[1] 王苗苗. 响应柑橘黄龙病的MAPK基因和PR基因鉴定及遗传转化[D].重庆:西南大学, 2018.
WANG M M.Identification and genetic transformation of citrus MAPK genes and PR genes induced by Huanglongbing[D].Chongqing:Southwest University, 2018.
[2] 易图永, 王运生, 谭小平, 等.柑橘主要病害成灾机理及绿色防控关键技术与应用[J].中国科技成果, 2020(20):11-13.
YI T Y, WANG Y S, TAN X P, et al.Disaster mechanism of main citrus diseases and key technologies and applications of green prevention and control[J].China Science and Technology Achievements, 2020(20):11-13.
[3] 尤有利, 彭抒昂, 邓秀新, 等.柑橘黄龙病防控"永春模式"构建与示范推广[J].中国科技成果, 2020, 21(8):26-27.
YOU Y L, PENG S A, DENG X X, et al.Construction and demonstration of "Yongchun model" for the prevention and control of citrus greening disease[J].China’s Scientific and Technological Achievements, 21(8):26-27.
[4] LADANIYA M.Nutritive and Medicinal Value of Citrus Fruits[M]//Citrus Fruit.Amsterdam:Elsevier, 2023:693-720.
[5] 温成韬. 中国水果竞争力国际比较分析[J].现代营销, 2020, (12):106-108.
WEN C T.International Comparative analysis of Chinese fruit competitiveness[J].Modern Marketing, 2020, (12):106-108.
[6] ZACARIAS L, CRONJE P J R, PALOU L.Postharvest Technology of Citrus Fruits.In The Genus Citrus[M], 2020, 421-446.
[7] IQBAL Z, KHAN M A, SHARIF M, et al.An automated detection and classification of citrus plant diseases using image processing techniques:A review[J].Computers and Electronics in Agriculture, 2018, 153:12-32.
[8] JIANG Q Y, ZHANG M, XU B G.Application of ultrasonic technology in postharvested fruits and vegetables storage:A review[J].Ultrasonics Sonochemistry, 2020, 69:105261.
[9] WEN T, ZHENG L Z, DONG S, et al.Rapid detection and classification of citrus fruits infestation by Bactrocera dorsalis (Hendel) based on electronic nose[J].Postharvest Biology and Technology, 2019, 147:156-165.
[10] SUN Q, ZHANG M, YANG P Q.Combination of LF-NMR and BP-ANN to monitor water states of typical fruits and vegetables during microwave vacuum drying[J].LWT, 2019, 116:108548.
[11] LUO W, FAN G Z, TIAN P, et al.Spectrum classification of citrus tissues infected by fungi and multispectral image identification of early rotten oranges[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2022, 279:121412.
[12] POREP J U, KAMMERER D R, CARLE R.On-line application of near infrared (NIR) spectroscopy in food production[J].Trends in Food Science & Technology, 2015, 46(2):211-230.
[13] PASQUINI C.Near infrared spectroscopy:A mature analytical technique with new perspectives: A review[J].Analytica Chimica Acta, 2018, 1026:8-36.
[14] ALISHAHI A, FARAHMAND H, PRIETO N, et al.Identification of transgenic foods using NIR spectroscopy:A review[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2010, 75(1):1-7.
[15] ZHANG D, ZHAO Z F, ZHANG S Y, et al.Accurate identification of soluble solid content in citrus by indirect laser-induced breakdown spectroscopy with its leaves[J].Microchemical Journal, 2021, 169:106530.
[16] HIJAZ F, GMITTER F G Jr, BAI J H, et al.Effect of fruit maturity on volatiles and sensory descriptors of four mandarin hybrids[J].Journal of Food Science, 2020, 85(5):1548-1564.
[17] MOLTÓ E, BLASCO J.Quality Evaluation of Citrus Fruits[M]//Computer Vision Technology for Food Quality Evaluation.Amsterdam:Elsevier, 2008:243-264.
[18] FU X P, WANG X Y, RAO X Q.An LED-based spectrally tuneable light source for visible and near-infrared spectroscopy analysis:A case study for sugar content estimation of citrus[J].Biosystems Engineering, 2017, 163:87-93.
[19] 汪小耀. 基于LED光源的柑橘糖度可见/近红外光谱检测研究[D].杭州:浙江大学, 2017.
WANG X Y.Study on visible/near infrared spectrum detection of citrus sugar content based on LED light source[D].Hangzhou:Zhejiang University, 2017.
[20] CAVACO A M, PIRES R, ANTUNES M D, et al.Validation of short wave near infrared calibration models for the quality and ripening of ‘Newhall’ orange on tree across years and orchards[J].Postharvest Biology and Technology, 2018, 141:86-97.
[21] THEANJUMPOL P, WONGZEEWASAKUN K, MUENMANEE N, et al.Non-destructive identification and estimation of granulation in ‘Sai Num Pung’ tangerine fruit using near infrared spectroscopy and chemometrics[J].Postharvest Biology and Technology, 2019, 153:13-20.
[22] TIAN X, LI J B, YI S L, et al.Nondestructive determining the soluble solids content of citrus using near infrared transmittance technology combined with the variable selection algorithm[J].Artificial Intelligence in Agriculture, 2020, 4:48-57.
[23] PIRES R, GUERRA R, CRUZ S P, et al.Ripening assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) on tree by SW-NIR reflectance spectroscopy-based calibration models[J].Postharvest Biology and Technology, 2022, 183:111750.
[24] 韩龙波. 柑橘光谱信息感知参数化平台设计及糖度无损检测研究[D].长沙:中南林业科技大学,2021.
HAN L B.Research on the design of citrus spectral information perception parameterized platform and nondestructive testing of sugar content[D].Changshao:Central South University of Forestry and Technology, 2021.
[25] HUANG C J, CAI J R, ZHOU Y, et al.Fusion models for detection of soluble solids content in mandarin by Vis/NIR transmission spectroscopy combined external factors[J].Infrared Physics & Technology, 2022, 124:104233.
[26] KIM S Y, HONG S J, KIM E, et al.Application of ensemble neural-network method to integrated sugar content prediction model for citrus fruit using VIS/NIR spectroscopy[J].Journal of Food Engineering, 2023, 338:111254.
[27] NCAMA K, OPARA U L, TESFAY S Z, et al.Application of Vis/NIR spectroscopy for predicting sweetness and flavour parameters of ‘Valencia’ orange (Citrus sinensis) and ‘Star Ruby’ grapefruit (Citrus x paradisi Macfad)[J].Journal of Food Engineering, 2017, 193:86-94.
[28] BIZZANI M, FLORES D W M, COLNAGO L A, et al.Non-invasive spectroscopic methods to estimate orange firmness, peel thickness, and total pectin content[J].Microchemical Journal, 2017, 133:168-174.
[29] TORRES I, PÉREZ-MARÍN D, DE LA HABA M J, et al.Developing universal models for the prediction of physical quality in citrus fruits analysed on-tree using portable NIRS sensors[J].Biosystems Engineering, 2017, 153:140-148.
[30] 王旭. 冰糖橙可溶性固形物和pH值近红外光谱检测[J].食品研究与开发, 2017, 38(3):143-146.
WANG X.Detecting of soluble solid content and pH of Bingtang orange by near-infrared spectroscopy[J].Food Research and Development, 2017, 38(3):143-146.
[31] 孙通, 莫欣欣, 刘木华.果皮对脐橙可溶性固形物可见/近红外检测精度的影响[J].光谱学与光谱分析, 2018, 38(5):1406-1411.
SUN T, MO X X, LIU M H.Effect of pericarp on prediction accuracy of soluble solid content in navel oranges by visible/near-infrared spectroscopy[J].Spectroscopy and spectral Analysis, 2018, 38(5):1406-1411.
[32] 刘燕德, 饶宇, 孙旭东, 等.尺寸差异对脐橙糖度可见近红外光谱检测模型影响[J].光谱学与光谱分析, 2020, 40(10):3241-3246.
LIU Y D, YAO Y, SUN X D, et al.Size effect on the near-infrared spectroscopy detection model of navel orange[J].Spectroscopy and spectral Analysis,2020, 40(10):3241-3246.
[33] SONG J, LI G L, YANG X D, et al.Rapid analysis of soluble solid content in navel orange based on visible-near infrared spectroscopy combined with a swarm intelligence optimization method[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2020, 228:117815.
[34] HAO Y, WANG Q M, ZHANG S M.Online accurate detection of soluble solids content in navel orange assisted by automatic orientation correction device[J].Infrared Physics & Technology, 2021, 118:103871.
[35] CHEN H Z, LIN B, CAI K, et al.Quantitative analysis of organic acids in pomelo fruit using FT-NIR spectroscopy coupled with network kernel PLS regression[J].Infrared Physics & Technology, 2021, 112:103582.
[36] 孙潇鹏, 刘灿灿, 陆华忠, 等.基于可见-近红外透射光谱的蜜柚检测中影响因素分析[J].包装与食品机械, 2022, 40(4):1-7.
SUN X P, LIU C C, LU H Z, et al.Analysis of influencing factors in the detection of honey pomelo based on visible-near infrared transmittance spectroscopy[J].Packaging and Food Machinery, 2022, 40(4):1-7.
[37] TIAN H, XU H R, YING Y B.Can light penetrate through pomelos and carry information for the non-destructive prediction of soluble solid content using VIS-NIRS?[J].Biosystems Engineering, 2022, 214:152-164.
[38] GRAHAM J, FEICHTENBERGER E.Citrus phytophthora diseases:Management challenges and successes[J].Journal of Citrus Pathology, 2015, 2(1):1-11.
[39] MAGWAZA L S, OPARA U L, CRONJE P, et al.Nonchilling physiological rind disorders in citrus fruit:A review[J].Horticultural Reviews, 2013, 41(41):131-176.
[40] GHOOSHKHANEH G N, GOLZARIAN M R, MOLLAZADE K.VIS-NIR spectroscopy for detection of citrus core rot caused by Alternaria alternata[J].Food Control, 2023, 144:109320.
[41] 李轶凡. 水果缺陷和内部品质同时在线检测方法研究[D].南昌:华东交通大学, 2016.
LI Y F.Simultaneous and online detection of fruit defect and internal quality based on visible-near infared tranmittance spectroscopy[D].Nanchang:East China Jiaotong University, 2016.
[42] NCAMA K, TESFAY S Z, FAWOLE O A, et al.Non-destructive prediction of ‘Marsh’ grapefruit susceptibility to postharvest rind pitting disorder using reflectance VIS/NIR spectroscopy[J].Scientia Horticulturae, 2018, 231:265-271.
[43] MOOMKESH S, AHMAD MIREEI S, SADEGHI M, et al.Early detection of freezing damage in sweet lemons using Vis/SWNIR spectroscopy[J].Biosystems Engineering, 2017, 164:157-170.
[44] TIAN S, WANG S, XU H R.Early detection of freezing damage in oranges by online Vis/NIR transmission coupled with diameter correction method and deep 1D-CNN[J].Computers and Electronics in Agriculture, 2022, 193:106638.
[45] AFONSO A M, GUERRA R, CAVACO A M, et al.Identification of asymptomatic plants infected with Citrus tristeza virus from a time series of leaf spectral characteristics[J].Computers and Electronics in Agriculture, 2017, 141:340-350.
[46] 贺胜晖, 李灵巧, 刘彤, 等.柑橘黄龙病检测的近红外光谱集成建模方法[J].分析科学学报, 2020, 36(2):287-290.
HE S H, LI L Q, LIU T, et al.Near-infrared spectroscopy based ensemble modeling method for Huanglongbing detection[J].Journal of Analytical Science, 2020, 36(2):287-290.
[47] 但松健. 基于NIR光谱分析的柑橘产地鉴别及品质检测技术研究[D].重庆:重庆大学,2017.
DAN S J.A study on determination of the geographical origins and internal qualities of oranges based on NIR spectroscopy analysis[D].Chongqing:Chongqing University, 2017.
[48] 李尚科. 柑橘类水果和陈皮光学无损检测及软件开发[D].长沙:湖南农业大学,2020.
LI S K.Optical nondestructive analysis of citrus and citri reticulatae pericarpium and software development[D].Changsha:Hunan Agricultural University, 2020.
[49] 姚婉清, 彭梦侠, 刘婷.梅州金柚品种的近红外无损鉴别[J].食品研究与开发, 2019, 40(11):166-169.
YAO W Q, PENG M X, LIU T.Nondestructive identification of golden pomelo varieties in Meizhou based on near infrared spectroscopy[J].Food Research and Development, 2019, 40(11):166-169.
[50] RUGGIERO L, AMALFITANO C, DI VAIO C, et al.Use of near-infrared spectroscopy combined with chemometrics for authentication and traceability of intact lemon fruits[J].Food Chemistry, 2022, 375:131822.
[51] ZHANG Y, LEE W S, LI M Z, et al.Non-destructive recognition and classification of citrus fruit blemishes based on ant colony optimized spectral information[J].Postharvest Biology and Technology, 2018, 143:119-128.
[52] 孙潇鹏, 刘灿灿, 陆华忠, 等.基于近红外透射光谱与机器视觉的蜜柚汁胞粒化分级检测[J].食品科学技术学报, 2021, 39(1):37-45.
SUN X P, LIU C C, LU H Z, et al.Detection of honey pomelo in different granulation levels based on near-infrared transmittance spectroscopy combined with machine vision[J].Journal of Food Science and Technology, 2021, 39(1):37-45.
[53] GAO Z, GAO W, ZENG S L, et al.Chemical structures, bioactivities and molecular mechanisms of citrus polymethoxyflavones[J].Journal of Functional Foods, 2018, 40:498-509.
[54] SHI Y S, ZHANG Y, LI H T, et al.Limonoids from citrus:Chemistry, anti-tumor potential, and other bioactivities[J].Journal of Functional Foods, 2020, 75:104213.
[55] LIU N, LI X, ZHAO P, et al.A review of chemical constituents and health-promoting effects of citrus peels[J].Food Chemistry, 2021, 365:130585.
[56] COSTA R, ALBERGAMO A, ARRIGO S, et al.Solid-phase microextraction-gas chromatography and ultra-high performance liquid chromatography applied to the characterization of lemon wax, a waste product from citrus industry[J].Journal of Chromatography A, 2019, 1603:262-268.
[57] DADWAL V, JOSHI R, GUPTA M.A comparative metabolomic investigation in fruit sections of Citrus medica L.and Citrus maxima L.detecting potential bioactive metabolites using UHPLC-QTOF-IMS[J].Food Research International, 2022, 157:111486.
[58] ZHENG H, ZHEN X T, CHEN Y, et al.In situ antioxidation-assisted matrix solid-phase dispersion microextraction and discrimination of chiral flavonoids from citrus fruit via ion mobility quadrupole time-of-flight high-resolution mass spectrometry[J].Food Chemistry, 2021, 343:128422.
[59] OLAREWAJU O O, MAGWAZA L S, NIEUWOUDT H, et al.Model development for non-destructive determination of rind biochemical properties of ‘Marsh’ grapefruit using visible to near-infrared spectroscopy and chemometrics[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2019, 209:62-69.
[60] SHAWKY E, SELIM D A.NIR spectroscopy-multivariate analysis for discrimination and bioactive compounds prediction of different citrus species peels[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2019, 219:1-7.