Models for estimation growth, yield and nutrients content of processing tomato
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/147106 |
Resumo: | In this work were discussed processes related to development and growth of processing tomato. The experiments were conducted in the years 2013 and 2014 in three different areas in the city of Guaíra-SP. In chapter 1 the objective was to calibrate and test the CROPGRO-Tomato model with data of five field experiments with processing tomato under different phosphorus concentrations in the soil. The treatments of experiments for calibration were for the area 1: 0, 150, 300, 450, 600 and 750 kg ha-1 P2O5 and for the areas two and three: 0, 200, 400, 600, 800 and 1000 kg ha-1 P2O5, in randomized block design with four replications. The experiments for testing the model 450 kg ha-1 P2O5 was applied. In each 15 days after transplanting (DAT) plants were collected for measuring biomass and leaf area. At the end of crop cycle plants were collected for evaluation of production. All data collected were used for calibration and testing of CROPGRO-Tomato model. The model was accurate (average d index = 0.91, average RRMSE = 0.24) to simulate response of processing tomato to different soil P concentrations. The objective of Experiment 2 was to estimate the leaf area index (LAI) of processing tomato using data obtained by destructive and non-destructive methods, meteorological data and number of leaves (NL). For Experiment 2 the methods of measuring leaf area were Li-Cor (destructive), ImageJ and Canopeo (digital images). Also for estimation of LAI it were used sum of degree-days (ΣDD), global radiation (Qg) and number of leaves (NL). Photographs were taken at random, in two different areas at 15, 30, 45, 60, 75, 90, 105, DAT 120 using a 1m2 square frame placed over the plants. Photographs were taken in 24 different points, in each point it was collected one plant for leaf area measurement using Li-Cor and leaves counting. LAI estimation using Canopeo and NL were the most accurated with RMSE=0.4, es= 0.7, R2= 0.93 and RMSE = 0.2, se = 0.7 and R2 = 0.92, respectively. It is possible to estimate LAI of processing tomato using non-destructive and low cost methods. The objective of Experiment 3 was to characterize the accumulation of biomass and nutrients in processing tomatoes grown in high and low fertility soils. Plants were collected in four replications (3 plants per replication), every ten days (30 to 120 DAT). After cleaned and dried the material was used to determine nutrient content and biomass. Data were adjusted to polynomial regressions. The decreasing order of nutrient accumulation was K, N, Ca, P, Mg, S, Fe, Cu, Mn, Zn in HF; and K, N, Ca, P, Mg, S, Fe, Mn, Cu, Zn in LF. Tomato plants grown in HF and LF soils, however fertilized in the same manner, have similar potential of biomass producing. |
id |
UNSP_bbd4bbc6b7475479c189e48a60f334b3 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/147106 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Models for estimation growth, yield and nutrients content of processing tomatoModelos para estimar crescimento, produtividade e teores de nutrientes do tomate industrialCrop modelingPlant nutritionBiomassLeaf area indexIn this work were discussed processes related to development and growth of processing tomato. The experiments were conducted in the years 2013 and 2014 in three different areas in the city of Guaíra-SP. In chapter 1 the objective was to calibrate and test the CROPGRO-Tomato model with data of five field experiments with processing tomato under different phosphorus concentrations in the soil. The treatments of experiments for calibration were for the area 1: 0, 150, 300, 450, 600 and 750 kg ha-1 P2O5 and for the areas two and three: 0, 200, 400, 600, 800 and 1000 kg ha-1 P2O5, in randomized block design with four replications. The experiments for testing the model 450 kg ha-1 P2O5 was applied. In each 15 days after transplanting (DAT) plants were collected for measuring biomass and leaf area. At the end of crop cycle plants were collected for evaluation of production. All data collected were used for calibration and testing of CROPGRO-Tomato model. The model was accurate (average d index = 0.91, average RRMSE = 0.24) to simulate response of processing tomato to different soil P concentrations. The objective of Experiment 2 was to estimate the leaf area index (LAI) of processing tomato using data obtained by destructive and non-destructive methods, meteorological data and number of leaves (NL). For Experiment 2 the methods of measuring leaf area were Li-Cor (destructive), ImageJ and Canopeo (digital images). Also for estimation of LAI it were used sum of degree-days (ΣDD), global radiation (Qg) and number of leaves (NL). Photographs were taken at random, in two different areas at 15, 30, 45, 60, 75, 90, 105, DAT 120 using a 1m2 square frame placed over the plants. Photographs were taken in 24 different points, in each point it was collected one plant for leaf area measurement using Li-Cor and leaves counting. LAI estimation using Canopeo and NL were the most accurated with RMSE=0.4, es= 0.7, R2= 0.93 and RMSE = 0.2, se = 0.7 and R2 = 0.92, respectively. It is possible to estimate LAI of processing tomato using non-destructive and low cost methods. The objective of Experiment 3 was to characterize the accumulation of biomass and nutrients in processing tomatoes grown in high and low fertility soils. Plants were collected in four replications (3 plants per replication), every ten days (30 to 120 DAT). After cleaned and dried the material was used to determine nutrient content and biomass. Data were adjusted to polynomial regressions. The decreasing order of nutrient accumulation was K, N, Ca, P, Mg, S, Fe, Cu, Mn, Zn in HF; and K, N, Ca, P, Mg, S, Fe, Mn, Cu, Zn in LF. Tomato plants grown in HF and LF soils, however fertilized in the same manner, have similar potential of biomass producing.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Estadual Paulista (Unesp)Cecílio Filho, Arthur Bernardes [UNESP]Rolim, Glauco de Souza [UNESP]Universidade Estadual Paulista (Unesp)Silva, Juliana Aparecida dos Santos da [UNESP]2017-01-10T17:35:00Z2017-01-10T17:35:00Z2016-11-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdfhttp://hdl.handle.net/11449/14710600087814633004102001P429381556851145927838769590779294enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESP2024-06-05T15:17:16Zoai:repositorio.unesp.br:11449/147106Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:50:31.103018Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Models for estimation growth, yield and nutrients content of processing tomato Modelos para estimar crescimento, produtividade e teores de nutrientes do tomate industrial |
title |
Models for estimation growth, yield and nutrients content of processing tomato |
spellingShingle |
Models for estimation growth, yield and nutrients content of processing tomato Silva, Juliana Aparecida dos Santos da [UNESP] Crop modeling Plant nutrition Biomass Leaf area index |
title_short |
Models for estimation growth, yield and nutrients content of processing tomato |
title_full |
Models for estimation growth, yield and nutrients content of processing tomato |
title_fullStr |
Models for estimation growth, yield and nutrients content of processing tomato |
title_full_unstemmed |
Models for estimation growth, yield and nutrients content of processing tomato |
title_sort |
Models for estimation growth, yield and nutrients content of processing tomato |
author |
Silva, Juliana Aparecida dos Santos da [UNESP] |
author_facet |
Silva, Juliana Aparecida dos Santos da [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Cecílio Filho, Arthur Bernardes [UNESP] Rolim, Glauco de Souza [UNESP] Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Silva, Juliana Aparecida dos Santos da [UNESP] |
dc.subject.por.fl_str_mv |
Crop modeling Plant nutrition Biomass Leaf area index |
topic |
Crop modeling Plant nutrition Biomass Leaf area index |
description |
In this work were discussed processes related to development and growth of processing tomato. The experiments were conducted in the years 2013 and 2014 in three different areas in the city of Guaíra-SP. In chapter 1 the objective was to calibrate and test the CROPGRO-Tomato model with data of five field experiments with processing tomato under different phosphorus concentrations in the soil. The treatments of experiments for calibration were for the area 1: 0, 150, 300, 450, 600 and 750 kg ha-1 P2O5 and for the areas two and three: 0, 200, 400, 600, 800 and 1000 kg ha-1 P2O5, in randomized block design with four replications. The experiments for testing the model 450 kg ha-1 P2O5 was applied. In each 15 days after transplanting (DAT) plants were collected for measuring biomass and leaf area. At the end of crop cycle plants were collected for evaluation of production. All data collected were used for calibration and testing of CROPGRO-Tomato model. The model was accurate (average d index = 0.91, average RRMSE = 0.24) to simulate response of processing tomato to different soil P concentrations. The objective of Experiment 2 was to estimate the leaf area index (LAI) of processing tomato using data obtained by destructive and non-destructive methods, meteorological data and number of leaves (NL). For Experiment 2 the methods of measuring leaf area were Li-Cor (destructive), ImageJ and Canopeo (digital images). Also for estimation of LAI it were used sum of degree-days (ΣDD), global radiation (Qg) and number of leaves (NL). Photographs were taken at random, in two different areas at 15, 30, 45, 60, 75, 90, 105, DAT 120 using a 1m2 square frame placed over the plants. Photographs were taken in 24 different points, in each point it was collected one plant for leaf area measurement using Li-Cor and leaves counting. LAI estimation using Canopeo and NL were the most accurated with RMSE=0.4, es= 0.7, R2= 0.93 and RMSE = 0.2, se = 0.7 and R2 = 0.92, respectively. It is possible to estimate LAI of processing tomato using non-destructive and low cost methods. The objective of Experiment 3 was to characterize the accumulation of biomass and nutrients in processing tomatoes grown in high and low fertility soils. Plants were collected in four replications (3 plants per replication), every ten days (30 to 120 DAT). After cleaned and dried the material was used to determine nutrient content and biomass. Data were adjusted to polynomial regressions. The decreasing order of nutrient accumulation was K, N, Ca, P, Mg, S, Fe, Cu, Mn, Zn in HF; and K, N, Ca, P, Mg, S, Fe, Mn, Cu, Zn in LF. Tomato plants grown in HF and LF soils, however fertilized in the same manner, have similar potential of biomass producing. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-11-04 2017-01-10T17:35:00Z 2017-01-10T17:35:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11449/147106 000878146 33004102001P4 2938155685114592 7838769590779294 |
url |
http://hdl.handle.net/11449/147106 |
identifier_str_mv |
000878146 33004102001P4 2938155685114592 7838769590779294 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129127361806336 |