The MADS6, JAGGED, and YABBY proteins synergistically determine floral organ development in rice.

MADS6, JAGGED (JAG), and DROOPING LEAF (DL) are key regulators of floral organ patterns in rice (Oryza sativa); however, how they work together in specifying floral organs remains to be determined. Here, we extensively analyzed the coordination mechanism. Genetic interactions showed that all double/triple mutant combinations of mads6-5 with jag and/or dl-sup7 generated an inflorescence from the spikelet center and lemma-like organs (LLOs) at the periphery, indicating that these genes synergistically promote floral organ specification, inhibit inflorescence initiation, and terminate the floral meristem (FM).

Scene-based dual domain non-uniformity correction algorithm for stripe and optics-caused fixed pattern noise removal.

Non-uniformity is a long-standing problem that significantly degrades infrared images through fixed pattern noise (FPN). Existing scene-based algorithms for non-uniformity correction (NUC) effectively eliminate stripe FPN assuming consistent inter-frame non-uniformity. However, they are ineffective in handling spatially continuous optical FPN.

Maps of cropping patterns in China during 2015-2021.

Multiple cropping is a widespread approach for intensifying crop production through rotations of diverse crops. Maps of cropping intensity with crop descriptions are important for supporting sustainable agricultural management. As the most populated country, China ranked first in global cereal production and the percentages of multiple-cropped land are twice of the global average.

Dense canopies browning overshadowed by global greening dominant in sparse canopies.

Greening, an increase in photosynthetically active plant biomass, has been widely reported as period-related and region-specific. We hypothesized that vegetation trends were highly density-dependent with intensified browning in dense canopies and increased greening in sparse canopies. We exploited this insight by estimating vegetation trends in peak growth from dense to sparse canopies graded from 1 to 20 using the non-parametric Mann-Kendall trend test based on the 500 m 8-day composite MODIS Near Infrared Reflectance of terrestrial vegetation (NIRv) time series datasets in the past two decades (2001-2019) at the global scale.

Automatic and adaptive paddy rice mapping using Landsat images: Case study in Songnen Plain in Northeast China.

Spatiotemporal explicit information on paddy rice distribution is essential for ensuring food security and sustainable environmental management. Paddy rice mapping algorithm through the Combined Consideration of Vegetation phenology and Surface water variations (CCVS) has been efficiently applied based on the 8day composites time series datasets. However, the great challenge for phenology-based algorithms introduced by unpromising data availability in middle/high spatial resolution imagery, such as frequent cloud cover and coarse temporal resolution, remained unsolved.

Greater phenological sensitivity on the higher Tibetan Plateau: new insights from weekly 5 km EVI2 datasets.

Plateau vegetation is considered to be highly sensitive to climate change, especially at higher altitudes. Although the Tibetan Plateau has experienced intensive warming over the past few decades, there is much contradictory evidence regarding its phenological variations and the impact of climatic change. In this study, we explored vegetation phenology through the inflexion point-based method with the weekly 0.

Rice cropping density and intensity lessened in southeast China during the twenty-first century.

Accurate and updated time series maps of paddy rice distribution and planting intensity will greatly improve our knowledge. Unfortunately, spatiotemporal explicit information on rice fields is relatively limited, and considerable uncertainties still exist as regards to its inter-annual variations in China. In this study, an improved rice mapping methodology was proposed through combined consideration of vegetation phenology and surface moisture variations from different seasonal rice.

A new approach for crop identification with wavelet variance and JM distance.

This paper develops a new crop mapping method through combined utilization of both time and frequency information based on wavelet variance and Jeffries-Matusita (JM) distance (CIWJ for short). A two-dimensional wavelet spectrum was obtained from datasets of daily continuous vegetation indices through a continuous wavelet transform using the Mexican hat and the Morlet mother wavelets. The time-average wavelet variance (TAWV) and the scale-average wavelet variance (SAWV) were then calculated based on the wavelet spectrum of the Mexican hat and the Morlet wavelet, respectively.

Characterizing spatiotemporal non-stationarity in vegetation dynamics in China using MODIS EVI dataset.

This paper evaluated the spatiotemporal non-stationarity in the vegetation dynamic based on 1-km resolution 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) datasets in China during 2001-2011 through a wavelet transform method. First, it revealed from selected pixels that agricultural crops, natural forests, and meadows were characterized by their distinct intra-annual temporal variation patterns in different climate regions. The amplitude of intra-annual variability generally increased with latitude.