Histone deacetylase enzymes participate in the regulation of many aspects of plant development. However, the genome-level targets of histone deacetylation during apple (Malus domestica) fruit development have not been resolved in detail, and the mechanisms of regulation of such a process are unknown. We previously showed that the complex of ethylene response factor 4 (MdERF4) and the TOPLESS co-repressor (MdTPL4) (MdERF4-MdTPL4) is constitutively active during apple fruit development, but whether this transcriptional repression complex is coupled to chromatin modification is unknown. Here, we show that a histone deacetylase (MdHDA19) is recruited to the MdERF4-MdTPL4 complex, thereby impacting fruit ethylene biosynthesis. Transient suppression of MdHDA19 expression promoted fruit ripening and ethylene production. To identify potential downstream target genes regulated by MdHDA19, we conducted chromatin immunoprecipitation (ChIP) sequencing of H3K9 and ChIP-quantitative PCR assays. We found that MdHDA19 affects ethylene production by facilitating H3K9 deacetylation and forms a complex with MdERF4-MdTPL4 to directly repress MdACS3a expression by decreasing the degree of acetylation. We demonstrate that an early-maturing-specific acetylation H3K9ac peak in MdACS3a and expression of MdACS3a were specifically up-regulated in fruit of an early-maturing, but not a late-maturing, cultivar. We provide evidence that a C-to-G mutation in the EAR motif of MdERF4 reduces the repression of MdACS3a by the MdERF4-MdTPL4-MdHDA19 complex. Taken together, our results reveal that the MdERF4-MdTPL-MdHDA19 repressor complex participates in the epigenetic regulation of apple fruit ripening.

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& Context Knowledge of the occurrence of sound and loose knots on the surface of sawn sugi (Cryptomeria japonica L.f.) is important for its grading and application. & Objectives This study examined an optical system for detecting sound and loose knots in sugi instead of human being using the combining information of the color and texture features. & Methods The proposed system could be conceptually divided into two components: a CCD camera scanning system and a defect detecting algorithm developed by the authors. In the algorithm, the contrast parameter calculated from a graylevel co-occurrence matrix was used to locate the potential defects represented by sound knots and loose knots. The rulebased approach, which was built according to the color feature histograms, was used to identify sound knots and loose knots. A series of samples containing single or multiple sound and/or loose knots were selected at random to verify the efficiency and accuracy of the proposed system. & Results There were 94 sound knots and 86 loose knots on the surfaces of these samples, and the accuracy of locating the positions of sound knots and loose knots was 94.7% and 97.6%, respectively. The accuracies of identifying knots as sound or loose were 96.6% and 98.8%, respectively. The overall detection accuracy of the system was 93.9%. & ConclusionsThe results indicate that the proposed vision system is an efficient means of detecting sound knots and loose knots.

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