Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Plant Phenotyping consists in characterizing their morphometric pa-rameters which allows correlating them to genotype expression, modulated by their environment. Particularly, nutrition and environment of plants impact significantly roots and symbiotic nodules growths. Under conditions of low mineral nitrogen in soil, legumes have the ability to fix atmospheric nitrogen symbiotically in nodules which are organs formed on the roots of the host plant. The observation of nodules and the evaluation of their characteristics are quite difficult manually, and commercial software provide currently time consuming and no accurate results.  proposes a fast and automated image processing technique using the skeletonization technique to determine very accurately nodule parameters, such as their number, location and size on the primary root. The results obtained will be used for the determination of other root parameters including dynamic follow of root architecture.
['Simeng Han', 'Frédéric Cointault', 'Christophe Salon', 'Jean-Claude Simon']
I am writing a research paper on a idea Automatic Detection of Nodules in Legumes by Imagery in a Phenotyping Context
[{"from": "human", "value": "I am writing a research paper on a idea Automatic Detection of Nodules in Legumes by Imagery in a Phenotyping Context"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Plant Phenotyping consists in characterizing their morphometric pa-rameters which allows correlating them to genotype expression, modulated by their environment. Particularly, nutrition and environment of plants impact significantly roots and symbiotic nodules growths. Under conditions of low mineral nitrogen in soil, legumes have the ability to fix atmospheric nitrogen symbiotically in nodules which are organs formed on the roots of the host plant. The observation of nodules and the evaluation of their characteristics are quite difficult manually, and commercial software provide currently time consuming and no accurate results.  proposes a fast and automated image processing technique using the skeletonization technique to determine very accurately nodule parameters, such as their number, location and size on the primary root. The results obtained will be used for the determination of other root parameters including dynamic follow of root architecture."}]