Climate change and its variability are some of the most critical threats to sustainable agriculture, with potentially severe consequences on Indonesia’s agriculture, such as changes in rainfall patterns, especially the onset of the wet season and the temporal distribution of rainfall. Most Indonesian farmers receive support from agricultural extension services, and therefore, design their agricultural calendar based on personal experience without considering global climate phenomena, such as La Niña and El Niño, which difficult to interpret on a local scale. This paper describes the Integrated Cropping Calendar Information System (ICCIS) as a mechanism for adapting to climate variability. The ICCIS contains recommendations on planting time, cropping pattern, planting area, varieties, fertilizers, agricultural machinery, potential livestock feed, and crop damage due to climate extremes for rice, maize, and soybean. To accelerate the dissemination of information, the ICCIS is presented in an integrated web-based information system. The ICCIS is disseminated to extension workers and farmers by Task Force of the Assessment Institute for Agricultural Technology (AIAT) located in each province. Based on the survey results, it is known that the ICCIS adoption rate is moderate to high. The AIAT must actively encourage and support the ICCIS Task Force team in each province. Concerning the technological recommendations, it is necessary to update the recommendations for varieties, fertilizer, and feed to be more compatible with local conditions. More accurate information and more intensive dissemination can enrich farmers’ knowledge, allowing for a better understanding of climate hazards and maintaining agricultural production.

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.

Physiological response of coffee plants to their environment was observed through leaf photosynthetic measurement. The leaf photosynthetic efficiency of coffee plants grown in agroforestry was identified at different elevations. Each elevation has variations in ambient air temperatures. OJIP transient fluorometry recorded that the photosynthetic efficiency responds differently at different elevations. The plants grown at 1200 MASL with higher ambient air temperatures experienced a rise in the OJIP steps of fluorescence transients, indicating the closure of some of the PSII reaction centers. However, the coffee plants grown at 1300 MASL, with lower ambient air temperatures and higher exposure to solar radiation, had better electron transport, as indicated by lower OJIP fluorescence transients, when compared to coffee plants grown at 1200 MASL. Regarding the OJIP fluorescence traits, it was found that the plants promoted better photosynthetic efficiency in the area with higher solar radiation and lower ambient air temperatures.

The concept of heat unit or degree days for a seasonal crop is calculated from the planting until harvest. Heat unit analysis can help in determining the optimum harvest time. The purpose of this paper was to determine the harvest time for tomato, chili, cucumber, and shallot based on the accumulation of heat unit in different altitudes, such as 8 m (low), 207 m (low), 517 meters (medium) and 920 meters above sea level (high). The heat unit (HU) = (T_avg -T_base ) *age of each phase. The reference cumulative value of the heat unit at harvest as follows; tomato is 1,661°C days, chili is 1,690°C days, cucumber is 979.8°C days and shallot is 945.8°C days. Based on the analysis, it is known that in the lowlands the harvest is faster than in the highlands because heat accumulation is achieved more quickly. The harvest time in lowland and highland was vary, as follows; around 41-66 days on tomatoes, 41-66 days on chilies, 30-37 days on cucumbers, and 29-36 days on shallots. By knowing the span of harvest time, it is hoped that the planting schedule for these vegetables will be adjusted to the needs and location.

The appropriate planting time is an alternative to avoid loss yield and increase the production of food crops. The objectives of this study were to analyze water balance for adjusting the proper planting time was carried out in three locations with different rainfall patterns and groundwater capacities. The analysis was performed using the water balance approach. Input data used are rainfall prediction potential evapotranspiration and groundwater storage capacity. The results showed that the water balance analysis in Bandar Sidoras Irrigation Area with an equatorial rainfall pattern has a water surplus period of 2 to 3 months longer than the Mrican Kanan and Gadungan Lambuk Irrigation Area, which have a monsoon rainfall pattern. However, the potential cropping pattern applied in each Irrigation Area is the same, Rice-Rice-Maize/Soybean, with the first planting season in Gadungan Lambuk in earlier of May to August. In comparison, the first planting season in the other two irrigation areas is from November to February. The water balance and rainfall prediction approaches are appropriate for determining optimal growth and development of food crops.