during El Niño climate cycles has increased political awareness of the need to incorporate these in drought-forecasting and warning systems for effective drought management. In this study, we develop a paddy drought hazard forecasting system (PDFS) based on a web-based geographic information system (GIS). The Drought Hazard Index (DHI) was used to derive a deterministic forecast model, which is a simplified version of the probabilistic forecast model used in the previous version of this system. Based on the DHI, rice field areas in Indonesia were classified into four categories: low (1.0< DHI< 3.3), moderate (3.33 < DHI

The relative impacts of the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events of Rice Cropping Calendar on Equatorial and Monsoon Region of Indonesia were studied. The spatial distribution of partial correlations between rainfalls with the ENSO and IOD over West Sumatera and West Java indicated a significant impact on rainfall anomalies normally along the period of September – November. The ENSO and IOD events, which is known as a monsoon type, had a wider impact in West Java, especially over northern of West Java. On the other hand, there was only a little impact of the ENSO and IOD on rainfall anomalies in the southern-west of West Sumatera. This strength was shown to be associated with the evolution of distinct weather types revealed by Pearson analysis. In these regions, the same impact of the ENSO and IOD on the width of planting area was very weak in the period of December-March whereas that in the period of June-November the impact on West Sumatera reached only 10% moreover, the impact in West Java could reach up to 80%. On the period scales, the ENSO and IOD events had significant impacts to delayed onsets of rice cropping calendar in which they were more intense than previous ones. In general, the magnitude of ENSO-delayed onsets was greater than delays to the IOD. The period-stratified ENSO variability during each of the months from September to November had a significant impact of delayed planting 2 to 4 dekads in West Sumatera and 4 to 6 dekads on West Java. This confirmed that strong ENSO events indeed affected the southern of West Sumatera and northern of West Java. Meanwhile, the period-stratified IOD variability on West Sumatera and West Java had a significant impact of delayed planting 2 to 4 dekads.

Lack of water in reproductive phases (flowering, fruit formation and maturation) of mango can reduce fruit production and quality. In these phases the plant must be protected from water stress. The aim of the research was to assess the effect of irrigation on the productivity and quality of mango fruits. The study was conducted at the Cukurgondang Experimental Station, Pasuruan, East Java, from April to December 2013, using 40 mango trees of 21 year-old Arumanis variety. Mangoes were planted on five rows with eight plants for each row and 6 m x 6 m spacing within the row. Fan jet sprayer irrigation was installed using hose according to plant diameter. The irrigation technique of fan jet sprayer with four nozzles per plant was applied at 125, 100, 75, 50 and 0% of crop water requirements or equal to 828, 663, 497, 331 and 0 liters of water per tree, every seven days. The parameters observed were the number and weight of fallen fruits and the number, weight and quality of mangoes harvested. The results showed that irrigation of 50% and 75% of crop water requirement had the highest and lowest number of fallen fruits (26% and 14% of total production), respectively. The highest and lowest total number of mangoes were 3.108 and 1904 fruits, respectively, which were achieved at irrigation of 50% and 75% of crop water requirement. Further, the highest and lowest total weight of mango fruits were 1036.2 and 677.9 kg respectively which were achieved at irrigation of 50% and 125% of crop water requirement. Mango fruits produced were dominated by grades 2 and 3 with A quality.