[1]

Garcia-Mas J, Benjak A, Sanseverino W, Bourgeois M, Mir G, et al. 2012. The genome of melon (Cucumis melo L.). Proceedings of the National Academy of Sciences of the United States of America 109:11872−77

doi: 10.1073/pnas.1205415109
[2]

Jeffrey C. 1980. A review of the Cucurbitaceae. Botanical Journal of the Linnean Society 81:233−47

doi: 10.1111/j.1095-8339.1980.tb01676.x
[3]

Fergany M, Kaur B, Monforte AJ, Pitrat M, Rys C, et al. 2011. Variation in melon (Cucumis melo) landraces adapted to the humid tropics of southern India. Genetic Resources and Crop Evolution 58:225−43

doi: 10.1007/s10722-010-9564-6
[4]

Kesh H, Kaushik P. 2021. Advances in melon (Cucumis melo L.) breeding: an update. Scientia Horticulturae 282:110045

doi: 10.1016/j.scienta.2021.110045
[5]

Eitenmiller RR, Johnson CD, Bryan WD, Warren DB, Gebhardt SE. 1985. Nutrient composition of cantaloupe and honeydew melons. Journal of Food Science 50:136−38

doi: 10.1111/j.1365-2621.1985.tb13294.x
[6]

Lester G. 1997. Melon (Cucumis melo L.) fruit nutritional quality and health functionality. HortTechnology 7:222−27

doi: 10.21273/HORTTECH.7.3.222
[7]

Manchali S, Murthy KNC. 2020. Muskmelon. In Nutritional Composition and Antioxidant Properties of Fruits and Vegetables, ed. Jaiswal AK. US: Academic Press. pp. 533−46. doi: 10.1016/B978-0-12-812780-3.00033-7

[8]

Goutzourelas N, Stagos D, Spanidis Y, Liosi M, Apostolou A, et al. 2015. Polyphenolic composition of grape stem extracts affects antioxidant activity in endothelial and muscle cells. Molecular Medicine Reports 12:5846−56

doi: 10.3892/mmr.2015.4216
[9]

Rahman MM, Hossain ASMS, Mostofa MG, Khan MA, Ali R, et al. 2019. Evaluation of anti-ROS and anticancer properties of Tabebuia pallida L. leaves. Clinical Phytoscience 5:17

doi: 10.1186/s40816-019-0111-5
[10]

Ismail HI, Chan KW, Mariod AA, Ismail M. 2010. Phenolic content and antioxidant activity of cantaloupe (Cucumis melo) methanolic extracts. Food Chemistry 119:643−47

doi: 10.1016/j.foodchem.2009.07.023
[11]

Bouaziz A, Djidel S, Assia B, Khennouf S. 2020. Polyphenolic content, antioxidant and anti-inflammatory activities of melon (Cucumis melo L. var. inodorus) seeds. Journal of Drug Delivery and Therapeutics 10:22−26

[12]

Rolim PM, Fidelis GP, Padilha CEA, Santos ES, Rocha HAO, et al. 2018. Phenolic profile and antioxidant activity from peels and seeds of melon (Cucumis melo L. var. reticulatus) and their antiproliferative effect in cancer cells. Revista Brasileira de Pesquisas Medicas e Biologicas 51:e6069

[13]

Wright CI, Van-Buren L, Kroner CI, Koning MMG. 2007. Herbal medicines as diuretics: a review of the scientific evidence. Journal of Ethnopharmacology 114:1−31

doi: 10.1016/j.jep.2007.07.023
[14]

Gill NS, Bajwa J, Dhiman K, Sharma P, Sood S, et al. 2011. Evaluation of therapeutic potential of traditionally consumed Cucumis melo seeds. Asian Journal of Plant Sciences 10:86−91

doi: 10.3923/ajps.2011.86.91
[15]

Parmar HS, Kar A. 2009. Protective role of Mangifera indica, Cucumis melo and Citrullus vulgaris peel extracts in chemically induced hypothyroidism. Chemico-Biological Interactions 177:254−58

doi: 10.1016/j.cbi.2008.11.006
[16]

Décordé K, Ventura E, Lacan D, Ramos J, Cristol JP, et al. 2010. An SOD rich melon extract Extramel® prevents aortic lipids and liver steatosis in diet-induced model of atherosclerosis. Nutrition, Metabolism and Cardiovascular Diseases 20:301−7

doi: 10.1016/j.numecd.2009.04.017
[17]

Naito Y, Akagiri S, Uchiyama K, Kokura S, Yoshida N, et al. 2005. Reduction of diabetes-induced renal oxidative stress by a cantaloupe melon extract/gliadin biopolymers, oxykine, in mice. BioFactors 23:85−95

doi: 10.1002/biof.5520230204
[18]

Chan KT, Li K, Liu SL, Chu KH, Toh M, et al. 2010. Cucurbitacin B inhibits STAT3 and the Raf/MEK/ERK pathway in leukemia cell line K562. Cancer Letters 289:46−52

doi: 10.1016/j.canlet.2009.07.015
[19]

Ibrahim SRM. 2010. New 2-(2-phenylethyl)chromone derivatives from the seeds of Cucumis melo L var. reticulatus. Natural Product Communications 5:403−6

[20]

Zinchenko TV, Mindlin MZ, Prokopovich NN. 1955. Anthelmintic properties of Cucumis melo seeds. Farmakologiia i Toksikologiia 18:41−43

[21]

Liu S, Gao P, Zhu Q, Zhu Z, Liu H, et al. 2020. Resequencing of 297 melon accessions reveals the genomic history of improvement and loci related to fruit traits in melon. Plant Biotechnology Journal 18:2545−58

doi: 10.1111/pbi.13434
[22]

Soller M, Brody T, Genizi A. 1976. On the power of experimental designs for the detection of linkage between marker loci and quantitative loci in crosses between inbred lines. Theoretical and Applied Genetics 47:35−39

doi: 10.1007/BF00277402
[23]

Komala M, Kuni P. 2022. Genetic diversity and molecular breeding of melon (Cucumis melo L.): a review. Current Agriculture Research Journal 10:181−92

doi: 10.12944/CARJ.10.3.03
[24]

Díaz A, Zarouri B, Fergany M, Eduardo I, Alvarez JM, et al. 2014. Mapping and introgression of QTL involved in fruit shape transgressive segregation into 'piel de sapo' melon (Cucumis melo L.). PLoS One 9:e104188

doi: 10.1371/journal.pone.0104188
[25]

Amanullah S, Liu S, Gao P, Zhu Z, Zhu Q, et al. 2018. QTL mapping for melon (Cucumis melo L.) fruit traits by assembling and utilization of novel SNPs based CAPS markers. Scientia Horticulturae 236:18−29

doi: 10.1016/j.scienta.2018.02.041
[26]

Ruggieri V, Alexiou KG, Morata J, Argyris J, Pujol M, et al. 2018. An improved assembly and annotation of the melon (Cucumis melo L.) reference genome. Scientific Reports 8:8088

doi: 10.1038/s41598-018-26416-2
[27]

Zhao G, Lian Q, Zhang Z, Fu Q, He Y, et al. 2019. A comprehensive genome variation map of melon identifies multiple domestication events and loci influencing agronomic traits. Nature Genetics 51:1607−15

doi: 10.1038/s41588-019-0522-8
[28]

Huang S, Li R, Zhang Z, Li L, Gu X, et al. 2009. The genome of the cucumber, Cucumis sativus L. Nature Genetics 41:1275−81

doi: 10.1038/ng.475
[29]

Bo K, Wei S, Wang W, Miao H, Dong S, et al. 2019. QTL mapping and genome-wide association study reveal two novel loci associated with green flesh color in cucumber. BMC Plant Biology 19:243

doi: 10.1186/s12870-019-1835-6
[30]

Wang X, Bao K, Reddy UK, Bai Y, Hammar SA, et al. 2018. The USDA cucumber (Cucumis sativus L.) collection: genetic diversity, population structure, genome-wide association studies, and core collection development. Horticulture Research 5:64

doi: 10.1038/s41438-018-0080-8
[31]

Liu H, Jiao J, Liang X, Liu J, Meng H, et al. 2016. Map-based cloning, identification and characterization of the w gene controlling white immature fruit color in cucumber (Cucumis sativus L.). Theoretical and Applied Genetics 129:1247−56

doi: 10.1007/s00122-016-2700-8
[32]

Fan S, Yang S, Shi K, Yang L, An M, et al. 2024. Genome-wide identification of the LRX gene family in Cucurbitaceae and expression analysis under salt and drought stress in cucumber. Vegetable Research 4:e026

doi: 10.48130/vegres-0024-0025
[33]

Zhang H, Li X, Yu H, Zhang Y, Li M, et al. 2019. A high-quality melon genome assembly provides insights into genetic basis of fruit trait improvement. iScience 22:16−27

doi: 10.1016/j.isci.2019.10.049
[34]

Yang J, Deng G, Lian J, Garraway J, Niu Y, et al. 2020. The chromosome-scale genome of melon dissects genetic architecture of important agronomic traits. iScience 23:101422

doi: 10.1016/j.isci.2020.101422
[35]

Yano R, Ariizumi T, Nonaka S, Kawazu Y, Zhong S, et al. 2020. Comparative genomics of muskmelon reveals a potential role for retrotransposons in the modification of gene expression. Communications Biology 3:432

doi: 10.1038/s42003-020-01172-0
[36]

Oren E, Tzuri G, Dafna A, Rees ER, Song B, et al. 2022. QTL mapping and genomic analyses of earliness and fruit ripening traits in a melon Recombinant Inbred Lines population supported by de novo assembly of their parental genomes. Horticulture Research 9:uhab081

doi: 10.1093/hr/uhab081
[37]

Lyu X, Xia Y, Wang C, Zhang K, Deng G, et al. 2023. Pan-genome analysis sheds light on structural variation-based dissection of agronomic traits in melon crops. Plant Physiology 193:1330−48

doi: 10.1093/plphys/kiad405
[38]

Li G, Tang L, He Y, Xu Y, Bendahmane A, et al. 2023. The haplotype-resolved T2T reference genome highlights structural variation underlying agronomic traits of melon. Horticulture Research 10:uhad182

doi: 10.1093/hr/uhad182
[39]

Nordborg M, Weigel D. 2008. Next-generation genetics in plants. Nature 456:720−23

doi: 10.1038/nature07629
[40]

Zhao H, Zhang T, Meng X, Song J, Zhang C, et al. 2023. Genetic mapping and QTL analysis of fruit traits in melon (Cucumis melo L.). Current Issues in Molecular Biology 45:3419−33

doi: 10.3390/cimb45040224
[41]

Sun Y, Wang J, Li Y, Jiang B, Wang X, et al. 2022. Pan-genome analysis reveals the abundant gene presence/absence variations among different varieties of melon and their influence on traits. Frontiers in Plant Science 13:835496

doi: 10.3389/fpls.2022.835496
[42]

Du X, Liu H, Zhu Z, Liu S, Song Z, et al. 2022. Identification of candidate chromosome region related to melon (Cucumis melo L.) fruit surface groove trait through biparental genetic mapping and genome-wide association study. Frontiers in Plant Science 13:828287

doi: 10.3389/fpls.2022.828287
[43]

Hou J, Zhou YF, Gao LY, Wang YL, Yang LM, et al. 2018. Dissecting the genetic architecture of melon chilling tolerance at the seedling stage by association mapping and identification of the elite alleles. Frontiers in Plant Science 9:1577

doi: 10.3389/fpls.2018.01577
[44]

Wei M, Huang Y, Mo C, Wang H, Zeng Q, et al. 2023. Telomere-to-telomere genome assembly of melon (Cucumis melo L. var. inodorus) provides a high-quality reference for meta-QTL analysis of important traits. Horticulture Research 10:uhad189

doi: 10.1093/hr/uhad189
[45]

Ma J, Li C, Zong M, Qiu Y, Liu Y, et al. 2022. CmFSI8/CmOFP13 encoding an OVATE family protein controls fruit shape in melon. Journal of Experimental Botany 73:1370−84

doi: 10.1093/jxb/erab510
[46]

Pereira L, Santo Domingo M, Ruggieri V, Argyris J, Phillips MA, et al. 2020. Genetic dissection of climacteric fruit ripening in a melon population segregating for ripening behavior. Horticulture Research 7:187

doi: 10.1038/s41438-020-00411-z
[47]

Li C, Dong S, Beckles DM, Liu X, Guan J, et al. 2023. GWAS reveals novel loci and identifies a pentatricopeptide repeat-containing protein (CsPPR) that improves low temperature germination in cucumber. Frontiers in Plant Science 14:1116214

doi: 10.3389/fpls.2023.1116214
[48]

Li N, Lin B, Wang H, Li X, Yang F, et al. 2019. Natural variation in ZmFBL41 confers banded leaf and sheath blight resistance in maize. Nature Genetics 51:1540−48

doi: 10.1038/s41588-019-0503-y
[49]

Ban D, Goreta S, Borošić J. 2006. Plant spacing and cultivar affect melon growth and yield components. Scientia Horticulturae 109:238−43

doi: 10.1016/j.scienta.2006.04.015
[50]

Zalapa JE, Staub JE, McCreight JD. 2006. Generation means analysis of plant architectural traits and fruit yield in melon. Plant Breeding 125:482−87

doi: 10.1111/j.1439-0523.2006.01273.x
[51]

Liu S, Raman H, Xiang Y, Zhao C, Huang J, et al. 2022. De novo design of future rapeseed crops: challenges and opportunities. The Crop Journal 10:587−96

doi: 10.1016/j.cj.2022.05.003
[52]

Schauer N, Semel Y, Roessner U, Gur A, Balbo I, et al. 2006. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nature Biotechnology 24:447−54

doi: 10.1038/nbt1192
[53]

Zhang T, Ding Z, Liu J, Qiu B, Gao P. 2020. QTL mapping of pericarp and fruit-related traits in melon (Cucumis melo L.) using SNP-derived CAPS markers. Scientia Horticulturae 265:109243

doi: 10.1016/j.scienta.2020.109243
[54]

Fukuoka S, Saka N, Mizukami Y, Koga H, Yamanouchi U, et al. 2015. Gene pyramiding enhances durable blast disease resistance in rice. Scientific Reports 5:7773

doi: 10.1038/srep07773
[55]

Yasuda N, Mitsunaga T, Hayashi K, Koizumi S, Fujita Y. 2015. Effects of pyramiding quantitative resistance genes pi21, Pi34, and Pi35 on rice leaf blast disease. Plant Disease 99:904−9

doi: 10.1094/PDIS-02-14-0214-RE
[56]

Shamsudin NAA, Swamy BPM, Ratnam W, Sta Cruz MT, Sandhu N, et al. 2016. Pyramiding of drought yield QTLs into a high quality Malaysian rice cultivar MRQ74 improves yield under reproductive stage drought. Rice 9:21

doi: 10.1186/s12284-016-0093-6
[57]

Tsilo TJ, Kolmer JA, Anderson JA. 2014. Molecular mapping and improvement of leaf rust resistance in wheat breeding lines. Phytopathology 104:865−70

doi: 10.1094/PHYTO-10-13-0276-R
[58]

Pierik R, Ballaré CL. 2021. Control of plant growth and defense by photoreceptors: from mechanisms to opportunities in agriculture. Molecular Plant 14:61−76

doi: 10.1016/j.molp.2020.11.021
[59]

Mendlinger S. 1994. Effect of increasing plant density and salinity on yield and fruit quality in muskmelon. Scientia Horticulturae 57:41−49

doi: 10.1016/0304-4238(94)90033-7
[60]

Yao H, Zhang Y, Yi X, Hu Y, Luo H, et al. 2015. Plant density alters nitrogen partitioning among photosynthetic components, leaf photosynthetic capacity and photosynthetic nitrogen use efficiency in field-grown cotton. Field Crops Research 184:39−49

doi: 10.1016/j.fcr.2015.09.005
[61]

Wang P, Wang Z, Sun X, Mu X, Chen H, et al. 2019. Interaction effect of nitrogen form and planting density on plant growth and nutrient uptake in maize seedlings. Journal of Integrative Agriculture 18:1120−29

doi: 10.1016/S2095-3119(18)61977-X
[62]

Duan Y, Li H, Amanullah S, Bao X, Guo Y, et al. 2023. A single nucleotide mutation in ClphyB gene is associated with a short lateral branch phenotype in watermelon. Scientia Horticulturae 321:112378

doi: 10.1016/j.scienta.2023.112378
[63]

Yusuf AF, Wibowo WA, Subiastuti AS, Daryono BS. 2020. Morphological studies of stability and identity of melon (Cucumis melo L.) 'Hikapel' and comparative cultivars. AIP Conference Proceedings 2260:030006

doi: 10.1063/5.0017606
[64]

Bharathkumar N, Sunil A, Meera P, Aksah S, Kannan M, et al. 2022. CRISPR/Cas-based modifications for therapeutic applications: a review. Molecular Biotechnology 64:355−72

doi: 10.1007/s12033-021-00422-8
[65]

Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, et al. 2012. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337:816−21

doi: 10.1126/science.1225829
[66]

Anzalone AV, Randolph PB, Davis JR, Sousa AA, Koblan LW, et al. 2019. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576:149−57

doi: 10.1038/s41586-019-1711-4
[67]

Nuñez JK, Chen J, Pommier GC, Cogan JZ, Replogle JM, et al. 2021. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell 184:2503−2519.e17

doi: 10.1016/j.cell.2021.03.025
[68]

Wang Y, Cheng X, Shan Q, Zhang Y, Liu J, et al. 2014. Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nature Biotechnology 32:947−51

doi: 10.1038/nbt.2969
[69]

Bai Y, Pavan S, Zheng Z, Zappel NF, Reinstädler A, et al. 2008. Naturally occurring broad-spectrum powdery mildew resistance in a Central American tomato accession is caused by loss of mlo function. Molecular Plant-Microbe Interactions 21:30−39

doi: 10.1094/MPMI-21-1-0030
[70]

Nekrasov V, Wang C, Win J, Lanz C, Weigel D, et al. 2017. Rapid generation of a transgene-free powdery mildew resistant tomato by genome deletion. Scientific Reports 7:482

doi: 10.1038/s41598-017-00578-x
[71]

Zheng Z, Nonomura T, Appiano M, Pavan S, Matsuda Y, et al. 2013. Loss of function in Mlo orthologs reduces susceptibility of pepper and tomato to powdery mildew disease caused by Leveillula taurica. PLoS One 8:e70723

doi: 10.1371/journal.pone.0070723
[72]

Liu J, Wu Y, Zhang X, Gill RA, Hu M, et al. 2023. Functional and evolutionary study of MLO gene family in the regulation of Sclerotinia stem rot resistance in Brassica napus L. Biotechnology for Biofuels and Bioproducts 16:86

doi: 10.1186/s13068-023-02325-z
[73]

Guo F, Huang Y, Qi P, Lian G, Hu X, et al. 2021. Functional analysis of auxin receptor OsTIR1/OsAFB family members in rice grain yield, tillering, plant height, root system, germination, and auxinic herbicide resistance. New Phytologist 229:2676−92

doi: 10.1111/nph.17061
[74]

Rodríguez-Leal D, Lemmon ZH, Man J, Bartlett ME, Lippman ZB. 2017. Engineering quantitative trait variation for crop improvement by genome editing. Cell 171:470−480.e8

doi: 10.1016/j.cell.2017.08.030
[75]

Pan W, Cheng Z, Han Z, Yang H, Zhang W, et al. 2022. Efficient genetic transformation and CRISPR/Cas9-mediated genome editing of watermelon assisted by genes encoding developmental regulators. Journal of Zhejiang University: Science B 23:339−44

doi: 10.1631/jzus.B2200119
[76]

Wang Z, Wan L, Ren J, Zhang N, Zeng H, et al. 2024. Improving the genome editing efficiency of CRISPR/Cas9 in melon and watermelon. Cells 13:1782

doi: 10.3390/cells13211782
[77]

Giordano A, Santo Domingo M, Quadrana L, Pujol M, Martín-Hernández AM, et al. 2022. CRISPR/Cas9 gene editing uncovers the roles of CONSTITUTIVE TRIPLE RESPONSE 1 and REPRESSOR OF SILENCING 1 in melon fruit ripening and epigenetic regulation. Journal of Experimental Botany 73:4022−33

doi: 10.1093/jxb/erac148
[78]

Nonaka S, Ito M, Ezura H. 2023. Targeted modification of CmACO1 by CRISPR/Cas9 extends the shelf-life of Cucumis melo var. reticulatus melon. Frontiers in Genome Editing 5:1176125

doi: 10.3389/fgeed.2023.1176125
[79]

Zhang T, Xu N, Amanullah S, Gao P. 2023. Genome-wide identification, evolution, and expression analysis of MLO gene family in melon (Cucumis melo L.). Frontiers in Plant Science 14:1144317

doi: 10.3389/fpls.2023.1144317
[80]

Bambil D, Pistori H, Bao F, Weber V, Alves FM, et al. 2020. Plant species identification using color learning resources, shape, texture, through machine learning and artificial neural networks. Environment Systems and Decisions 40:480−84

doi: 10.1007/s10669-020-09769-w
[81]

Nabwire S, Suh HK, Kim MS, Baek I, Cho BK. 2021. Review: application of artificial intelligence in phenomics. Sensors 21:4363

doi: 10.3390/s21134363
[82]

Kirchgessner N, Liebisch F, Yu K, Pfeifer J, Friedli M, et al. 2016. The ETH field phenotyping platform FIP: a cable-suspended multi-sensor system. Functional Plant Biology 44:154−68

doi: 10.1071/FP16165
[83]

Casanova JJ, O'Shaughnessy SA, Evett SR, Rush CM. 2014. Development of a wireless computer vision instrument to detect biotic stress in wheat. Sensors 14:17753−69

doi: 10.3390/s140917753
[84]

Song P, Wang J, Guo X, Yang W, Zhao C. 2021. High-throughput phenotyping: breaking through the bottleneck in future crop breeding. The Crop Journal 9:633−45

doi: 10.1016/j.cj.2021.03.015
[85]

Farooq MA, Gao S, Hassan MA, Huang Z, Rasheed A, et al. 2024. Artificial intelligence in plant breeding. Trends in Genetics 40:891−908

doi: 10.1016/j.tig.2024.07.001
[86]

Naroui Rad MR, Koohkan S, Fanaei HR, Pahlavan Rad MR. 2015. Application of Artificial Neural Networks to predict the final fruit weight and random forest to select important variables in native population of melon (Cucumis melo L.). Scientia Horticulturae 181:108−12

doi: 10.1016/j.scienta.2014.10.025
[87]

Kalantar A, Edan Y, Gur A, Klapp I. 2020. A deep learning system for single and overall weight estimation of melons using unmanned aerial vehicle images. Computers and Electronics in Agriculture 178:105748

doi: 10.1016/j.compag.2020.105748
[88]

Cho BH, Lee KB, Hong Y, Kim KC. 2022. Determination of internal quality indices in oriental melon using snapshot-type hyperspectral image and machine learning model. Agronomy 12:2236

doi: 10.3390/agronomy12092236
[89]

Xue W, Ding H, Jin T, Meng J, Wang S, et al. 2024. CucumberAI: cucumber fruit morphology identification system based on artificial intelligence. Plant Phenomics 6:193

doi: 10.34133/plantphenomics.0193
[90]

Lasky JR, Upadhyaya HD, Ramu P, Deshpande S, Hash CT, et al. 2015. Genome-environment associations in sorghum landraces predict adaptive traits. Science Advances 1:e1400218

doi: 10.1126/sciadv.1400218
[91]

Sartor RC, Noshay J, Springer NM, Briggs SP. 2019. Identification of the expressome by machine learning on omics data. Proceedings of the National Academy of Sciences of the United States of America 116:18119−25

doi: 10.1073/pnas.1813645116
[92]

Uygun S, Azodi CB, Shiu SH. 2019. Cis-regulatory code for predicting plant cell-type transcriptional response to high salinity. Plant Physiology 181:1739−51

doi: 10.1104/pp.19.00653
[93]

Li Z, Cao L, Zhao L, Yu L, Chen Y, et al. 2020. Identification and biotechnical potential of a Gcn5-related N-acetyltransferase gene in enhancing microalgal biomass and starch production. Frontiers in Plant Science 11:544827

doi: 10.3389/fpls.2020.544827
[94]

Meena M, Shubham S, Paritosh K, Pareek N, Vivekanand V. 2021. Production of biofuels from biomass: predicting the energy employing artificial intelligence modelling. Bioresource Technology 340:125642

doi: 10.1016/j.biortech.2021.125642
[95]

Tzuri G, Zhou X, Chayut N, Yuan H, Portnoy V, et al. 2015. A 'golden' SNP in CmOr governs the fruit flesh color of melon (Cucumis melo). The Plant Journal 82:267−79

doi: 10.1111/tpj.12814
[96]

Kim N, Oh J, Kim B, Choi EK, Hwang US, et al. 2015. The CmACS-7 gene provides sequence variation for development of DNA markers associated with monoecious sex expression in melon (Cucumis melo L.). Horticulture, Environment, and Biotechnology 56:535−45

doi: 10.1007/s13580-015-0024-2
[97]

Zhang C, Ren Y, Guo S, Zhang H, Gong G, et al. 2013. Application of comparative genomics in developing markers tightly linked to the Pm-2F gene for powdery mildew resistance in melon (Cucumis melo L.). Euphytica 190:157−68

doi: 10.1007/s10681-012-0828-4
[98]

Eleblu JSY, Haraghi A, Mania B, Camps C, Rashid D, et al. 2019. The gynoecious CmWIP1 transcription factor interacts with CmbZIP48 to inhibit carpel development. Scientific Reports 9:15443

doi: 10.1038/s41598-019-52004-z