Search

Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over large areas through field observations. The use of satellite remote sensing data has made phenology data collection easier, although the quality and the utility of such data to understand agro-ecosystem function have not been widely studied. Here, we evaluated satellite data-based estimates of rice phenological stages in California, USA by comparing them with survey data and with predictions by a temperature-driven phenology model. We then used the satellite data-based estimates to quantify the crop phenological response to changes in weather. We used time-series of MODIS satellite data and PhenoRice, a rule-based rice phenology detection algorithm, to determine annual planting, heading and harvest dates of paddy rice in California between 2002 and 2017. At the state level, our satellite-based estimates of rice phenology were very similar to the official survey data, particularly for planting and harvest dates (RMSE = 3.8-4.0 days). Satellite based observations were also similar to predictions by the DD10 temperature-driven phenology model. We analyzed how the timing of these phenological stages varied with concurrent temperature and precipitation over this 16-year time period. We found that planting was earlier in warm springs (-1.4 days °C-1 for mean temperature between mid-April and mid-May) and later in wet years (5.3 days 100 mm-1 for total precipitation from March to April). Higher mean temperature during the pre-heading period of the growing season advanced heading by 2.9 days °C-1 and shortened duration from planting to heading by 1.9 days °C-1. The entire growing season was reduced by 3.2 days °C-1 because of the increased temperature during the rice season. Our findings confirm that satellite data can be an effective way to estimate variations in rice phenology and can provide critical information that can be used to improve understanding of agricultural responses to weather variation.

Over the last 10 yr, California has experienced a series of ever-worsening droughts. Rice, traditionally a flooded crop, has come under increasing scrutiny with respect to its water use, leading to proposals to evaluate alternative irrigation systems. For growers, weed competition is one of the most limiting factors to maintaining high yields, so understanding the shifts among species in weed communities under the proposed alternative irrigation systems is vital. A field study was conducted from 2012 to 2014 to compare weed population and growth dynamics with three irrigation systems: (1) a conventional water-seeded control system (WS-Control), with a permanent flood of 10 to 15 cm from planting until 1 mo prior to harvest; (2) a water-seeded alternate wet and dry system (WS-AWD), with the field flooded from planting until canopy closure, after which floodwater was allowed to subside and the field was reflooded when the soil volumetric water content reached 35%; and (3) a drill-seeded alternate wet and dry system (DS-AWD), with rice drill seeded and then flush irrigated to establish the crop, after which the field was flooded until canopy closure and then underwent an alternate wet and dry (AWD) treatment similar to WS-AWD. In the AWD treatments, there were two drying periods, neither of which occurred after the heading stage. The dynamics of major weed species were evaluated using plant density counts (2012) and relative cover and biomass (2013 and 2014). Grasses (sprangletop and watergrass species) dominated the DS-AWD system; sedges, broadleaves, and grasses dominated both WS systems. The WS-AWD system increased smallflower umbrella sedge relative cover at canopy closure, relative dry weight at harvest, and percent frequency when compared with the WS-Control system. Yields did not differ across treatments when weeds were controlled (P > 0.05); in the absence of herbicides, yields in the WS-AWD were equivalent to the WS-Control (ranging from 40 to 65% of the herbicide-treated yields) and zero in the DS-AWD due to weed pressure. Nomenclature: bearded sprangletop, Leptochloa fusca (L.) Kunth N. Snow; ducksalad, Heteranthera rotundifolia (Kunth) Griseb.; redstem, Ammannia coccinea Rottb.; ricefield bulrush, Schoenoplectus mucronatus (L.) Palla; smallflower umbrella sedge, Cyperus difformis L.; rice (Oryza sativa L.).

Our current understanding of the mechanisms driving spatiotemporal yield variability in rice systems is insufficient for effective management at the sub-field scale. The overall objective of this study was to evaluate the potential of precision management for rice production. The spatiotemporal properties of multiyear yield monitor data from four rice fields, representing varying soil types and locations within the primary rice growing region in California, were quantified and characterized. The role of water management, land-leveling, and the spatial distribution of soil properties in driving yield heterogeneity was explored. Mean yield and coefficient of variation at the sampling points within each field ranged from 9.2 to 12.1 Mg ha-1 and from 7.1 to 14.5 %, respectively. Using a k-means clustering and randomization method, temporally stable yield patterns were identified in three of the four fields. Redistribution of dissolved organic carbon, nitrogen, potassium and salts by lateral flood water movement was observed across all fields, but was only related to yield variability via exacerbating areas with high soil salinity. The effects of cold water temperature and land-leveling on yield variability were not observed. Soil electrical conductivity and/or plant available phosphorus were identified as the underlying causes of the within-field yield patterns using classification and regression trees. Our results demonstrate that while the high temporal yield variability in some rice fields does not permit precision management, in other fields exhibiting stable yield patterns with identifiable causes, precision management and modified water management may improve the profitability and resource-use efficiency of rice production systems. © 2013 Springer Science+Business Media New York.