App for seed longevity analysis (Pi/ longevity for any percentage of viable seeds) and survival analysis: a methodology for agricultural seed performance aferition

• Grant number: 18/25698-4
• Support Opportunities: Regular Research Grants
• Start date: April 01, 2019
• End date: June 30, 2021
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Maria Márcia Pereira Sartori
• Grantee: Maria Márcia Pereira Sartori
• Host Institution: Faculdade de Ciências Agronômicas (FCA). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
• City of the host institution: Botucatu
• Associated researchers: Edvaldo Aparecido Amaral da Silva

Abstract

The half-life index of agricultural seed longevity, P50, can become an important tool for commercial seed management. The parameter also allows the evaluation of storage in seed banks, whose main purpose is the preservation of species. The P50 modeling is traditionally performed by setting the Probit function, however, studies show that this model has limitations, due to non-normality of residues. This fact culminated in the search for more robust models (Logit) or certain modifications in the models, which were object of study with application to different species and / or conditions, resulting in improvements in the determination of P50. However, in view of the observed and obtained in the literature can be inferred that it would be necessary to use several models to predict the half-life in seeds, as well as to measure extreme values, as example P25 or P75, depending on the different conditions, or species, which would be very difficult and would require great modeling knowledge. This project will, therefore, evaluate the adjustment of models in the conditions of non-normal distribution, Cauchy and Power in the prediction of P50 or any percentage studied, for soybean, corn and bean seeds, and proposes an application that facilitates the execution of the calculations, finding the best model for each condition. A second line of study, parallel to this evaluation, will address the use of survival analysis statistics as a tool for joint evaluation of seed groups. Survival analysis has a complementary role in the exploratory analysis of survival data. This would allow greater inferences about the phenomenon. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DE FARIA, RUTE QUELVIA; DOS SANTOS, AMANDA R. P.; VASCO, LAINARA C. P. DOS SANTOS; GARIEPY, YVAN; SARTORI, MARIA M. P.; RAGHAVAN, VIJAYA. Quality of Soybean Seeds after Microwave Drying. APPLIED SCIENCES-BASEL, v. 13, n. 14, p. 14-pg., 2023-07-01. (18/25698-4)

AMORIM, DEOCLECIO JARDIM; PEREIRA DOS SANTOS, AMANDA RITHIELI; DA PIEDADE, GABRIELA NUNES; DE FARIA, RUTE QUELVIA; AMARAL DA SILVA, EDVALDO APARECIDO; PEREIRA SARTORI, MARIA MARCIA. The Use of the Generalized Linear Model to Assess the Speed and Uniformity of Germination of Corn and Soybean Seeds. AGRONOMY-BASEL, v. 11, n. 3, MAR 2021. (18/25698-4)

CANTAO, RENATO FERNANDES; RIBEIRO-OLIVEIRA, JOAO PAULO; DA SILVA, EDVALDO A. AMARAL; DOS SANTOS, AMANDA RITHIELI; DE FARIA, RUTE QUELVIA; SARTORI, MARIA MARCIA PEREIRA. POMONA: a multiplatform software for modeling seed physiology. FRONTIERS IN PLANT SCIENCE, v. 14, p. 13-pg., 2023-07-06. (18/25698-4, 17/50211-9, 16/13126-0)

DE FARIA, RUTE Q.; DOS SANTOS, AMANDA R. P.; BATISTA, THIAGO B.; GARIEPY, YVAN; DA SILVA, EDVALDO A. A.; SARTORI, MARIA M. P.; RAGHAVAN, VIJAYA. The Effect of Magneto-Priming on the Physiological Quality of Soybean Seeds. PLANTS-BASEL, v. 12, n. 7, p. 20-pg., 2023-04-01. (18/25698-4)