Optimization of ‘Tainongyihao’ Mango Inflorescence-Cutting Technology
Inflorescence cutting is a critical cultural practice that enhances yield and fruit quality in mango cultivation. This study evaluated four treatments with the “Tainongyihao” mango: no cutting (CK), 1/3, 1/2, and 2/3 cutting of the central inflorescence axis, classified as light (L), medium (M), and...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Horticulturae |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2311-7524/11/3/239 |
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| Summary: | Inflorescence cutting is a critical cultural practice that enhances yield and fruit quality in mango cultivation. This study evaluated four treatments with the “Tainongyihao” mango: no cutting (CK), 1/3, 1/2, and 2/3 cutting of the central inflorescence axis, classified as light (L), medium (M), and heavy (H) cutting, respectively. Inflorescences were categorized by length, and field experiments were conducted during the growth periods of autumn–winter and winter–spring fruit in under-regulated and conventional harvest systems. The measured indicators include yield efficiency per unit trunk circumference, average fruit weight, reduced sugar content, total soluble solids (TSS), total titratable acids (TA), vitamin C content (Vc), and the TSS/TA ratio. Results indicated that light cutting was optimal for yield efficiency of autumn–winter fruit, while medium and heavy cutting were most effective for winter–spring fruit. Comprehensive fruit quality improved most under heavy cutting across all inflorescences. Long inflorescences benefited from heavy or medium cutting, medium inflorescences benefited from heavy cutting, and short inflorescences benefited from medium cutting. Interactive effects were observed between inflorescence-cutting treatments and inflorescence length, with fruit quality consistently improving under inflorescence-cutting treatments. Heavy cutting is recommended for manual operations, and all the results of this paper provide a foundation for developing artificial intelligence (AI)-based inflorescence-cutting technologies that enable precise and efficient mango cultivation practices. |
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| ISSN: | 2311-7524 |