Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It consists of data on rice planting and harvesting dates by growing season and estimates of monthly production for all riceproducing countries. Sources used for planting and harvesting dates include global and regional databases, national publications, online reports, and expert knowledge. Monthly production data were estimated based on annual or seasonal production statistics, and planting and harvesting dates. RiceAtlas has 2,725 spatial units. Compared with available global crop calendars, RiceAtlas is nearly ten times more spatially detailed and has nearly seven times more spatial units, with at least two seasons of calendar data, making RiceAtlas the most comprehensive and detailed spatial database on rice calendar and production.

Abstract. Knowing where and when rice is grown is essential for planning and decision-making in relation to food security, as well as in research wherein crop area and calendar are important inputs in crop production simulations, assessment of biotic and abiotic stresses, and analysis of the effect of climate change on crop production, among others. Remote sensing allows for efficient mapping and characterization of rice areas. In this study, we derived the rice planting window in all rice growing regions in the Philippines from 2016 to 2018 using multi-temporal Synthetic Aperture Radar (SAR), specifically TerraSAR-X and Sentinel-1. Using a rule-based method, rice area and Start of Season (SoS) were mapped based on the unique backscatter behaviour of rice corresponding to the initial deliberate agronomic flooding followed by rapid biomass increase. We defined the planting window per year and semester as the 15th and 85th percentile and the peak of planting as the dominant planting date. The accuracy of the rice map was 93% and the SoS was strongly correlated with the actual planting dates reported by farmers (R2 = 0.71) based on 482 ground observations in the Philippines in 2018 Semester 1. From this analysis, the planting window in the Philippines for the Semester 2 (wet season) is April-August (peak in June-July), and for Semester 1 (dry season) is September-February (peak in November-December) with large differences across regions. In majority of the regions, the planting window spans more than 100 days, which can have implications on incidence of pests and diseases.

Chicken mortality was studied in 24 randomly selected smallholder flocks in one village in Yucatan, Mexico between July and December 1993. Each family received a package of 10 to 12 chicks of 3 weeks of age. Approximately half of the chicks were purebred and the remainder were crosses produced by mating exotic with local breeds. All smallholders were visited twice a week. Feeding and management (except vaccination and medication) were left to smallholders. Data were processed by Chi-square, Mantel-Haenzel test and survival analysis. Before reaching 140 days of age 43.2% of the birds died. The highest mortality was observed during the 113 to 140 days of age period and the lowest was in the period between 22 and 56 days of age. Of all birds, 10.5% died from coccidiosis and 7.6% from Marek's disease. Of the risk factors investigated only medication and genotype showed significant effects on mortality. The effect of genotype was significant up to 112 days of age (P < 0.05). Crossbred birds lived longer than purebred; independently, medicated birds lived longer than non-medicated birds.

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Occurrence of pests and diseases are influenced by several factors including weather, landscape and field-level factors such as crop management practices including crop establishment method. In this paper, we adopted and applied a method using Sentinel-1A (S-1A) Synthetic Aperture Radar (SAR) intensity to discriminate between rice fields that are transplanted and direct seeded to come up with a robust method for automated classification of crop establishment method. Multi-temporal S-1A C-band dual polarization images at 20m resolution covering the wet cropping season over four provinces in the Philippines were acquired from March to November 2018. Field measurements, observations and interviews were conducted on 186 sample fields and mean backscatter values for each of the sampled fields were generated from S-1A data acquired during the season. The reported dates of land preparation and estimated dates of crop growth stages were matched with the corresponding SAR acquisition dates. We used the Mann-Whitney U test to identify growth stages for which there are significant differences in backscatter values between transplanted and direct seeded rice. The results are generally consistent with the findings of a previous study conducted in one province in the Philippines in the dry season of 2017. We found, however, some inconsistencies in terms of the polarization where the significant differences were observed. These findings demonstrate the possibility of discriminating transplanted from direct seeded rice using SAR temporal data but suggests further fine tuning in the methodology is needed for different locations and seasons.