Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot

Katja Herzog; Florian Schwander; Hanns-Heinz Kassemeyer; Evi Bieler; Markus Dürrenberger; Oliver Trapp; Reinhard Töpfer

doi:10.3389/fpls.2021.808365

Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot

Front Plant Sci. 2022 Feb 10:12:808365. doi: 10.3389/fpls.2021.808365. eCollection 2021.

Authors

Katja Herzog¹, Florian Schwander¹, Hanns-Heinz Kassemeyer^{2

3}, Evi Bieler⁴, Markus Dürrenberger⁴, Oliver Trapp¹, Reinhard Töpfer¹

Affiliations

¹ Institute for Grapevine Breeding Geilweilerhof, Julius Kühn-Institut, Siebeldingen, Germany.
² Plant Pathology & Diagnostic, State Institute for Viticulture and Enology Freiburg, Freiburg, Germany.
³ Plant Biomechanics Group & Botanic Garden, Faculty of Biology, University of Freiburg, Freiburg, Germany.
⁴ Nano Imaging Lab, Swiss Nano Science Institute, University of Basel, Basel, Switzerland.

Abstract

Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for loose grape bunches, which is recently the most evident trait to decrease the infection risk of Botrytis bunch rot. This study focused on plant phenomics of multiple traits by applying fast sensor technologies to measure berry impedance (Z _REL ), berry texture, and 3D bunch architecture. As references, microscopic determined cuticle thickness (MS _CT ) and infestation of grapes with Botrytis bunch rot were used. Z _REL hereby is correlated to grape bunch density OIV204 (r = -0.6), cuticle thickness of berries (r = 0.61), mean berry diameter (r = -0.63), and Botrytis bunch rot (r = -0.7). However, no correlation between Z _REL and berry maturity or berry texture was observed. In comparison to the category of traditional varieties (mostly susceptible), elite breeding lines show an impressive increased Z _REL value (+317) and a 1-μm thicker berry cuticle. Quantitative trait loci (QTLs) on LGs 2, 6, 11, 15, and 16 were identified for Z _REL and berry texture explaining a phenotypic variance of between 3 and 10.9%. These QTLs providing a starting point for the development of molecular markers. Modeling of Z _REL and berry texture to predict Botrytis bunch rot resilience revealed McFadden R ² = 0.99. Taken together, this study shows that in addition to loose grape bunch architecture, berry diameter, Z _REL , and berry texture values are probably additional parameters that could be used to identify and select Botrytis-resilient wine grape varieties. Furthermore, grapevine breeding will benefit from these reliable methodologies permitting high-throughput screening for additional resilience traits of mechanical and physical barriers to Botrytis bunch rot. The findings might also be applicable to table grapes and other fruit crops like tomato or blueberry.

Keywords: Botrytis cinerea; QTL; Vitis vinifera ssp. vinifera; berry cuticle; berry texture analysis; grapevine; high-throughput; phenomics.