A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality

Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Bo Wen [verfasserIn] Ruiyang Li [verfasserIn] Xue Zhao [verfasserIn] Shuang Ren [verfasserIn] Yali Chang [verfasserIn] Kexin Zhang [verfasserIn] Shan Wang [verfasserIn] Guiyi Guo [verfasserIn] Xujun Zhu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model

Übergeordnetes Werk:	In: Agriculture - MDPI AG, 2012, 11(2021), 12, p 1225
Übergeordnetes Werk:	volume:11 ; year:2021 ; number:12, p 1225

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/agriculture11121225

Katalog-ID:	DOAJ074415077

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520			\|a Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes.
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allfields	10.3390/agriculture11121225 doi (DE-627)DOAJ074415077 (DE-599)DOAJ284100e99b3e4ba5815505ed72717f5f DE-627 ger DE-627 rakwb eng S1-972 Bo Wen verfasserin aut A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General) Ruiyang Li verfasserin aut Xue Zhao verfasserin aut Shuang Ren verfasserin aut Yali Chang verfasserin aut Kexin Zhang verfasserin aut Shan Wang verfasserin aut Guiyi Guo verfasserin aut Xujun Zhu verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 12, p 1225 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:12, p 1225 https://doi.org/10.3390/agriculture11121225 kostenfrei https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f kostenfrei https://www.mdpi.com/2077-0472/11/12/1225 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 12, p 1225
spelling	10.3390/agriculture11121225 doi (DE-627)DOAJ074415077 (DE-599)DOAJ284100e99b3e4ba5815505ed72717f5f DE-627 ger DE-627 rakwb eng S1-972 Bo Wen verfasserin aut A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General) Ruiyang Li verfasserin aut Xue Zhao verfasserin aut Shuang Ren verfasserin aut Yali Chang verfasserin aut Kexin Zhang verfasserin aut Shan Wang verfasserin aut Guiyi Guo verfasserin aut Xujun Zhu verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 12, p 1225 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:12, p 1225 https://doi.org/10.3390/agriculture11121225 kostenfrei https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f kostenfrei https://www.mdpi.com/2077-0472/11/12/1225 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 12, p 1225
allfields_unstemmed	10.3390/agriculture11121225 doi (DE-627)DOAJ074415077 (DE-599)DOAJ284100e99b3e4ba5815505ed72717f5f DE-627 ger DE-627 rakwb eng S1-972 Bo Wen verfasserin aut A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General) Ruiyang Li verfasserin aut Xue Zhao verfasserin aut Shuang Ren verfasserin aut Yali Chang verfasserin aut Kexin Zhang verfasserin aut Shan Wang verfasserin aut Guiyi Guo verfasserin aut Xujun Zhu verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 12, p 1225 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:12, p 1225 https://doi.org/10.3390/agriculture11121225 kostenfrei https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f kostenfrei https://www.mdpi.com/2077-0472/11/12/1225 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 12, p 1225
allfieldsGer	10.3390/agriculture11121225 doi (DE-627)DOAJ074415077 (DE-599)DOAJ284100e99b3e4ba5815505ed72717f5f DE-627 ger DE-627 rakwb eng S1-972 Bo Wen verfasserin aut A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General) Ruiyang Li verfasserin aut Xue Zhao verfasserin aut Shuang Ren verfasserin aut Yali Chang verfasserin aut Kexin Zhang verfasserin aut Shan Wang verfasserin aut Guiyi Guo verfasserin aut Xujun Zhu verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 12, p 1225 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:12, p 1225 https://doi.org/10.3390/agriculture11121225 kostenfrei https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f kostenfrei https://www.mdpi.com/2077-0472/11/12/1225 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 12, p 1225
allfieldsSound	10.3390/agriculture11121225 doi (DE-627)DOAJ074415077 (DE-599)DOAJ284100e99b3e4ba5815505ed72717f5f DE-627 ger DE-627 rakwb eng S1-972 Bo Wen verfasserin aut A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes. soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General) Ruiyang Li verfasserin aut Xue Zhao verfasserin aut Shuang Ren verfasserin aut Yali Chang verfasserin aut Kexin Zhang verfasserin aut Shan Wang verfasserin aut Guiyi Guo verfasserin aut Xujun Zhu verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 12, p 1225 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:12, p 1225 https://doi.org/10.3390/agriculture11121225 kostenfrei https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f kostenfrei https://www.mdpi.com/2077-0472/11/12/1225 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 12, p 1225
language	English
source	In Agriculture 11(2021), 12, p 1225 volume:11 year:2021 number:12, p 1225
sourceStr	In Agriculture 11(2021), 12, p 1225 volume:11 year:2021 number:12, p 1225
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model Agriculture (General)
isfreeaccess_bool	true
container_title	Agriculture
authorswithroles_txt_mv	Bo Wen @@aut@@ Ruiyang Li @@aut@@ Xue Zhao @@aut@@ Shuang Ren @@aut@@ Yali Chang @@aut@@ Kexin Zhang @@aut@@ Shan Wang @@aut@@ Guiyi Guo @@aut@@ Xujun Zhu @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	686948173
id	DOAJ074415077
language_de	englisch
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This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. 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callnumber-first	S - Agriculture
author	Bo Wen
spellingShingle	Bo Wen misc S1-972 misc soil pH misc soil nutrients misc main chemical components in tea misc spatial variation characteristic misc quadratic regression model misc Agriculture (General) A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality
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topic_title	S1-972 A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality soil pH soil nutrients main chemical components in tea spatial variation characteristic quadratic regression model
topic	misc S1-972 misc soil pH misc soil nutrients misc main chemical components in tea misc spatial variation characteristic misc quadratic regression model misc Agriculture (General)
topic_unstemmed	misc S1-972 misc soil pH misc soil nutrients misc main chemical components in tea misc spatial variation characteristic misc quadratic regression model misc Agriculture (General)
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title	A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality
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title_full	A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality
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author_browse	Bo Wen Ruiyang Li Xue Zhao Shuang Ren Yali Chang Kexin Zhang Shan Wang Guiyi Guo Xujun Zhu
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title_sort	quadratic regression model to quantify plantation soil factors that affect tea quality
callnumber	S1-972
title_auth	A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality
abstract	Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes.
abstractGer	Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes.
abstract_unstemmed	Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting the quality of green tea. This study aimed to relate key biochemical substances in tea to soil nutrient composition and the effectiveness of fertilization. Seventy tea samples and their corresponding plantation soil were randomly collected from Xinyang City, China. The catechins, free amino acids, and caffeine in tea were examined, as well as the soil pH, nitrate (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<O</mi<</mrow<<mn<3</mn<<mo<-</mo<</msubsup<</semantics<</math<</inline-formula<-N), ammonium (<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM). The ordinary kriging was employed to visualize the spatial variation characteristic by ArcGIS. A quadratic regression model was used to analyze the effects of the soil environment on the tea. The results showed that the soil pH of the study area was suitable for cultivating tea plants. The relationship between soil pH and tea polyphenols and catechins presented the U-shape curve, whereas the soil pH and <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msubsup<<mrow<<mi mathvariant="normal"<N</mi<<mi mathvariant="normal"<H</mi<</mrow<<mn<4</mn<<mo<+</mo<</msubsup<</semantics<</math<</inline-formula<-N and the free amino acids, the soil pH, and caffeine presented the inverted U-shape curve. Soil management measures could be implemented to control the soil environment for improving the tea quality. The combination of the macro metrological model with individual experimentation could help to analyze the detailed influence mechanisms of environmental factors on plant physiological processes.
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title_short	A Quadratic Regression Model to Quantify Plantation Soil Factors That Affect Tea Quality
url	https://doi.org/10.3390/agriculture11121225 https://doaj.org/article/284100e99b3e4ba5815505ed72717f5f https://www.mdpi.com/2077-0472/11/12/1225 https://doaj.org/toc/2077-0472
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author2	Ruiyang Li Xue Zhao Shuang Ren Yali Chang Kexin Zhang Shan Wang Guiyi Guo Xujun Zhu
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