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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title>Frontiers in Plant Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Plant Sci.</abbrev-journal-title>
<issn pub-type="epub">1664-462X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpls.2023.1148616</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Plant Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Optimizing drip fertigation at different periods to improve yield, volatile compounds and cup quality of Arabica coffee</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Rongmei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheng</surname>
<given-names>Jinhuan</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Liu</surname>
<given-names>Xiaogang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1710014"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Zhihui</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2131154"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Huiyong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Guo</surname>
<given-names>Jinjin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Haidong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Cui</surname>
<given-names>Ningbo</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2131215"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Lu</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology</institution>, <addr-line>Kunming</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Tropical and Subtropical Economic Crops Institute, Yunnan Academy of Agricultural Sciences</institution>, <addr-line>Baoshan</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>State Key Laboratory of Hydraulics and Mountain River Engineering and College of Water Resource and Hydropower, Sichuan University</institution>, <addr-line>Chengdu, Sichuan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Yang Gao, Chinese Academy of Agricultural Sciences, China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Miroslava Rakocevic, State University of Northern Rio de Janeiro, Brazil; Ioannis S. Minas, Colorado State University, United States; Anzhen Qin, Chinese Academy of Agricultural Sciences, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Xiaogang Liu, <email xlink:href="mailto:liuxiaogangjy@126.com">liuxiaogangjy@126.com</email>; Ningbo Cui, <email xlink:href="mailto:cuiningbo@126.com">cuiningbo@126.com</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>06</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1148616</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>01</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>31</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Li, Cheng, Liu, Wang, Li, Guo, Wang, Cui and Zhao</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Li, Cheng, Liu, Wang, Li, Guo, Wang, Cui and Zhao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>How to improve and regulate coffee bean yield and quality through split fertilization in the whole life cycle of coffee is still unclear and deserves further study. A field experiment of 5-year-old Arabica coffee trees was conducted for 2 consecutive years from 2020 to 2022. The fertilizer (750&#xa0;kg ha<sup>-1</sup> year<sup>-1</sup>, N-P<sub>2</sub>O<sub>5</sub>-K<sub>2</sub>O:20%-20%-20%) was split in three times at early flowering (FL), the berry expansion (BE), and the berry ripening (BR). Taking equal fertilization throughout the growth cycle (FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>) as the control check, variable fertilizations including FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>, and FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>. Leaf net photosynthetic rate (<italic>A</italic>
<sub>net</sub>), stomatal conductance (<italic>g</italic>
<sub>s</sub>), transpiration rate (<italic>T</italic>
<sub>r</sub>), leaf water use efficiency (LWUE), carboxylation efficiency (CE), partial factor productivity of fertilizer (PFP), bean yield, crop water use efficiency (WUE), bean nutrients, volatile compounds and cup quality, and the correlation of nutrients with volatile compounds and cup quality was evaluated. FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> had the maximum <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub>, followed by FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>. The highest dry bean yield and WUE were obtained from FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, which increased by 8.86% and 8.47% compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> in two-year average. The ash, total sugar, fat, protein, caffeine and chlorogenic acid in FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> were 6.47%, 9.48%, 3.60%, 14.02%, 4.85% and 15.42% higher than FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>. Cluster analysis indicated FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> and FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> under medium roasted degree increased pyrazines, esters, ketones and furans, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> under dark roasted degree increased ketones and furans. The aroma, flavor, acidity and overall score of medium roasted coffee were higher than dark roasted coffee, while the body score of dark roasted coffee was higher than medium roasted coffee. The nutrient contents were correlated with the volatile compounds and cup quality. TOPSIS indicated that FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> was the optimal fertilization mode in the xerothermic regions. The obtained optimum fertilization mode can provide a scientific basis for coffee fertilization optimization and management.</p>
</abstract>
<kwd-group>
<kwd>Arabica coffee</kwd>
<kwd>optimized fertilization</kwd>
<kwd>bean nutrients</kwd>
<kwd>volatile compounds</kwd>
<kwd>cup quality</kwd>
</kwd-group>
<contract-num rid="cn001">51979133, 51922072, 52279041</contract-num>
<contract-num rid="cn002">2022YFQ0082</contract-num>
<contract-sponsor id="cn001">National Natural Science Foundation of China<named-content content-type="fundref-id">10.13039/501100001809</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Sichuan Province Science and Technology Support Program<named-content content-type="fundref-id">10.13039/100012542</named-content>
</contract-sponsor>
<counts>
<fig-count count="9"/>
<table-count count="3"/>
<equation-count count="18"/>
<ref-count count="53"/>
<page-count count="16"/>
<word-count count="8697"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Plant Abiotic Stress</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The xerothermic regions of southwest China have sufficient light and heat, and a small annual temperature difference, which are very suitable for coffee cultivation. Both Arabica&#x2019;s planting area and yield account for more than 98% of the coffee planting area and yield owned by China (<xref ref-type="bibr" rid="B53">Zhang et&#xa0;al., 2020</xref>). However, the poor soil and the weak ability of soil to retain water and fertilizer limit the bean quality and yield. Moreover, local people adopt one-time fertilizer application in the rainy season, resulting in soil nutrient loss, low fertilizer use efficiency, low coffee yield and quality, and many environmental pollution problems (<xref ref-type="bibr" rid="B13">Dinesh et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B5">Bruno et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B6">Byrareddy et&#xa0;al., 2019</xref>).</p>
<p>Soil nutrient content determines crop growth and nutrient absorption and utilization by roots, which directly affects the yield and quality of crops (<xref ref-type="bibr" rid="B13">Dinesh et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B17">Fang et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B8">Cai et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B50">Ye et&#xa0;al., 2020</xref>). Nitrogen is an essential nutrient in coffee and the basis for plant growth and development. The yield loss is as high as 60% when nitrogen is not applied during the coffee reproductive stage (<xref ref-type="bibr" rid="B36">Salamanca-Jimenez et&#xa0;al., 2017</xref>). Studies found that appropriate nitrogen application is beneficial to coffee root growth and nutrient uptake, promotes chlorophyll synthesis, enhances net photosynthetic rate (<italic>A</italic>
<sub>net</sub>) and stomatal conductance (<italic>g</italic>
<sub>s</sub>), improves nitrogen use efficiency and increases yield of coffee beans (<xref ref-type="bibr" rid="B5">Bruno et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B36">Salamanca-Jimenez et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B52">Zhang et&#xa0;al., 2017</xref>). Potassium fertilizer is indispensable in the growth and maturation of coffee fruit as it can promote cell differentiation and protein and carbohydrate synthesis (<xref ref-type="bibr" rid="B37">Silva et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B1">Ali et&#xa0;al., 2021</xref>). Although, the effect of phosphate fertilizer on coffee growth, photosynthesis and yield is not as vital as nitrogen and potassium fertilizer, it plays an important role in promoting coffee growth and mineral nutrient absorption (<xref ref-type="bibr" rid="B7">Cai et&#xa0;al., 2007</xref>). <xref ref-type="bibr" rid="B52">Zhang et&#xa0;al. (2017)</xref> showed that the plant height, stem diameter growth rate, <italic>A</italic>
<sub>net</sub>, <italic>g</italic>
<sub>s</sub> and intrinsic water use efficiency of coffee saplings under medium and high fertilizer treatment were higher than those under low fertilizer treatment, and it was found that the growth indexes of coffee were superexcellent when the application of nitrogen, phosphorus and potassium was 1:0.8:0.5. <xref ref-type="bibr" rid="B26">Liu et&#xa0;al. (2016)</xref> found that fertilization could significantly increase the contents of caffeine, protein and chlorogenic acid in coffee beans. <xref ref-type="bibr" rid="B23">Kr&#xf3;l et&#xa0;al. (2020)</xref> found that coffee beans obtained by using organic fertilizer contain more bioactive substances (total phenols, phenolic acids, flavonoids, etc.), while the excessive use of chemical fertilizers resulted in more caffeine in coffee beans. The above studies indicated that fertilization could meet the nutrient requirements of coffee vegetative and reproductive growth, promote photosynthetic physiology, and improve yield and quality of beans (<xref ref-type="bibr" rid="B5">Bruno et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B26">Liu et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B23">Kr&#xf3;l et&#xa0;al., 2020</xref>). Previous studies have shown that fertilization can increase the abundance of volatile compounds in fruit, such as tomato, strawberry and apple (<xref ref-type="bibr" rid="B31">Raffo et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B12">Cvelbar Weber et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B29">Paskovi&#x107; et&#xa0;al., 2021</xref>). The effects of cultivars, planting area, altitude, climate, processing method and roasting degree, etc. on the volatile flavor of coffee have been reported (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B14">Dong et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B41">Tassew et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B51">Zakidou et&#xa0;al., 2021</xref>), but little is known about the effect of fertilization on volatile compounds.</p>
<p>One-time fertilization, excessive fertilization or unsystematic fertilization tend to reduce fertilizer use efficiency, leading to low productivity (<xref ref-type="bibr" rid="B49">Yan et&#xa0;al., 2021</xref>). <xref ref-type="bibr" rid="B4">Bruno et&#xa0;al. (2015)</xref> found that the most effective nitrogen use efficiency in coffee was 200&#xa0;kg ha<sup>-1</sup> year<sup>-1</sup> by studying the nitrogen use efficiency of different fertilizer application amount. <xref ref-type="bibr" rid="B24">Leal et&#xa0;al. (2010)</xref> found that at least 30% of nitrogen in urea would be lost by volatilization when 360&#xa0;kg ha<sup>-1</sup> urea was applied in coffee. Drip fertigation can synchronously and evenly transport water and fertilizer to crop roots, reduce water evaporation and nutrient leakage, and thus achieve efficient utilization of water and fertilizer (<xref ref-type="bibr" rid="B19">Guo et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). Drip fertigation can promote crop growth and improve leaf photosynthetic capacity by changing soil microenvironment, thus increasing crop yield, quality and water, and fertilizer use efficiency (<xref ref-type="bibr" rid="B35">Sakai et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B45">Vinecky et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B18">Geisseler et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B33">Rakocevic et&#xa0;al., 2023</xref>). Split fertilization under drip fertigation significantly affects the availability of soil nutrients in the root zone of crops, promotes the absorption of nutrients and the effective allocation of photosynthetic assimilates, which is conducive to high yields of crops (<xref ref-type="bibr" rid="B3">Bartholo et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B28">Parvizi and Sepaskhah, 2015</xref>; <xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). Previous studies have shown that split fertilization can increase crop nutrient absorption efficiency, improve photosynthesis, and coordinate organic matter distribution in various organs of crops, which is conducive to starch synthesis and accumulation, increase vitamin C and soluble sugar content, and further facilitate crop yield and fruit quality (<xref ref-type="bibr" rid="B46">Wang et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B5">Bruno et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B10">Corr&#xea;a et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B6">Byrareddy et&#xa0;al., 2019</xref>). With the same amount of fertilizer applied during the mango growth period, increasing the fertilizer application rate at fruit expansion could improve mango yield and partial fertilizer productivity, and increasing the fertilizer application at fruit ripening could increase the content of vitamin C, carotenoids and soluble solids in mango (<xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). The fertilizer requirement of coffee was found to be closely related to the physiological stages (<xref ref-type="bibr" rid="B3">Bartholo et&#xa0;al., 2003</xref>). <xref ref-type="bibr" rid="B5">Bruno et&#xa0;al. (2011)</xref> found that the leaves have the greatest demand for nitrogen fertilizer during the fruit expansion of coffee. <xref ref-type="bibr" rid="B38">Sun et&#xa0;al. (2018)</xref> indicated that the application of nitrogen fertilizer at the fruit expansion period was beneficial to increasing the dry matter accumulation of <italic>Coffea canephora</italic>, while excessive application of nitrogen fertilizer would reduce fertilizer use efficiency. It is not clear about the amount of fertilizer required for adult coffee trees in each growth period, but it is well known that fertilization during coffee berry expansion is most conducive to increasing fruit yield. At present, studies about coffee fertilization have focused on the effects of different nitrogen application rates or fertilizer ratios on growth, yield and quality (<xref ref-type="bibr" rid="B13">Dinesh et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B4">Bruno et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B35">Sakai et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B38">Sun et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B6">Byrareddy et&#xa0;al., 2019</xref>). However, there are few reports about the effects of split fertilization on photosynthetic physiology, yield, quality and volatiles of coffee.</p>
<p>How to improve and regulate coffee bean yield and quality through split fertilization is still unclear and deserves further study. We hypothesized that different fertilizer application at early flowering, berry expansion and berry ripening would affect coffee leaf gas exchange, bean yield and quality. In this experiment, the effects of drip fertigation on leaf gas exchange, bean nutrients, volatile components and cup quality of Arabica coffee were studied. The aim was to find the best combination of drip irrigation and split fertilization mode, and provide practical basis for nutrient management, high-quality and high-yield of Arabica coffee in the xerothermic regions.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Experimental site</title>
<p>The field experiment was conducted from February 2020 to February 2022 in Lujiangba, Baoshan, Yunnan Province, Southwest China (25&#xb0;4&#x2032;N, 99&#xb0;11&#x2032;E; 799.50&#xa0;m above sea level) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The region has a typical hot-dry valley climate, with average annual precipitation of 755.40&#xa0;mm (80% concentrated in June to October), average annual evaporation of 2101.90&#xa0;mm, average annual temperature of 21.3&#xb0;C, absolute maximum and minimum temperatures of 40.4&#xb0;C and 0.2&#xb0;C, average annual sunshine hours of 2328&#xa0;h, and a relative humidity of 71%. The precipitation was 583.3&#xa0;mm in 2020-2021 and 575.8&#xa0;mm in 2021-2022, and the average daily minimum and maximum temperatures were 10.22&#xb0;C and 32.49&#xb0;C (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). The soil in the experimental field was red-brown sandy loam, with organic matter of 17.0&#xa0;g kg<sup>-1</sup>, total nitrogen of 1.1&#xa0;g kg<sup>-1</sup>, total phosphorus of 1.15&#xa0;g kg<sup>-1</sup>, available nitrogen of 90.6 mg kg<sup>-1</sup>, available phosphorus of 12.7 mg kg<sup>-1</sup>, and available potassium of 126.7 mg kg<sup>-1</sup>.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Geographical location of the experimental site.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g001.tif"/>
</fig>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>The solar radiation, daily temperature, precipitation and irrigation quota during the experiment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g002.tif"/>
</fig>
<p>The 5-year-old coffee trees (Catimor CIFC7963) with uniform growth potential (1.65-1.85&#xa0;m of height) were used as the experimental material. The row spacing was 1.5&#xa0;m &#xd7; 2.0&#xa0;m.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Experiment design</title>
<p>The total fertilization amount was determined to be 750&#xa0;kg ha<sup>-1</sup> year<sup>-1</sup> referring to the local fertilization practices and split in three times at early flowering (FL: March), the berry expansion (BE: July), and the berry ripening (BR: October). There were 7 fertilization modes: equal fertilization throughout the growth cycle (FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>) and 6 variable fertilizations (FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>). Each treatment had 3 replicates, in which consisted of 5 trees, each replicate was an experimental plot with an area of 15 m<sup>2</sup> (2&#xa0;m &#xd7; 7.5&#xa0;m), and 21 plots in total. Macronutrient water-soluble fertilizer (N-P<sub>2</sub>O<sub>5</sub>-K<sub>2</sub>O:20%-20%-20%) (Xuelvfeng, Saigute Biotechnology Co., Ltd., Wuhan, China) was adopted and applied on 5<sup>th</sup> March, 20<sup>th</sup> July and 25<sup>th</sup> October in 2020, 8<sup>th</sup> March, 25<sup>th</sup> July, and 29<sup>th</sup> October in 2021. Drip fertigation was carried out with a differential pressure fertilization tank.</p>
<p>The irrigation quota was determined based on monthly water consumption intensity data in local Arabica coffee (<xref ref-type="bibr" rid="B9">Chen et&#xa0;al., 1995</xref>) and effective precipitation in the region. The equation 1:</p>
<disp-formula>
<label>Eq. 1</label>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:msub>
<mml:mi>I</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mo stretchy="false">(</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#xd7;</mml:mo>
<mml:mi>n</mml:mi>
<mml:mo stretchy="false">)</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>I<sub>i</sub>
</italic> is irrigation quota in the ith period (mm), <italic>ET<sub>ci</sub>
</italic> is average water consumption intensity in the <italic>i</italic>th period (mm d<sup>&#x2212;1</sup>), <italic>n</italic> is the period (d), and <italic>P<sub>i</sub>
</italic> is effective precipitation in the <italic>i</italic>th period (mm).</p>
<p>The field irrigation system was equipped with a water pumping station, a filter device, a main pipeline, branch pipelines, capillary pipelines, and emitters. The branch control method was adopted to design drip irrigation pipelines, and the irrigation amount was controlled by the water meter. The flow rate of emitters was 2.5 L h<sup>-1</sup> with a working pressure of 0.3 MPa. One circular capillary was set 0.3&#xa0;m away from the trunk, and each circular capillary installed 2 emitters. All treatments were fully irrigated every 7 days during the experiment, with a total irrigation quota of 957.0&#xa0;mm. The precipitation and irrigation quota are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>. Manual tillage and weeding were carried out monthly, pest controlled in early May, there was no shaping and pruning of coffee trees. Other field management was consistent with local practice.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Measurements and calculations</title>
<sec id="s2_3_1">
<label>2.3.1</label>
<title>Leaf gas exchange measurements</title>
<p>The <italic>A</italic>
<sub>net</sub>, transpiration rate (<italic>T</italic>
<sub>r</sub>), <italic>g</italic>
<sub>s</sub> of healthy functional leaves of the 3<sup>rd</sup> to 5<sup>th</sup> pairs in the superior plant layer counted from the tip was measured using a portable photosynthesis system (LI-6400XT, Lincoln, Nebraska, USA) at 9:00-11:00 am (under natural irradiance) on 22<sup>nd</sup> May, 5<sup>th</sup> October, 21<sup>st</sup> December in 2020 and 26<sup>th</sup> May, 5<sup>th</sup> October, 23<sup>rd</sup> December in 2021.</p>
<p>Leaf water use efficiency (LWUE) was calculated (<xref ref-type="bibr" rid="B25">Li et&#xa0;al., 2021</xref>) as equation 2:</p>
<disp-formula>
<label>Eq. 2</label>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:mi>L</mml:mi>
<mml:mi>W</mml:mi>
<mml:mi>U</mml:mi>
<mml:mi>E</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mrow>
<mml:mtext>net</mml:mtext>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>r</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Where LWUE is leaf water use efficiency (&#x3bc;mol mmol<sup>-1</sup>), <italic>A</italic>
<sub>net</sub> is leaf net photosynthetic rate (&#xb5;mol m<sup>-2</sup> s<sup>-1</sup>), <italic>T</italic>
<sub>r</sub> is transpiration rate (mmol m<sup>-2</sup> s<sup>-1</sup>).</p>
<p>Carboxylation efficiency (CE) was calculated (<xref ref-type="bibr" rid="B27">Liu et&#xa0;al., 2019</xref>) as equation 3:</p>
<disp-formula>
<label>Eq. 3</label>
<mml:math display="block" id="M3">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>E</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mrow>
<mml:mtext>net</mml:mtext>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>C</mml:mi>
<mml:mtext>i</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:mfrac>
<mml:mo>&#xd7;</mml:mo>
<mml:mn>1000</mml:mn>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Where CE is carboxylation efficiency (mmol m<sup>-2</sup> s<sup>-1</sup>), <italic>C</italic>
<sub>i</sub> is intercellular CO<sub>2</sub> concentration (&#xb5;mol mol<sup>-1</sup>).</p>
</sec>
<sec id="s2_3_2">
<label>2.3.2</label>
<title>Dry bean yield</title>
<p>Fresh bright-red mature beans were harvested by hand in batches from December to February of the next year. The fresh beans were decorticated with a coffee decorticator and soaked in water. Then the beans were washed, kneaded, shelled and degummed. The bean yield (kg ha<sup>-1</sup>) was determined after dried in natural sunlight until the water content was about 11%-12%. Appropriate amount of coffee beans harvested in 2021-2022 were selected to determine the nutrients of green coffee beans, volatile compounds and cup quality of roasted beans.</p>
</sec>
<sec id="s2_3_3">
<label>2.3.3</label>
<title>Crop water use efficiency and partial factor productivity of fertilizer</title>
<p>Crop water use efficiency (WUE) was calculated (<xref ref-type="bibr" rid="B26">Liu et&#xa0;al., 2016</xref>) as equation 4:</p>
<disp-formula>
<label>Eq. 4</label>
<mml:math display="block" id="M4">
<mml:mrow>
<mml:mi>W</mml:mi>
<mml:mi>U</mml:mi>
<mml:mi>E</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>Y</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where WUE is crop water use efficiency (kg m<sup>&#x2212;3</sup>), <italic>Y</italic> is coffee dry bean yield (kg ha<sup>&#x2212;1</sup>), and <italic>ET</italic> is total water consumption over the growing period (mm). <italic>ET</italic> was calculated as equation 5:</p>
<disp-formula>
<label>Eq. 5</label>
<mml:math display="block" id="M5">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:mi>T</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>I</mml:mi>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>&#x394;</mml:mi>
<mml:mi>W</mml:mi>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>I</italic> is total irrigation quota (mm), <italic>P<sub>r</sub>
</italic> is effective precipitation (mm), and <italic>&#x394;W</italic> is variation of soil moisture during the experimental period (mm).</p>
<p>Partial factor productivity of fertilizer (PFP) was calculated (<xref ref-type="bibr" rid="B11">Cui et&#xa0;al., 2020</xref>) as equation 6:</p>
<disp-formula>
<label>Eq. 6</label>
<mml:math display="block" id="M6">
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:mi>F</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>Y</mml:mi>
<mml:mi>F</mml:mi>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Where PFP is partial factor productivity of fertilizer (kg <sup>&#x2212;1</sup>), <italic>Y</italic> is total dry bean yield of coffee (kg ha<sup>&#x2212;1</sup>), <italic>F</italic> is the total input of fertilizer (kg ha<sup>&#x2212;1</sup>).</p>
</sec>
<sec id="s2_3_4">
<label>2.3.4</label>
<title>Nutritional components</title>
<p>The appropriate amount of shelled coffee beans was crushed with a grinder (WK-1000A, Shandong Jingcheng Medicine Equipment Manufacturing Co., Ltd., Shandong, China) to determine their nutrients. Ash content was determined by the muffle furnace method. About 5.00&#xa0;g of coffee sample was placed into a muffle furnace (M10L1200, Sigma (Shanghai) High Temperature Electric Furnace Co., Ltd., Shanghai, China) at 600 &#xb1; 25&#xb0;C to completely carbonizing till smokeless, cooling and weighing. Protein was determined by Kjeldahl method. Weighing fully mixed grinded coffee samples 0.20-0.30&#xa0;g into the digestive tube, adding a mixed catalyst of copper sulfate and potassium sulfate and 20 mL of sulfuric acid in a fume hood for digestion and carbonization. Automatic liquid addition, distillation, titration and recording with automatic Kjeldahl nitrogen analyzer (K1100, Haineng Future Technology Group Co. Ltd, Shandong, China). Fat was determined by Soxhlet extraction method. Weighing an evenly mixed coffee sample of 5.00&#xa0;g in a Soxhlet extractor (BSXT06-150, Beijing Haifuda Technology Co., Ltd., Beijing, China), extracting 6-8&#xa0;h for 70&#xb0;C water bath, siphoning every 3-5&#xa0;min. Total sugar was determined by anthrone colorimetric method. 0.60 mL of the prepared extract was added with 2.40 mL of anthrone reagent. Standard curves were measured with 0.10 mg mL<sup>-1</sup> glucose standard solution at 620 nm wavelength by spectrophotometer (UV-1600, Shanghai Meifuda Instrument Co., Ltd., Shanghai, China). Caffeine and chlorogenic acid were determined by ultraviolet spectrophotometry (<xref ref-type="bibr" rid="B21">Khochapong et&#xa0;al., 2021</xref>). The prepared coffee sample extract was mixed with dichloromethane at a ratio of 1:1. After 10&#xa0;min of shaking, caffeine and chlorogenic acid were separated using a separatory funnel. The absorbance of chlorogenic acid (dissolved in distilled water) was determined by spectrophotometer at a wavelength of 324 nm with distilled water as blank. The caffeine extract (dissolved in dichloromethane) was determined by spectrophotometry at a wavelength of 274 nm with dichloromethane as a blank.</p>
</sec>
<sec id="s2_3_5">
<label>2.3.5</label>
<title>Coffee bean roasting and volatile compounds</title>
<p>120 g of green coffee beans were poured into a coffee baking machine (TN-100-1G, VINA NHATRANG, Vietnam) with the pot temperature of 180&#xb0;C, the firepower of 1 Kw, and the damper of 0.5. Adjusting the firepower to 1.5 Kw when the bean temperature reached 170&#xb0;C, then reduced the firepower to 0.8 Kw after the first explosion began at 193&#xb0;C, held for 2&#xa0;min, and took out when the temperature reached 208&#xb0;C to obtain coffee samples with medium roasting degrees. After the first explosion under the same conditions, held for 3&#xa0;min, and took out when the temperature reached 225&#xb0;C to obtain coffee samples with dark roasting degrees. Then the cooling device was opened 1&#xa0;min before flameout, and the coffee samples were quickly cooled to room temperature. The roasted coffee beans were crushed and passed through 40 mesh sieves, and then the volatile compounds were measured.</p>
<p>Headspace-gas chromatography-mass spectrometry (HS-GC-MS) described by <xref ref-type="bibr" rid="B14">Dong et&#xa0;al. (2019)</xref> was used for the analysis of volatile compounds. The solid-phase microextraction probe (SPME) (50/30 &#x3bc;m CAR/PDMS/DVB, Supelco, USA) was inserted into the injection port of GCMS-QP2010 gas chromatography-mass spectrometer (Shimadu, Japan) and aged for 1&#xa0;h at 300&#xb0;C. Up to 1.5&#xa0;g of roasted ground coffee was placed in a 10 mL vial, equilibrated with a thermostatic heater at 60&#xb0;C for 20&#xa0;min, extracted for 30&#xa0;min using the SPME fiber in the headspace, and then injected into the 250&#xb0;C injection port for desorption for 3&#xa0;min. Volatile compounds were separated using a polar DB-WAX capillary column (30&#xa0;m &#xd7; 0.25&#xa0;mm &#xd7; 0.25 &#x3bc;m film thickness). The oven temperature was maintained at 40&#xb0;C for 2&#xa0;min, raised at 1.5&#xb0;C/min to 130&#xb0;C, and then increased at 4&#xb0;C/min up to 200&#xb0;C and held for 5&#xa0;min. The detector temperature was 230&#xb0;C, and the injection port temperature was 250&#xb0;C. The carrier gas was helium without split injection, with a flow rate of 1.0 mL/min for 3&#xa0;min. Mass spectrometry analysis operated in the electron impact ionization mode (70 eV), with a scan range of 35-350 amu and ion source temperature of 230&#xb0;C.</p>
<p>The compounds were tentatively identified by comparing the mass spectra based on a similarity search more than 80% of NIST05 library as well as related literature. The peak area normalization method was used for quantitative analysis (<xref ref-type="bibr" rid="B15">Dong et&#xa0;al., 2018</xref>).</p>
</sec>
<sec id="s2_3_6">
<label>2.3.6</label>
<title>Cup quality</title>
<p>The roasted coffee beans were naturally cooled and ground into fine powder with an average particle size of about 0.60-0.70&#xa0;mm. Then 10.00&#xa0;g roasted ground coffee was added into the cup and about 180 mL purified water at 90&#xb0;C was poured on the cup for 4&#xa0;min (<xref ref-type="bibr" rid="B47">Worku et&#xa0;al., 2018</xref>). Referring to the method of <xref ref-type="bibr" rid="B20">Hu et&#xa0;al. (2020)</xref>, coffee cup quality was determined by five professional evaluators. The sensory scoring indexes included aroma, flavor, aftertaste, acidity, body, balance, overall, cleanliness, uniformity, and sweetness. The sensory indexes were evaluated in the range of 0 to 10 with the increment of 0.25, and the sum of 10 sensory indexes was the total score of an individual sample.</p>
</sec>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>TOPSIS comprehensive scoring method</title>
<p>Technique for order preference by similarity to ideal solution (TOPSIS) is a commonly used comprehensive evaluation method. It can make full use of the information of the original data, and the results can accurately reflect the gap between the evaluation schemes. According to the improved TOPSIS, the comprehensive benefit evaluation model of coffee physiological indexes, nutritional quality indexes and coffee cups was established (<xref ref-type="bibr" rid="B26">Liu et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). Steps are as follows:</p>
<p>(1) Establishing the matrix <italic>R</italic> of evaluation objects and evaluation indicators. There were 7 evaluation objects (m) of fertilization, and 34 evaluation indexes (n) in 2021-2022 for <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub>, <italic>g</italic>
<sub>s</sub>, LWUE, CE, bean yield, bean quality (ash, total sugar, fat, protein, caffeine and chlorogenic acid), and indexes of coffee cups with different roasting degrees (aroma, flavor, aftertaste, acidity, body, balance, overall, cleanliness, uniformity, sweetness and total score), using the equation 7:</p>
<disp-formula>
<label>Eq. 7</label>
<mml:math display="block" id="M7">
<mml:mrow>
<mml:mi>R</mml:mi>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mo>&#xd7;</mml:mo>
<mml:mi>n</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>r<sub>ij</sub>
</italic> is the <italic>j</italic>th evaluation index under the <italic>i</italic>th evaluation object, m = 7, n = 34.</p>
<p>(2) Indicators were normalized to build a normative decision matrix <italic>Z</italic>=(<italic>z<sub>ij</sub>
</italic>)<italic>
<sub>m</sub>
</italic>
<sub>&#xd7;</sub>
<italic>
<sub>n</sub>
</italic>, using the equation 8:</p>
<disp-formula>
<label>Eq. 8</label>
<mml:math display="block" id="M8">
<mml:mrow>
<mml:msub>
<mml:mi>Z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#xb7;</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>m</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
<mml:msup>
<mml:mo stretchy="false">)</mml:mo>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>0.5</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(3) Weight determination:</p>
<p>(a) The judgment matrix was constructed using the equation 9:</p>
<disp-formula>
<label>Eq. 9</label>
<mml:math display="block" id="M9">
<mml:mrow>
<mml:mi>B</mml:mi>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msub>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:mo>&#xd7;</mml:mo>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msub>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>j</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:mo>&#xd7;</mml:mo>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>b<sub>xp</sub>
</italic> is the <italic>p</italic>th evaluation object under the <italic>x</italic>th evaluation index of the matrix.</p>
<p>(b) Each column of the judgment matrix was normalized using the equation 10:</p>
<disp-formula>
<label>Eq. 10</label>
<mml:math display="block" id="M10">
<mml:mrow>
<mml:msubsup>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#xb7;</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>k</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>n</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>k</italic> represents the <italic>k</italic>th evaluation index.</p>
<p>(c) The matrix was summed by rows using the equation 11:</p>
<disp-formula>
<label>Eq. 11</label>
<mml:math display="block" id="M11">
<mml:mrow>
<mml:msub>
<mml:mover accent="true">
<mml:mi>w</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>m</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msubsup>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(d) The vector <inline-formula>
<mml:math display="inline" id="im1">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>W</mml:mi>
<mml:mo stretchy="true">&#xaf;</mml:mo>
</mml:mover>
<mml:mo>=</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mo stretchy="false">[</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>w</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#xaf;</mml:mo>
</mml:mover>
<mml:mo>,</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>w</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#xaf;</mml:mo>
</mml:mover>
<mml:mo>,</mml:mo>
<mml:mo>&#xb7;</mml:mo>
<mml:mo>&#xb7;</mml:mo>
<mml:mo>&#xb7;</mml:mo>
<mml:mo>,</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>w</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#xaf;</mml:mo>
</mml:mover>
<mml:mo stretchy="false">]</mml:mo>
</mml:mrow>
<mml:mtext>T</mml:mtext>
</mml:msup>
</mml:mrow>
</mml:math>
</inline-formula> was normalized using the equation 12:</p>
<disp-formula>
<label>Eq. 12</label>
<mml:math display="block" id="M12">
<mml:mrow>
<mml:msub>
<mml:mi>w</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mover accent="true">
<mml:mi>w</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mi>p</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#xb7;</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>n</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mover accent="true">
<mml:mi>w</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(4) The weighting matrix <italic>Z</italic>&#x2032; was constituted using the equation 13:</p>
<disp-formula>
<label>Eq. 13</label>
<mml:math display="block" id="M13">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>w</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>&#xb7;</mml:mo>
<mml:msub>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(5) The positive ideal solution (<inline-formula>
<mml:math display="inline" id="im2">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>) and the negative ideal solution (<inline-formula>
<mml:math display="inline" id="im3">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>) were obtained using the equation 14 and 15:</p>
<disp-formula>
<label>Eq. 14</label>
<mml:math display="block" id="M14">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:munder>
<mml:mrow>
<mml:mi>max</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>i</mml:mi>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:munder>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula>
<label>Eq. 15</label>
<mml:math display="block" id="M15">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:munder>
<mml:mrow>
<mml:mi>min</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>i</mml:mi>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:munder>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(6) The Euclidean distances of <inline-formula>
<mml:math display="inline" id="im4">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im5">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> between each object and <inline-formula>
<mml:math display="inline" id="im6">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> <inline-formula>
<mml:math display="inline" id="im7">
<mml:mrow>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> were calculated using the equation 16 and 17:</p>
<disp-formula>
<label>Eq. 16</label>
<mml:math display="block" id="M16">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>m</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:mstyle>
<mml:mo>&#x2212;</mml:mo>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>j</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
<mml:msup>
<mml:mo stretchy="false">)</mml:mo>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mn>0.5</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula>
<label>Eq. 17</label>
<mml:math display="block" id="M17">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>m</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
<mml:mo>'</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:mstyle>
<mml:mo>&#x2212;</mml:mo>
<mml:msubsup>
<mml:mi>z</mml:mi>
<mml:mi>j</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
<mml:msup>
<mml:mo stretchy="false">)</mml:mo>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mn>0.5</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:math>
</disp-formula>
<p>(7) The relative proximity coefficients were calculated and sorted using the equation 18. The closer <italic>R<sub>c</sub>
</italic> is to 1, the better the evaluation object is.</p>
<disp-formula>
<label>Eq. 18</label>
<mml:math display="block" id="M18">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>c</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:mfrac>
<mml:mo>,</mml:mo>
<mml:mo stretchy="false">(</mml:mo>
<mml:mn>0</mml:mn>
<mml:mo>&#x2264;</mml:mo>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>c</mml:mi>
</mml:msub>
<mml:mo>&#x2264;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:math>
</disp-formula>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Statistical analysis</title>
<p>To realize data visualization, hierarchical clustering was used to investigate the variation of flavor substances among different fertilizer treatments. hierarchical clustering creates a hierarchical nested clustering tree by calculating the similarity between data points of different categories. The merging algorithm of hierarchical clustering combines the two most similar data points of all data by calculating the similarity between two categories of data points, and repeats this process. Each class of compounds was normalized in the study. Moreover, square Euclidean distance was used to perform similarity measure, and the data points with the smallest distance value were combined each other. The clustering algorithm was ward&#x2019;s linkage method that minimizes the sum of squares of all clusters.</p>
<p>Data collecting and collating were conducted by Excel 2010. TOPSIS was executed by Excel 2010. Graphics drawing and cluster analysis was performed by Origin 2018 software. One-way analysis of variance (ANOVA) (<italic>P</italic>&lt;0.05) and Pearson correlation analysis were performed using SPSS 23.0 software. Part of experimental pictures are shown in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Pictures of experiment. <bold>(A)</bold> experimental field, <bold>(B)</bold> Leaf gas exchange measurements, <bold>(C)</bold> Berry maturity, <bold>(D)</bold> Coffee bean roasting.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g003.tif"/>
</fig>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Leaf gas exchange</title>
<p>Different fertilization mode had significant effects on <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub>, <italic>g</italic>
<sub>s</sub> and CE of Arabica coffee. Among them, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> had the highest <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub>, with a two-year average value of 10.67 &#xb5;mol m<sup>-2</sup> s<sup>-1</sup> and 199.77 mmol m<sup>-2</sup> s<sup>-1</sup>, respectively, while FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> had the lowest <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub> (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, C</bold>
</xref>). FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> had the highest <italic>T</italic>
<sub>r</sub> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>), with a two-year average value of 4.36 mmol m<sup>-2</sup> s<sup>-1</sup>. In 2020-2021, compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> decreased <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub> by 8.07% and 5.26%, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> decreased <italic>A</italic>
<sub>net</sub> by 6.22%, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> increased <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub> by 5.35% and 6.53%, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> increased <italic>g</italic>
<sub>s</sub> by 8.12%. In 2021-2022, compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> decreased <italic>A</italic>
<sub>net</sub> by 6.30%, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> increased <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub> by 7.07% and 8.97%, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> increased <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub> by 5.16%, 5.85% and 10.62%, respectively. For the two-year average, compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> and FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> decreased <italic>A</italic>
<sub>net</sub> by 7.23% and 5.28%, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> increased <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub> by 7.92%, 6.34% and 7.74%, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> increased <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub> by 5.28%, 5.37%, and 9.63%. Except for FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>, other treatments decreased CE compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4D</bold>
</xref>). Compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> decreased CE by 12.02%, 8.00% and 10.07% in 2020-2021, and decreased CE by 11.15%, 7.09% and 9.41% of two-year average, respectively. The LWUE value of FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> was the highest, with a two-year average of 2.49 &#x3bc;mol mmol<sup>-1</sup> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4E</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Effects of split fertilization on leaf net photosynthetic rate <bold>(A)</bold>, transpiration rate <bold>(B)</bold>, stomatal conductance <bold>(C)</bold>, carboxylation efficiency <bold>(D)</bold> and leaf water use efficiency <bold>(E)</bold> of Arabica coffee. Different lowercase letters at the top of the bar indicate significant differences among treatments (<italic>P</italic>&lt;0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g004.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Dry bean yield</title>
<p>Different fertilization mode significantly influenced the yield of Arabica coffee. In both years, the highest yield occurred in FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> and the lowest yield occurred in FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>). Compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, the yield of FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> were decreased by 19.11% and 7.24% in 2020-2021, decreased by 18.38% and 7.92% in 2021-2022, and two-year average yield decreased by 18.74% and 7.58%. However, the yield of FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> in 2020-2021, 2021-2022 and two-years average were 8.99%, 8.74% and 8.86% higher than those in FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, respectively. Furthermore, there was no significant difference in yield among FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Effects of split fertilization on dry bean yield of Arabica coffee. Different lowercase letters at the top of the bar indicate significant differences among treatments (<italic>P</italic>&lt;0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g005.tif"/>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Crop water use efficiency and partial factor productivity of fertilizer</title>
<p>Different fertilization mode had significant effect on crop water use efficiency (WUE) of Arabica coffee in two years. As could be seen from <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>, there was no significant difference on WUE between FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> and FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>. Compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> decreased average WUE by 18.64% and 8.47%, while FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> increased by 8.47%.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Effects of split fertilization on crop water use efficiency <bold>(A)</bold> and partial factor productivity of fertilizer <bold>(B)</bold> of Arabica coffee. Different lowercase letters at the top of the bar indicate significant difference among treatments (<italic>P</italic>&lt;0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g006.tif"/>
</fig>
<p>In terms of PFP, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> had the lowest PFP, and both FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> had higher PFP (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>), indicating that higher fertilization in BE was conducive to improving fertilizer utilization efficiency.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Nutritional components</title>
<p>Different fertilization had significant effects on bean nutrient content of Arabica coffee. FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> had the highest nutrient content except of fat and caffeine, while FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> had the lowest except of caffeine and chlorogenic acid (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, F<sub>I150</sub>F<sub>II350</sub>F<sub>III250</sub> and F<sub>I250</sub>F<sub>II350</sub>F<sub>III150</sub> increased ash content by 1.98% and 6.47%, increased total sugar content by 5.23% and 9.68%, increased fat content by 5.77% and 3.60%, increased protein content by 7.57% and 14.02%, increased caffeine content by 18.45% and 4.85%, and increased chlorogenic acid content by 11.46% and 15.42%. Compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> decreased ash content by 10.97% and 10.79%, decreased total sugar content by 9.07% and 6.19%, decreased fat content by 3.73% and 3.39%, decreased protein content by 7.05% and 6.65%, and decreased chlorogenic acid content by 12.64% and 14.96%. The caffeine content of FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> and FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> decreased by 7.77% and 6.80% compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>. There was no significant difference on nutrient content among FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150B</sub> and FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> except of ash content.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Effects of fertilization modes at different growth stages on bean nutrients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Treatment</th>
<th valign="middle" align="center">Ash<break/>/g (100g)<sup>-1</sup>
</th>
<th valign="middle" align="center">Total sugar<break/>/g (100g)<sup>-1</sup>
</th>
<th valign="middle" align="center">Fat<break/>/g (100g)<sup>-1</sup>
</th>
<th valign="middle" align="center">Protein<break/>/g (100g)<sup>-1</sup>
</th>
<th valign="middle" align="center">Caffeine<break/>/%</th>
<th valign="middle" align="center">Chlorogenic acid<break/>/g kg<sup>-1</sup>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="center">5.56&#xb1;0.12b</td>
<td valign="middle" align="center">11.47&#xb1;0.10d</td>
<td valign="middle" align="center">14.73&#xb1;0.07cd</td>
<td valign="middle" align="center">15.33&#xb1;0.19c</td>
<td valign="middle" align="center">1.03&#xb1;0.02bc</td>
<td valign="middle" align="center">23.73&#xb1;1.01b</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="center">5.27&#xb1;0.13c</td>
<td valign="middle" align="center">11.28&#xb1;0.21d</td>
<td valign="middle" align="center">14.59&#xb1;0.15d</td>
<td valign="middle" align="center">15.23&#xb1;0.16c</td>
<td valign="middle" align="center">1.12&#xb1;0.08b</td>
<td valign="middle" align="center">23.23&#xb1;0.69b</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="center">5.67&#xb1;0.14ab</td>
<td valign="middle" align="center">12.07&#xb1;0.10b</td>
<td valign="middle" align="center">15.58&#xb1;0.22a</td>
<td valign="middle" align="center">16.49&#xb1;0.33b</td>
<td valign="middle" align="center">1.22&#xb1;0.04a</td>
<td valign="middle" align="center">26.45&#xb1;0.77a</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="center">4.95&#xb1;0.20d</td>
<td valign="middle" align="center">10.43&#xb1;0.11f</td>
<td valign="middle" align="center">14.18&#xb1;0.08e</td>
<td valign="middle" align="center">14.25&#xb1;0.17d</td>
<td valign="middle" align="center">1.05&#xb1;0.04b</td>
<td valign="middle" align="center">20.73&#xb1;0.80c</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="center">5.92&#xb1;0.20a</td>
<td valign="middle" align="center">12.58&#xb1;0.09a</td>
<td valign="middle" align="center">15.26&#xb1;0.23b</td>
<td valign="middle" align="center">17.48&#xb1;0.26a</td>
<td valign="middle" align="center">1.08&#xb1;0.04b</td>
<td valign="middle" align="center">27.39&#xb1;0.45a</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="center">4.96&#xb1;0.10d</td>
<td valign="middle" align="center">10.76&#xb1;0.13e</td>
<td valign="middle" align="center">14.23&#xb1;0.16e</td>
<td valign="middle" align="center">14.31&#xb1;0.13d</td>
<td valign="middle" align="center">0.95&#xb1;0.04c</td>
<td valign="middle" align="center">20.18&#xb1;1.02c</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="center">5.22&#xb1;0.16cd</td>
<td valign="middle" align="center">11.77&#xb1;0.10c</td>
<td valign="middle" align="center">14.95&#xb1;0.19c</td>
<td valign="middle" align="center">15.17&#xb1;0.22c</td>
<td valign="middle" align="center">0.96&#xb1;0.03c</td>
<td valign="middle" align="center">23.65&#xb1;0.64b</td>
</tr>
<tr>
<td valign="middle" align="left">Significance test (<italic>P</italic> value)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are means &#xb1; standard deviations (n=3), different lowercase letters in the same column indicate significant difference at <italic>P</italic>&lt;0.05 level.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Volatile compounds</title>
<sec id="s3_5_1">
<label>3.5.1</label>
<title>Volatile compounds of roasted coffee beans at various fertilization modes</title>
<p>The volatile compounds and relative contents of medium (M) and dark (D) roasted coffee under different fertilization modes are shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>. The results showed that 81 volatile compounds were identified in roasted ground coffee, including 15 furans, 14 ketones, 2 aldehydes, 8 esters, 2 alcohols, 6 phenols, 2 acids, 12 pyrazines, 6 pyridines, 7 pyrroles and 7 others. Medium roasted beans detected 63-73 volatiles and dark roasted beans detected 69-75 volatiles. There were 54 same volatile compounds accounting for 81.00-91.00% in coffee beans under different fertilization treatments, which constituted the main flavor of coffee (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>).</p>
<p>Furans obtained the most abundant relative content (32.71-37.80%) among all volatile compounds in roasted coffee beans, mainly including furfuryl alcohol (increasing with roasting degree), furfural (decreasing with roasting degree) and 5-methylfurfural. The relative contents of furans in MFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, DFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, DFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> and MFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> were all above 35.00% (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Pyrazines (16.89-23.08%) are the important flavor compounds whose content was only second to furans, and the relative content of pyrazine compounds under dark roasting showed a downward trend compared with that under medium roasting (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Among them, 2,5-dimethylpyrazine, 2,6-dimethylpyrazine, 2,3,5-trimethylpyrazine and 2,3-dimethylpyrazine are important to coffee flavor. Ketones were the third major volatile compounds (11.59-17.66%). Among them, 1-acetyloxy-2-propanone and 1-(2-Hydroxy-5-methylphenyl) ethenone had higher content, while 2,3-butanedione and 2,3-pentanedione that contributed greatly to coffee flavor were in low content (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Pyrroles and pyridines accounted for 5.95-8.02% and 3.20-7.42%, respectively, while they had less effect on coffee flavor due to low sensory threshold (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Phenolic compounds (2.99-6.83%) increased with the deepening of roasting degree, mainly including maltol, phenol and 4-ethyl-2-methoxyphenol (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Acids mainly including acetic acid and isovaleric acid (1.42-10.26%) decreased with the deepening of roasting degree, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> obtained low acids content (1.42 -2.05%) due to acetic acid was not detected in this treatment (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). The acids content in MFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, MFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and DFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> were all more than 8.00% (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>). Furthermore, there was no significant difference on the content of esters (3.51-4.33%) among different treatments (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S1</bold>
</xref>).</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Cumulative graph <bold>(A)</bold> and hierarchical cluster analysis <bold>(B)</bold> of volatile compounds in medium and dark roasted coffee under different fertilization modes. I, the first major cluster; II, the second major cluster. M, medium roasting degree; D, dark roasting degree.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g007.tif"/>
</fig>
</sec>
<sec id="s3_5_2">
<label>3.5.2</label>
<title>Cluster analysis of volatile compounds</title>
<p>Cluster analysis was used to visualize the data across a wide range of substances and treatments. As shown in <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B</bold>
</xref>, different roasting treatments were clearly divided into two clusters. Cluster I represented medium roasting treatments, which contained high content of acids and pyrazines. Cluster II represented dark roasting treatments, which had a high content of pyrroles, pyridines, phenols, alcohols, aldehydes, and others (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B</bold>
</xref>). This indicated that roasting degree had an important effect on the relative content of volatile compounds. Cluster I contained 2 subcategories. The first subcategory included MFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, MFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> and MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>, which contained high content of pyrroles, pyridines and acids. The second subcategory included MFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, MFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> and MFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>, which had a high content of pyrazines, esters, ketones and furans. The first subcategory of cluster II was DFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, DFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, DFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>, DFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> and DFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>, in which pyridines and pyrroles were significantly higher than other treatments (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B</bold>
</xref>). Among them, the contents of pyrroles and pyridines were the highest in DFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> and DFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, while esters and ketones were low. The second subcategory of cluster II contained DFL<sub>150</sub>BE<sub>250</sub>BR<sub>250</sub> and DFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, which had high content of ketones, furans, phenols, alcohols, aldehydes and others (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Cup quality</title>
<p>The sensory indicators of cleanliness, uniformity and sweetness were not displayed in the <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> because they were all 10 points. The scores of aroma, acidity, balance and overall of medium roasted coffee generally ranged from 7.25 to 7.75. Among them, the sensory scores of MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> were all higher than 7.40, especially the flavor indicator, which had a great influence on the final total score. However, the sensory scores of MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> were low, which ranged from 6.75 to 7.25. In the situation of dark roasted coffee, the body scores ranged from 7.25 to 7.75, with acidity of 6.50 to 7.00. The total scores of medium roasted coffees were in order of MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> &gt; MFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> &gt; MFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> &gt; MFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> &gt; MFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> &gt; MFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> &gt; MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>, and the scores were all greater than 80.00 except of MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>. The total scores of dark roasted coffees were in the order of DFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> &gt; DFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> &gt; DFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> &gt; DFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub> &gt; DFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> &gt; DFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> &gt; DFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, and the total scores of other treatments except DFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> and DFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> were above 80.00. Moreover, the total scores of FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> under medium roasting degree were higher than dark roasting degree.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Cup quality of medium and dark roasted beans under different fertilization modes.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Treatment</th>
<th valign="middle" align="center">Aroma</th>
<th valign="middle" align="center">Flavor</th>
<th valign="middle" align="center">Aftertaste</th>
<th valign="middle" align="center">Acidity</th>
<th valign="middle" align="center">Body</th>
<th valign="middle" align="center">Balance</th>
<th valign="middle" align="center">Overall</th>
<th valign="middle" align="center">Total Score</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">MFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.44ab</td>
<td valign="middle" align="left">7.19bc</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.25cd</td>
<td valign="middle" align="left">81.13bc</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="left">7.31b</td>
<td valign="middle" align="left">7.06cd</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.38a</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.31bcd</td>
<td valign="middle" align="left">80.81c</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">7.31ab</td>
<td valign="middle" align="left">7.31ab</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.50ab</td>
<td valign="middle" align="left">82.19a</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="left">7.44ab</td>
<td valign="middle" align="left">6.88d</td>
<td valign="middle" align="left">6.88c</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">6.81c</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">7.19d</td>
<td valign="middle" align="left">79.81d</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">7.63a</td>
<td valign="middle" align="left">82.63a</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.31b</td>
<td valign="middle" align="left">7.25abc</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.13b</td>
<td valign="middle" align="left">7.50a</td>
<td valign="middle" align="left">7.25cd</td>
<td valign="middle" align="left">81.00bc</td>
</tr>
<tr>
<td valign="middle" align="left">MFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="left">7.5ab</td>
<td valign="middle" align="left">7.31ab</td>
<td valign="middle" align="left">7.19b</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">7.19b</td>
<td valign="middle" align="left">7.38a</td>
<td valign="middle" align="left">7.44abc</td>
<td valign="middle" align="left">81.56b</td>
</tr>
<tr>
<td valign="middle" align="left">Significance test (<italic>P</italic> value)</td>
<td valign="middle" align="left">0.020</td>
<td valign="middle" align="left">&lt;0.001</td>
<td valign="middle" align="left">&lt;0.001</td>
<td valign="middle" align="left">0.266</td>
<td valign="middle" align="left">&lt;0.001</td>
<td valign="middle" align="left">0.340</td>
<td valign="middle" align="left">0.001</td>
<td valign="middle" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.13bc</td>
<td valign="middle" align="left">7.13ab</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">6.81b</td>
<td valign="middle" align="left">7.56ab</td>
<td valign="middle" align="left">7.13a</td>
<td valign="middle" align="left">7.19ab</td>
<td valign="middle" align="left">80.50bc</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="left">7.00c</td>
<td valign="middle" align="left">7.00b</td>
<td valign="middle" align="left">7.19b</td>
<td valign="middle" align="left">6.75b</td>
<td valign="middle" align="left">7.44ab</td>
<td valign="middle" align="left">7.19a</td>
<td valign="middle" align="left">7.13ab</td>
<td valign="middle" align="left">79.69d</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.25ab</td>
<td valign="middle" align="left">7.13ab</td>
<td valign="middle" align="left">7.19b</td>
<td valign="middle" align="left">6.69b</td>
<td valign="middle" align="left">7.38b</td>
<td valign="middle" align="left">7.13a</td>
<td valign="middle" align="left">7.25ab</td>
<td valign="middle" align="left">80.00cd</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>
</td>
<td valign="middle" align="left">7.13bc</td>
<td valign="middle" align="left">7.13ab</td>
<td valign="middle" align="left">7.06b</td>
<td valign="middle" align="left">6.69b</td>
<td valign="middle" align="left">7.56ab</td>
<td valign="middle" align="left">7.25a</td>
<td valign="middle" align="left">7.06b</td>
<td valign="middle" align="left">79.88cd</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.25ab</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">7.00a</td>
<td valign="middle" align="left">7.44ab</td>
<td valign="middle" align="left">7.13a</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">81.00ab</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>
</td>
<td valign="middle" align="left">7.13bc</td>
<td valign="middle" align="left">7.13ab</td>
<td valign="middle" align="left">7.44a</td>
<td valign="middle" align="left">6.81b</td>
<td valign="middle" align="left">7.63a</td>
<td valign="middle" align="left">7.13a</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">80.56bc</td>
</tr>
<tr>
<td valign="middle" align="left">DFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>
</td>
<td valign="middle" align="left">7.38a</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">7.56a</td>
<td valign="middle" align="left">6.81b</td>
<td valign="middle" align="left">7.63a</td>
<td valign="middle" align="left">7.25a</td>
<td valign="middle" align="left">7.31a</td>
<td valign="middle" align="left">81.25a</td>
</tr>
<tr>
<td valign="middle" align="left">Significance test (<italic>P</italic> value)</td>
<td valign="middle" align="left">0.003</td>
<td valign="middle" align="left">0.309</td>
<td valign="middle" align="left">&lt;0.001</td>
<td valign="middle" align="left">0.007</td>
<td valign="middle" align="left">0.078</td>
<td valign="middle" align="left">0.451</td>
<td valign="middle" align="left">0.032</td>
<td valign="middle" align="left">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>M, medium roasting degree; D, dark roasting degree. Different lowercase letters in the same column under the same roasting degree indicate a significant difference at <italic>P</italic>&lt;0.05 level. </p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Correlation analysis of bean nutrients and volatile compounds/cup quality</title>
<p>Correlation analysis found that nutrients were correlated with flavor compounds to some extent (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). Total sugar content was positively correlated with furan and pyrazine content, while negatively correlated with acid content. Protein content was positively correlated with ketone and pyrazine content, while negatively correlated with acid and pyrrole content. Furthermore, there were interactions between volatile compounds.</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Correlation analysis of nutrients in green coffee beans and volatile compounds in roasted coffee beans. As is ash; Ts is total sugar; Fa is fat; Pr is protein; Ca is caffeine; Cha is chlorogenic acid; Fu is furans; Ke is ketones; Ald is aldehydes; Es is esters; Alc is alcohols; Ph is phenol; Ac is acids; Pyra is pyrazines; Pyri is pyridines; Pyrr is pyrroles; Oth is others. *denotes significant correlation between indicators (<italic>P</italic>&lt;0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g008.tif"/>
</fig>
<p>By exploring the correlation of nutrients content and cup quality, we found that total sugar content was positively correlated with aroma, flavor, aftertaste, acidity, body and overall indicator, fat content was positively correlated with body and overall indicator, chlorogenic acid content was positively correlated with overall indicator, and some sensory indexes influenced each other (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9</bold>
</xref>). Overall, there was no direct correlation between nutrients and sensory scores, while there was a clear correlation between green bean nutrients content.</p>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Correlation analysis of nutrients in green coffee beans and cup quality in roasted coffee beans. As is ash; Ts is total sugar; Fa is fat; Pr is protein; Ca is caffeine, Cha is chlorogenic acid. Ar is aroma; Fl is flavor; Af is aftertaste; Ac is acidity; Bo is body; Ba is balance; Ov is overall. *denotes significant correlation between indicators (<italic>P</italic>&lt;0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-14-1148616-g009.tif"/>
</fig>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>Comprehensive evaluation by TOPSIS</title>
<p>The TOPSIS method was used to comprehensively analyze and evaluate the <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub>, <italic>g</italic>
<sub>s</sub>, LWUE, CE, bean yield, bean quality and coffee cup quality indicators of different fertilization modes in 2021-2022. The results are shown in the <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>, and detailed information is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supp. S2</bold>
</xref>. As can be seen from the <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>, the ranking order was: FL<sub>250</sub>BE<sub>350</sub>BR<sub>150,</sub> FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>, FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> and FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>. This indicated that FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> could provide sufficient nutrients during the fertilizer-demanding period of coffee, which can not only promote the growth of Arabica coffee, but also improve the yield and quality of coffee beans. Therefore, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> was the optimal drip fertigation mode.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>TOPSIS comprehensive analysis of different fertilization modes of Arabica coffee.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Treatment</th>
<th valign="middle" align="center">
<inline-formula>
<mml:math display="inline" id="im8">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th valign="middle" align="center">
<inline-formula>
<mml:math display="inline" id="im9">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th valign="middle" align="center">
<italic>R<sub>c</sub>
</italic>
</th>
<th valign="middle" align="center">Ranking</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>
</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.48</td>
<td valign="top" align="center">4</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub>
</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.40</td>
<td valign="top" align="center">5</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>
</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.68</td>
<td valign="top" align="center">2</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub>
</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.16</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>
</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.79</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub>
</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.28</td>
<td valign="top" align="center">6</td>
</tr>
<tr>
<td valign="middle" align="left">FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub>
</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.53</td>
<td valign="top" align="center">3</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>
<inline-formula>
<mml:math display="inline" id="im10">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>, Positive ideal solution distance; <inline-formula>
<mml:math display="inline" id="im11">
<mml:mrow>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>, negative ideal solution distance; R<sub>c</sub>, relative proximity coefficient.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<sec id="s4_1">
<label>4.1</label>
<title>Leaf gas exchange of Arabica coffee</title>
<p>Under the conditions of drip irrigation, rational fertilization modes can timely and effectively meet the demand of crops for soil water and nutrients, improve the flower bud differentiation rate, delay leaf senescence, and prolong leaf gas exchange time, thus improving the photosynthetic capacity of plants (<xref ref-type="bibr" rid="B3">Bartholo et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B52">Zhang et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B27">Liu et&#xa0;al., 2019</xref>). The study found that compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, increasing fertilizer amount under the same irrigation level during FL and BE period was beneficial for the rapid increase in <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub>, and <italic>g</italic>
<sub>s</sub>, while change of fertilization at BR had a little effect on <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub> and <italic>g</italic>
<sub>s</sub>. It might be because the trees possess vigorous life activities at BE and BR, which require massive levels of nutrients. However, the leaf senescence and the decrease of key photosynthetic enzyme activities at BR result in the weakening of leaf gas exchange (<xref ref-type="bibr" rid="B3">Bartholo et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B32">Rakocevic et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). The BE is vital for the formation of coffee cherry. Increasing fertilizer application under the condition of sufficient soil water is beneficial to the absorption and accumulation of plant nutrients, which increase the leaf area, chlorophyll content and the synthesis of photosynthetic enzymes, thus effectively improving leaf gas exchange at BE and promoting the accumulation of photosynthetic products (<xref ref-type="bibr" rid="B45">Vinecky et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B38">Sun et&#xa0;al., 2018</xref>). By comparing the average <italic>A</italic>
<sub>net</sub> over two years, it was found that FL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> obtained the maximum value of <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub>, and FL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> obtained the minimum value of <italic>A</italic>
<sub>net</sub> and <italic>g</italic>
<sub>s</sub>. This further indicates that the FL and BE are the key phenophases of coffee photosynthesis, and more nutrients are needed to lay the foundation for high quality and high yield of Arabica coffee.</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Dry bean yield and water use efficiency of Arabica coffee</title>
<p>Under drip fertigation, split fertilization at different growth period can promote the transportation and absorption of nutrients in plants, enhance cell metabolism and carbohydrate synthesis, and promote the formation of coffee yield and quality (<xref ref-type="bibr" rid="B45">Vinecky et&#xa0;al., 2017</xref>). F<sub>I250</sub>F<sub>II350</sub>F<sub>III150</sub> obtained the highest dry bean yield, while F<sub>I250</sub>F<sub>II150</sub>F<sub>III350</sub> obtained the lowest dry bean yield. This indicates that the yield of coffee beans is closely related to the amount of fertilizer applied in different growth periods, especially at FS (<xref ref-type="bibr" rid="B5">Bruno et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B38">Sun et&#xa0;al., 2018</xref>). Fertilization at phenophases and periods of maturation can timely supplement and balance the nutrient demand of coffee organs, and sufficient water supply can simultaneously promote nutrients release, thus promoting nutrient cycling and absorption in plants, accelerating the synthesis of cytokinin, promoting fruit expansion and weight of single fruit (<xref ref-type="bibr" rid="B28">Parvizi and Sepaskhah, 2015</xref>; <xref ref-type="bibr" rid="B27">Liu et&#xa0;al., 2019</xref>). In addition, the vigorous physiological activities and strong photosynthetic capacity of coffee trees at BE may be conducive to the accumulation of photosynthetic products (<xref ref-type="bibr" rid="B37">Silva et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B52">Zhang et&#xa0;al., 2017</xref>). The increase of fertilization at FL can promote the blossom, improve fruit setting rate, accelerate the growth of new shoots, and lay the foundation for the reproductive growth of coffee. We all know that excessive or insufficient fertilization is not conducive to yield production. In this study, FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> simultaneously obtained the maximum WUE and the highest bean yield, indicating that this kind of fertilization pattern met the growth demands of coffee. Therefore, it is necessary to apply fertilizer by period according to crop fertilizer requirement.</p>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>Nutritional components of coffee beans</title>
<p>Soil nutrients can be absorbed and utilized by plants through microbial decomposition and transformation. One-time fertilization is easy to cause the overload operation of soil microorganisms, which may reduce the utilization rate of soil nutrients (<xref ref-type="bibr" rid="B39">Sun et&#xa0;al., 2022</xref>). Fertilization on demand according to crop growth period can improve soil microbial metabolism ability and increase soil nutrient availability, thereby improving fruit nutritional quality (<xref ref-type="bibr" rid="B13">Dinesh et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B35">Sakai et&#xa0;al., 2015</xref>). In addition, drip fertigation can provide accurate application of water and fertilizer, reduce nutrient leaching, well maintain the loose state and porosity of soil, thus improving soil physical and chemical properties (<xref ref-type="bibr" rid="B35">Sakai et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B49">Yan et&#xa0;al., 2021</xref>). In this study, FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> significantly increased the content of ash, total sugar, fat, protein, caffeine and chlorogenic acid compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>. However, FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> significantly decreased the content of ash, total sugar, fat, protein and chlorogenic acid compared with FL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>. On the one hand, split fertilization according to growth period may affect the decomposition and conversion rate of nutrients by soil microorganisms, thus affecting the availability of nutrients (<xref ref-type="bibr" rid="B35">Sakai et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B45">Vinecky et&#xa0;al., 2017</xref>). On the other hand, the BE is the critical period for the formation of nutritional quality of coffee cherry. The amount of fertilizer applied during this period directly affects the nutrient transport and distribution in coffee trees, and the formation and accumulation of photosynthetic products (<xref ref-type="bibr" rid="B52">Zhang et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B38">Sun et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B48">Wu et&#xa0;al., 2019</xref>). It was found that nitrogen fertilizer was closely related to the synthesis of amino acids in fruit. Appropriate amount of nitrogen fertilizer could increase the contents of caffeine, protein and chlorogenic acid and the yield of coffee beans (<xref ref-type="bibr" rid="B46">Wang et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B26">Liu et&#xa0;al., 2016</xref>). Phosphorus is involved in plant photosynthesis and nitrogen absorption and metabolism, and adjusts the proportion of nutrients in plants, thus regulating the content of chlorogenic acid in fruits (<xref ref-type="bibr" rid="B46">Wang et&#xa0;al., 2008</xref>). Potassium fertilizer can enhance enzyme activity in plants, participate in regulating CO<sub>2</sub> fixation in photosynthesis, and promote sugar metabolism and protein synthesis, thus improving fruit quality (<xref ref-type="bibr" rid="B1">Ali et&#xa0;al., 2021</xref>). Therefore, fertilization according to the nutrient requirements of Arabica coffee can coordinate the growth of vegetative organs and reproductive organs, and the accumulation and distribution of assimilates, so as to achieve the purpose of improving the nutrient content of coffee beans.</p>
</sec>
<sec id="s4_4">
<label>4.4</label>
<title>Volatile compounds of roasted beans</title>
<p>In addition to the stimulation effect and the health care function of caffeine, the popularity of coffee is mainly attributed to the unique aroma and flavor of volatile compounds in roasted coffee (<xref ref-type="bibr" rid="B16">Dulsat-Serra et&#xa0;al., 2016</xref>). Furans with sweet, caramel and barbecue tastes are associated with the thermal decomposition of sugars, the Maillard reaction of reducing sugars and amino acids, and the oxidation of polyunsaturated fatty acids (<xref ref-type="bibr" rid="B34">Rocha et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B51">Zakidou et&#xa0;al., 2021</xref>). In this study, the content of different furans varied with roasting degree, which might be related to the decomposition conditions of precursors and the further decomposition of furans with the deepening of roasting degree. <xref ref-type="bibr" rid="B30">Petisca et&#xa0;al. (2014)</xref> found that furfural and its derivatives would further decompose into furoic acid under heating conditions, and then decarboxylated to produce CO<sub>2</sub>. Cluster analysis showed that FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> had high relative content of furans under different roasting degrees, which might be related to the high total sugar and protein content in these two treatments. Correlation analysis results also indicated that total sugar content was positively correlated with furan content. The formation of pyrazines is related to the Maillard reaction and the pyrolysis of amino acids (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>). Pyrazines show attractive coffee or cocoa fragrance, and its third-generation derivatives have barbecue and earthy tastes (<xref ref-type="bibr" rid="B43">Toci and Boldrin, 2018</xref>). The content of pyrazines in the baking process depends on the ratio of amino acids to sugars in the reaction system (<xref ref-type="bibr" rid="B42">Toci et&#xa0;al., 2020</xref>). In this study, pyrazine compounds had high relative content under medium roasting degrees (M), which might be due to the fracture of the six-membered ring of pyrazines under dark roasting degrees (D), resulting in the formation of olefins and then volatilization (<xref ref-type="bibr" rid="B22">Kiefer et&#xa0;al., 1997</xref>). The relative contents of pyrazines in MFL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub>, MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub>, MFL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> and MFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> were higher than that under dark roasting degrees, which might be due to the high protein content in these treatments. Moreover, the high pyrazine content in FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> might be attributed to the defective coffee beans, which resulted in the content of free amino acids far exceeding that of carbohydrates, thus more pyrazines were generated through the Maillard reaction (<xref ref-type="bibr" rid="B42">Toci et&#xa0;al., 2020</xref>). Correlation analysis found that pyrazine content was positively correlated with total sugar and protein content, which further explained the relationship among the three substances. The formation of ketones is related to Maillard reaction or Strecker degradation (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B42">Toci et&#xa0;al., 2020</xref>). The high content of ketones in FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> might be related to the high protein content. Acids affect the flavor and taste of coffee, and tend to decompose at high temperature. The high content of acids in MFL<sub>250</sub>BE<sub>250</sub>BR<sub>250</sub>, MFL<sub>150</sub>BE<sub>250</sub>BR<sub>350</sub> and MFL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> might be closely related to the nutrient content and defective beans in coffee (<xref ref-type="bibr" rid="B42">Toci et&#xa0;al., 2020</xref>). Many studies have shown that the precursors of green coffee beans are closely related to the flavor compounds of roasted coffee (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B20">Hu et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B51">Zakidou et&#xa0;al., 2021</xref>). This study found that there were differences in coffee volatile compounds among different treatments. The main reason may be that fertilization amount at different periods affected the tree growth and physiological activity, which changed the nutritional components of beans.</p>
</sec>
<sec id="s4_5">
<label>4.5</label>
<title>Cup quality of roasted beans</title>
<p>Cup quality directly affects the price of coffee. A high-quality cup is a balanced combination of flavor, body and aroma (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>). Due to the cultivar, growing environment, processing method and roasting degree, the composition and content of coffee are different, which directly affects the taste, aroma, color and quality of roasted coffee. In this study, the high scores of coffee aroma, acidity and balance of medium roasted beans might be related to the ketones and acids generated by proteins and sugars under medium roasting degrees. The correlation analysis indicated that protein content was positively correlated with ketone content, and sugar content was positively correlated with coffee aroma and acidity score. In addition to being a sweet substance, sugar is also conducive to the formation of coffee aroma and flavor (<xref ref-type="bibr" rid="B40">Sunarharum et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B51">Zakidou et&#xa0;al., 2021</xref>). It has been found that coffee cups with high sugar content also have high quality (<xref ref-type="bibr" rid="B2">Barbosa et&#xa0;al., 2019</xref>). The body score of coffee under dark roasting degrees was higher than that under medium roasting degrees, which might be related to the increasing fat content under dark roasting degrees. <xref ref-type="bibr" rid="B44">Vasconcelos et&#xa0;al. (2007)</xref> found that the maximum fat content of Arabica during the baking process was 11.18% higher than that of green coffee beans. Correlation analysis showed that fat content was positive correlation with body score. The release of volatile compounds such as aldehydes, ketones and alcohols from fat during baking process affects the body of coffee, thereby influencing the cup quality (<xref ref-type="bibr" rid="B2">Barbosa et&#xa0;al., 2019</xref>). Only the quality score of FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> was below 80.00 under different roasting degrees. This might be due to the low total sugar and fat content of some green beans, which led to the fact that various volatile substances of roasted coffee beans did not reach the equilibrium point, thus affecting the cup quality.</p>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusions</title>
<p>Increasing fertilization ratio at FL and BE obviously improved the average <italic>A</italic>
<sub>net</sub>, <italic>T</italic>
<sub>r</sub>, <italic>g</italic>
<sub>s</sub> and CE. FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> significantly increased bean yield, WUE and PFP, while FL<sub>250</sub>BE<sub>150</sub>BR<sub>350</sub> and FL<sub>350</sub>BE<sub>150</sub>BR<sub>250</sub> significantly decreased those indexes. FL<sub>150</sub>BE<sub>350</sub>BR<sub>250</sub> and FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> increased contents of total sugar, fat, protein, caffeine and chlorogenic acid compared with other treatments. Medium roasted coffee beans contained high levels of acids and pyrazines, while dark roasted coffee beans contained high levels of pyrroles, pyridines, phenols, alcohols, aldehydes and other compounds. MFL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> and DFL<sub>350</sub>BE<sub>250</sub>BR<sub>150</sub> obtained the highest total cup score. Correlation analysis showed that bean nutrient contents were closely related to volatile and cup quality. The TOPSIS indicated that FL<sub>250</sub>BE<sub>350</sub>BR<sub>150</sub> was the best fertilization mode. The experiment can provide some practical reference for coffee cultivation. Further study may focus on the relationship between soil environment and coffee quality and volatile components.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>RL: Investigation, Formal Analysis, Visualization, Writing Original Draft. JC: Investigation, Formal Analysis, Visualization. XL: Conceptualization, Methodology, Writing Review and Editing, supervision. ZW: Writing Review and Editing, Visualization. HL: Resources, Writing Review and Editing. JG: Methodology, Writing Review and Editing. HW: Methodology, Writing Review and Editing. NC: Conceptualization, Methodology, Writing Review and Editing, supervision. LZ: Writing Review and Editing, supervision. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This study was supported by the National Natural Science Foundation of China (No. 51979133, 51922072, 52279041), Sichuan Science and Technology Program (No. 2022YFQ0082) and Yunnan Fundamental Research Projects (grant NO. 202301AS070030).</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpls.2023.1148616/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpls.2023.1148616/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.xlsx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="DataSheet_2.xlsx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
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