Assessment of the Rice Panicle Initiation by Using NDVI-Based Vegetation Indexes

Joon-Keat Lai,Wen-Shin Lin

doi:10.3390/app112110076

Abstract

The assessment of rice panicle initiation is crucial for the management of nitrogen fertilizer application that affects yield and quality of grain. The occurrence of panicle initiation could be determined via either green ring, internode-elongation, or a 1–2 mm panicle, and was observed through manual dissection. The quadratic polynomial regression model was used to construct the model of the trend of normalized difference vegetation index-based vegetation indexes (NDVI-based VIs) between pre-tillering and panicle differentiation stages. The slope of the quadratic polynomial regression model tended to be alleviated in the period in which the panicle initiation stage should occur. The results indicated that the trend of the NDVI-based VIs was correlated with panicle initiation. NDVI-based VIs could be a useful indicator to remotely assess panicle initiation.

Highlights

Rice (Oryza sativa L.) is one of the most important staple foods for more than half of the world population
Rice yield is known to be increased by the nitrogen topdressing at the panicle initiation (PI) stage that is the beginning of the reproductive stage [1,2,3]
The required Growing degree day (GDD) of group 2 for PI was approximately 80◦C lower than group 4. These biases indicated that the DAT and GDD are both largely affected by weather variability

Summary

Introduction

Rice (Oryza sativa L.) is one of the most important staple foods for more than half of the world population. When 30% of the main culms have panicles 2 mm or longer, it is considered as the panicle differentiation (PD) stage [3] that is late for nitrogen topdressing Those methods are inconvenient and inefficient for largescale estimation. Large-scale, and non-destructive approaches that help to monitor the plant growth stages, such as modified-calendar days and heat units, are potential candidates to be used for the precise estimation of PI. Growing degree day (GDD) is an excellent heat unit that has been widely applied in corn production [10] since it was first proposed to describe the timeline of biological development [7] These methods are rudimentary and are not able to distinguish the variability between fields. A non-destructive and high temporal resolution approach was expected to be established for PI assessment in this study

Field Experiment Design and Management

Determination of PI through Dissection

PI Determination through Manual Dissection

NDVI-Based VIs Selection

Conclusions