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Rice management practices which make the sustainable use of resources more efficient are important interventions towards food security. Monitoring rice crop establishment methods (transplanting or direct seeding) using remote sensing data, can provide vital information on the type of practices as well as their spread and change over time. Direct seeding is a water and labour saving practice that is being promoted across Asia, yet most existing rice crop monitoring methods assume that the rice is transplanted and hence they may not perform as well as direct seeding becomes more popular. To improve the ability of rice crop monitoring methods, it is important to understand the differences in the multi-temporal information due to different crop establishment methods and then incorporate that into improved monitoring systems. Crop establishment is a rapid event that cannot be easily seen with remote sensing. However, we can infer which establishment method is used from resulting observable differences in land surface characteristics such as field condition and crop development stage in terms of delayed or prolonged stages that occur over a longer time. In this study, temporal information from Sentinel-1 Synthetic Aperture Radar (SAR) backscatter was used to first detect alterations in field condition and rice growth, and then link those to crop establishment practices. Farmer surveys and field observations were conducted in the province of Nueva Ecija (Philippines) in four selected municipalities across the province in 2017, to obtain information on field boundaries and crop management practices for 61 fields. Multi-temporal, dual-polarised, C-band backscatter data at 20m spatial resolution was acquired from Sentinel-1A every 12 days over the study area during the dry season, from November 2016 to May 2017. Mean backscatter values were calculated for each rice field and SAR acquisition date. The SAR acquisition dates were selected based on the reported dates for land management activities and the estimated dates of the crop growth stages. We used a Mann-Whitney U test to study whether there are significant differences in backscatter between the two practices during the land management activities and crop growth stages. Significant differences were observed in the early growing season, particularly during land preparation, crop establishment, rice tillering and stem elongation in cross-polarised, co-polarised and band ratio backscatter values. Our findings demonstrated that crop establishment methods could be clearly discriminated by SAR at these stages and that there is more opportunity for their discrimination than has been presented in the earlier literature. The increased practice of dry and wet direct seeding has implications for many remote sensing-based rice monitoring methods that rely on a strong water signal during the early season to determine if a field has been (trans)planted with rice. This signal is weakened or is even non existent when direct seeding is practised. Rice monitoring systems will need to adapt so that they can still accurately monitor the cultivated rice area as new resource conserving crop management practices become more common. As well as SAR intensity information, these algorithms should also incorporate coherence, spectral reflectance and vegetation indices in a multi-sensor approach to rice crop monitoring.

The International Rice Research Institute, in collaboration with partner institutions, collected rice varietal release and adoption data for 11 countries in Asia: China, India, Pakistan, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. For China, data were collected for the top eight rice producing provinces (Anhui, Guangxi, Heilongjiang, Hubei, Hunan, Jiangsu, Jiangxi, Sichuan). For India, five states with predominantly irrigated rice were included in this study (Andhra Pradesh, Haryana, Punjab, Tamil Nadu, Telangana). Adoption data in some countries were derived from existing farm surveys or seed sales. Fourteen expert elicitation meetings were conducted between 2014 and 2016 in areas where there are no data on varietal adoption. Overall, adoption rate of modern rice varieties was 92%. The average varietal age ranged from four to 40 years. Varietal turnover was fastest in China, where there are several breeding institutions that release many varieties annually, and slowest in Myanmar and Thailand due to popular rice varieties that are pureline selection and which were released before 1980.

Purpose: Rice is an important staple crop cultivated in more than 163 million ha globally. Although information on the distribution of global rice production is available by country and, at times, at subnational level, information on its distribution within a year is often lacking in different rice growing regions. Knowing when and where rice is planted and harvested and the associated production is crucial to policy and decision making on food security. To examine seasonal and geographic variations in food supply, we developed a detailed rice crop calendar and linked it with disaggregated production data. Approach and methods used: We compiled from various sources detailed data on rice production, and planting and harvesting dates by growing season. To standardize the production data to the same period, we adjusted the production values so that the totals for each country will be the same as those of FAO for 2010-2012. We then linked data on rice production with the corresponding crop calendar information to estimate production at harvest time by month then we calculated totals for each country and region. Key results: The bulk of global annual harvests of rice is from September to November, corresponding with the harvest of the wet season rice in Asia and Africa. Total rough rice production during those peak months exceed 381 million tons, which account for about half of annual global rice output. Production is lowest in January with only 11 million tons in total. Regional production is lowest in Asia in January, Americas in December, Africa in July and rest of the world in May. Synthesis and Applications: A globally complete and spatially detailed rice crop calendar is important to crop growth simulation modelling and assessment of vulnerability of rice areas to biotic and abiotic stresses. Linked to production estimates, it can be used in analyzing spatial and seasonal production trends to better assess and predict price fluctuations , and to mitigate potential significant shortfalls in food production at certain times of the year.