Janani Malaisamy^*, Jebakumar Rethnaraj

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1845-1862, 2023, DOI:10.32604/iasc.2023.034280

Abstract Prediction of the nutrient deficiency range and control of it through application of an appropriate amount of fertiliser at all growth stages is critical to achieving a qualitative and quantitative yield. Distributing fertiliser in optimum amounts will protect the environment’s condition and human health risks. Early identification also prevents the disease’s occurrence in groundnut crops. A convolutional neural network is a computer vision algorithm that can be replaced in the place of human experts and laboratory methods to predict groundnut crop nitrogen nutrient deficiency through image features. Since chlorophyll and nitrogen are proportionate to one another, the Smart Nutrient Deficiency… More >

Hans Christian Correa-Aguado^1,3, Gloria Viviana Cerrillo-Rojas¹, Alejandro Rocha-Uribe², Ruth Elena Soria-Guerra², José Francisco Morales-Domínguez^1,*

Phyton-International Journal of Experimental Botany, Vol.90, No.2, pp. 515-531, 2021, DOI:10.32604/phyton.2021.013619

Abstract The need for renewable energy sources makes microalgae an essential feedstock for biofuels production. The molecular aspects and the response to nitrogen (N)-limited conditions with a phytohormone stimulus in microalgae have been slightly explored. In this work, Scenedesmus obliquus was used as a study model to analyze the effect of benzyl amino purine (BAP) and gibberellic acid (GA) coupled to nitrogen limitation on cell growth, biomass and fatty acids. The selected 10^-5 M BAP increased the biomass by 1.44-fold, and 10^-6 M GA by 1.35-fold. The total lipids also increased by 2.8 and 1.11-fold, respectively. The 10^-5 M BAP and… More >