A team of Chinese researchers has developed a cost-effective, high-throughput imaging method to accurately estimate cotton plant height and above-ground biomass.
- This approach using a high-definition digital camera and Canopeo software has been validated across various cotton genotypes and irrigation levels, and offers a non-destructive, accessible tool for monitoring crop growth, potentially enhancing intelligent farmland management.
- Its ease of use will allow ordinary farmers and researchers to efficiently assess crop phenotypes, paving the way for broader applications in crop monitoring and precision agriculture.
- The research article published in Technology in Agronomy investigates the feasibility of using imaging technology to efficiently estimate cotton plant height (PH) and above-ground biomass (AGB).
The Context: Traditional phenotypic analysis methods are labour-intensive, time-consuming, and inefficient, making them unsuitable for large-scale farmland.
- While recent advancements in high-throughput phenotypic analysis, particularly digital image analysis, have improved efficiency, current techniques often focus on nutritional diagnostics rather than comprehensive crop monitoring. Cotton is an important cash crop that is widely cultivated worldwide.
- However, the feasibility of efficient and non-destructive crop phenotypic monitoring technologies for estimating cotton plant height and above-ground biomass has not yet been determined.
Materials and Methods: The study utilised eighty cotton varieties from the cotton-growing areas of the Yellow and Yangtze River basins.
- It was conducted in the drought shed in the Qingyuan Experimental Field at Hebei Agricultural University (Baoding City, Hebei Province, China) from April to July 2021.
- The drought sheds automatically close and open during the rainy and sunny seasons, respectively. Full-grain and uniform seeds were selected for sowing in soil and subjected to different treatments.
- There were 90,000 plants/hm2 in the field with an equal row spacing of 50 cm. The field management was similar to that applied during the conventional cultivation of high-yielding cotton fields.
- A water meter was used to measure and record the actual amount of irrigation. The seeds were artificially sown on 20 April 2021, and harvested on 5 November 2021.
- The data were collected at the initial flowering stage of cotton, and the plants with consistent growth were selected for index measurement. All the indices were measured at 09:00. Five representative plants were measured from each treatment, and their average values were used as the final results.
The Software: Canopeo is a cost-free image analytical software that can be used as a mobile application on Android or IOS devices.
- It was developed in the MATLAB programming language and uses the red, green, and blue (RGB) color values.
- Canopeo-based image analysis is an efficient, simple, accurate, cost-effective, and non-destructive method that enables the reliable and quick large-scale measurement of crop canopies and other phenotypic features.
- The method involves photographing green crops using smartphones or digital cameras and generating image pixel percentages to compare the correlations between the real-time and estimated PGC (percentages of green colour) of the PH and AGB.
- If the correlation is very high, the PGC can represent the PH and AGB and serve as a substitute method to evaluate dry crop matter and PH.
- Notably, high-definition digital cameras are inexpensive and offer high image resolution and simple data processing steps, making them the cost-effective methods of choice for data acquisition.
