Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato
This study aims to evaluate the behavior of seed longevity in soybean, maize, and tomato stored under controlled conditions using Logistic and Boltzmann sigmoidal models. Additionally, it seeks to determine the performance of these models in predicting <inline-formula><math xmlns="http...
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MDPI AG
2024-12-01
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| Series: | AgriEngineering |
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| author | Felipe Souza Carvalho Brunna Rithielly Rezende Amanda Rithieli Pereira dos Santos Maria Márcia Pereira Sartori |
| author_facet | Felipe Souza Carvalho Brunna Rithielly Rezende Amanda Rithieli Pereira dos Santos Maria Márcia Pereira Sartori |
| author_sort | Felipe Souza Carvalho |
| collection | DOAJ |
| description | This study aims to evaluate the behavior of seed longevity in soybean, maize, and tomato stored under controlled conditions using Logistic and Boltzmann sigmoidal models. Additionally, it seeks to determine the performance of these models in predicting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula>. The models were fitted to the experimental longevity data, and their performance in predicting the percentiles was evaluated. The Logistic model showed better performance in predicting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 50%), <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 85%), and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 25%), estimating the parameters more frequently within the experimental range (obtained from the initial viability data). The results of this study suggest that some cultivars exhibited different patterns in deterioration rates, with some showing abrupt declines in viability, highlighting differences in the speed and nature of seed deterioration. The Logistic model proved to be superior, with an accuracy of 83% in estimating the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> percentiles, while the Boltzmann model achieved an accuracy of 54%. The tomato cultivar Gaucho showed the greatest loss in germination, reaching <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> quickly, while the soybean cultivar M 7119 IPRO and maize cultivar MAM06 maintained high germination for a longer period. These findings emphasize the importance of using viability percentiles to optimize storage practices, minimize economic losses, and prevent genetic erosion in conservation programs. Modeling seed longevity using sigmoidal models can significantly contribute to determining various viability percentiles, supporting storage practices and providing valuable insights for strategic decision-making in seed management, proving useful in both commercial and species conservation contexts. |
| format | Article |
| id | doaj-art-2485c1573dac41c2b50b5e04138e608a |
| institution | Kabale University |
| issn | 2624-7402 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj-art-2485c1573dac41c2b50b5e04138e608a2025-01-24T13:16:12ZengMDPI AGAgriEngineering2624-74022024-12-0171510.3390/agriengineering7010005Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and TomatoFelipe Souza Carvalho0Brunna Rithielly Rezende1Amanda Rithieli Pereira dos Santos2Maria Márcia Pereira Sartori3Department of Crop Science, College of Agricultural Sciences, São Paulo State University, Botucatu 18618687, SP, BrazilDepartment of Crop Science, College of Agricultural Sciences, São Paulo State University, Botucatu 18618687, SP, BrazilDepartment of Agricultural Engineering, Federal Institute of Education, Science, and Technology of Goiás, Urutaí 75790000, GO, BrazilDepartment of Crop Science, College of Agricultural Sciences, São Paulo State University, Botucatu 18618687, SP, BrazilThis study aims to evaluate the behavior of seed longevity in soybean, maize, and tomato stored under controlled conditions using Logistic and Boltzmann sigmoidal models. Additionally, it seeks to determine the performance of these models in predicting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula>. The models were fitted to the experimental longevity data, and their performance in predicting the percentiles was evaluated. The Logistic model showed better performance in predicting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 50%), <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 85%), and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> (time for viability to drop to 25%), estimating the parameters more frequently within the experimental range (obtained from the initial viability data). The results of this study suggest that some cultivars exhibited different patterns in deterioration rates, with some showing abrupt declines in viability, highlighting differences in the speed and nature of seed deterioration. The Logistic model proved to be superior, with an accuracy of 83% in estimating the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>85</mn></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> percentiles, while the Boltzmann model achieved an accuracy of 54%. The tomato cultivar Gaucho showed the greatest loss in germination, reaching <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>P</mi></mrow><mrow><mn>25</mn></mrow></msub></mrow></semantics></math></inline-formula> quickly, while the soybean cultivar M 7119 IPRO and maize cultivar MAM06 maintained high germination for a longer period. These findings emphasize the importance of using viability percentiles to optimize storage practices, minimize economic losses, and prevent genetic erosion in conservation programs. Modeling seed longevity using sigmoidal models can significantly contribute to determining various viability percentiles, supporting storage practices and providing valuable insights for strategic decision-making in seed management, proving useful in both commercial and species conservation contexts.https://www.mdpi.com/2624-7402/7/1/5logistic modelBoltzmann modelSigmoid functions<i>P</i><sub>50</sub><i>P</i><sub>85</sub><i>P</i><sub>25</sub> |
| spellingShingle | Felipe Souza Carvalho Brunna Rithielly Rezende Amanda Rithieli Pereira dos Santos Maria Márcia Pereira Sartori Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato AgriEngineering logistic model Boltzmann model Sigmoid functions <i>P</i><sub>50</sub> <i>P</i><sub>85</sub> <i>P</i><sub>25</sub> |
| title | Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato |
| title_full | Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato |
| title_fullStr | Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato |
| title_full_unstemmed | Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato |
| title_short | Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato |
| title_sort | modeling seed longevity and percentile prediction a sigmoidal function approach in soybean maize and tomato |
| topic | logistic model Boltzmann model Sigmoid functions <i>P</i><sub>50</sub> <i>P</i><sub>85</sub> <i>P</i><sub>25</sub> |
| url | https://www.mdpi.com/2624-7402/7/1/5 |
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