start-ver=1.4 cd-journal=joma no-vol=91 cd-vols= no-issue=3 article-no= start-page= end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2022 dt-pub=2022 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Deep Learning Predicts Rapid Over-softening and Shelf Life in Persimmon Fruits en-subtitle= kn-subtitle= en-abstract= kn-abstract=In contrast to the progress in the research on physiological disorders relating to shelf life in fruit crops, it has been difficult to non-destructively predict their occurrence. Recent high-tech instruments have gradually enabled non-destructive predictions for various disorders in some crops, while there are still issues in terms of efficiency and costs. Here, we propose application of a deep neural network (or simply deep learning) to simple RGB images to predict a severe fruit disorder in persimmon, rapid over-softening. With 1,080 RGB images of eSoshuf persimmon fruits, three convolutional neural networks (CNN) were examined to predict rapid over-softened fruits with a binary classification and the date to fruit softening. All of the examined CNN models worked successfully for binary classification of the rapid over-softened fruits and the controls with > 80% accuracy using multiple criteria. Furthermore, the prediction values (or confidence) in the binary classification were correlated to the date to fruit softening. Although the features for classification by deep learning have been thought to be in a black box by conventional standards, recent feature visualization methods (or gexplainableh deep learning) has allowed identification of the relevant regions in the original images. We applied Grad-CAM, Guided backpropagation, and layer-wise relevance propagation (LRP), to find early symptoms for CNNs classification of rapid over-softened fruits. The focus on the relevant regions tended to be on color unevenness on the surface of the fruit, especially in the peripheral regions. These results suggest that deep learning frameworks could potentially provide new insights into early physiological symptoms of which researchers are unaware. en-copyright= kn-copyright= en-aut-name=SuzukiMaria en-aut-sei=Suzuki en-aut-mei=Maria kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=MasudaKanae en-aut-sei=Masuda en-aut-mei=Kanae kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=AsakumaHideaki en-aut-sei=Asakuma en-aut-mei=Hideaki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=TakeshitaKouki en-aut-sei=Takeshita en-aut-mei=Kouki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=BabaKohei en-aut-sei=Baba en-aut-mei=Kohei kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=KuboYasutaka en-aut-sei=Kubo en-aut-mei=Yasutaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=UshijimaKoichiro en-aut-sei=Ushijima en-aut-mei=Koichiro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=UchidaSeiichi en-aut-sei=Uchida en-aut-mei=Seiichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=AkagiTakashi en-aut-sei=Akagi en-aut-mei=Takashi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= affil-num=1 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=2 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=3 en-affil=Fukuoka Agriculture and Forestry Research Center kn-affil= affil-num=4 en-affil=Department of Advanced Information Technology, Kyushu University kn-affil= affil-num=5 en-affil=Department of Advanced Information Technology, Kyushu University kn-affil= affil-num=6 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=7 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=8 en-affil=Department of Advanced Information Technology, Kyushu University kn-affil= affil-num=9 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= END start-ver=1.4 cd-journal=joma no-vol=91 cd-vols= no-issue=1 article-no= start-page=58 end-page=67 dt-received= dt-revised= dt-accepted= dt-pub-year=2022 dt-pub=20220122 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Fasciation in Strawberry Floral Organs and Possible Implications for Floral Transition en-subtitle= kn-subtitle= en-abstract= kn-abstract=Fasciation in strawberry is characterized by an enlarged and flattened receptacle, clustering of flowers, and altered inflorescence architecture. However, the developmental process of fasciated flowers remains obscure. In this study, the fasciation incidence and developmental process in the primary fruit and inflorescence architecture were evaluated and compared for the non-susceptible cultivars, eNyohof and eSagahonokaf and one of the most susceptible cultivars, eAi-Berryf. The severity and frequency of flower and inflorescence fasciation was clearly greater in the vigorously growing large plants of eAi-Berryf compared to small plants and large plants of the other two cultivars. In eAi-Berryf, the deformation of the large shoot apical meristem (SAM) into an oval shape was the initial symptom observed before and during floral transition. Such oval-shaped SAMs often differentiated two or more leaf primordia almost at the same time, which then developed into divided multiple vegetative SAMs before floral transition and linearly-fasciated SAMs during floral transition, respectively. The development of fasciation symptoms was observed after downregulation of FaTFL1. Although inflorescence or receptacle fasciation could be controlled when early and rapid floral induction was achieved by intermittent low-temperature treatment, severe fasciation was observed in late-flowered plants which were either not responsive or not subjected to this treatment. These results indicate that fasciation of floral organs may be triggered and develop during floral transition and that temperature fluctuations around boundary values between floral inhibition to induction may cause a half-finished or slowly processed floral transition and finally result in severe fasciation in vigorously growing eAi-Berryf plants. en-copyright= kn-copyright= en-aut-name=Thi CamNguyen en-aut-sei=Thi Cam en-aut-mei=Nguyen kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=SunagawaNaomichi en-aut-sei=Sunagawa en-aut-mei=Naomichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=SesumiMiho en-aut-sei=Sesumi en-aut-mei=Miho kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=KitamuraYoshikuni en-aut-sei=Kitamura en-aut-mei=Yoshikuni kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=TanakaYoshiyuki en-aut-sei=Tanaka en-aut-mei=Yoshiyuki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=GotoTanjuro en-aut-sei=Goto en-aut-mei=Tanjuro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=YasubaKen-ichiro en-aut-sei=Yasuba en-aut-mei=Ken-ichiro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=YoshidaYuichi en-aut-sei=Yoshida en-aut-mei=Yuichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= affil-num=1 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=2 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=3 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=4 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=5 en-affil=Graduate School of Agriculture, Kyoto University kn-affil= affil-num=6 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=7 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= affil-num=8 en-affil=Graduate School of Environmental and Life Sciences, Okayama University kn-affil= END start-ver=1.4 cd-journal=joma no-vol=88 cd-vols= no-issue=1 article-no= start-page=1 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2019 dt-pub=20190131 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Publication of the first special issue of The Horticulture Journal Preface en-subtitle= kn-subtitle= en-abstract= kn-abstract= en-copyright= kn-copyright= en-aut-name=YoshidaYuichi en-aut-sei=Yoshida en-aut-mei=Yuichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= affil-num=1 en-affil=Okayama University kn-affil= END