Mengzhen Kang

TL;DR: The model reproduced accurately the dynamics of plant growth, architecture and geometry of various annual and woody plants, enabling 3D visualization and was able to simulate the variability of leaf size on the plant and compensatory growth following pruning, as a result of internal competition for resources.

TL;DR: A new mathematical model for plant growth, GreenLab, is presented, based on a powerful factorization of the plant structure, which finds applications to build trees very efficiently and to compute biomass production and distribution, in the context of functional structural models.

TL;DR: Based on the idea of substructure decomposition, the theoretical mean and variance of the number of organs in a plant structure from the model are computed recurrently by applying a compound law of generating functions.

TL;DR: The AutoRegressive Integrated Moving Average model, back propagation network method, and recurrent neural network method were tested to forecast the price of agricultural products in short term and long term and it is expected that the deep learning method represented by a neural network will become the mainstream method of agricultural product price forecasting.

TL;DR: This paper proposes an agricultural provenance system based on techniques of blockchain, which is featured by decentralization, collective maintenance, consensus trust and reliable data, in order to solve the trust crisis in product supply chain.