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After replanting apple (Malus domestica Borkh.) on the same site severe growth suppressions, and a decline in yield and fruit quality are observed in all apple producing areas worldwide. The causes of this complex phenomenon, called apple replant disease (ARD), are only poorly understood up to now which is in part due to inconsistencies in terms and methodologies. Therefore we suggest the following definition for ARD: ARD describes a harmfully disturbed physiological and morphological reaction of apple plants to soils that faced alterations in their (micro-) biome due to the previous apple cultures. The underlying interactions likely have multiple causes that extend beyond common analytical tools in microbial ecology. They are influenced by soil properties, faunal vectors, and trophic cascades, with genotype-specific effects on plant secondary metabolism, particularly phytoalexin biosynthesis. Yet, emerging tools allow to unravel the soil and rhizosphere (micro-) biome, to characterize alterations of habitat quality, and to decipher the plant reactions. Thereby, deep insights into the reactions taking place at the root rhizosphere interface will be gained. Counteractions are suggested, taking into account that culture management should emphasize on improving soil microbial and faunal diversity as well as habitat quality rather than focus on soil disinfection.
Apple replant disease (ARD) is a soil-borne disease, which is of particular importance for fruit tree nurseries and fruit growers. The disease manifests by a poor vegetative development, stunted growth, and reduced yield in terms of quantity and quality, if apple plants (usually rootstocks) are replanted several times at the same site. Genotype-specific differences in the reaction of apple plants to ARD are documented, but less is known about the genetic mechanisms behind this symptomatology. Recent transcriptome analyses resulted in a number of candidate genes possibly involved in the plant response. In the present study, the expression of 108 selected candidate genes was investigated in root and leaf tissue of four different apple genotypes grown in untreated ARD soil and ARD soil disinfected by γ-irradiation originating from two different sites in Germany. Thirty-nine out of the 108 candidate genes were differentially expressed in roots by taking a p-value of < 0.05 and a fold change of > 1.5 as cutoff. Sixteen genes were more than 4.5-fold upregulated in roots of plants grown in ARD soil. The four genes MNL2 (putative mannosidase); ALF5 (multi antimicrobial extrusion protein); UGT73B4 (uridine diphosphate (UDP)-glycosyltransferase 73B4), and ECHI (chitin-binding) were significantly upregulated in roots. These genes seem to be related to the host plant response to ARD, although they have never been described in this context before. Six of the highly upregulated genes belong to the phytoalexin biosynthesis pathway. Their genotype-specific gene expression pattern was consistent with the phytoalexin content measured in roots. The biphenyl synthase (BIS) genes were found to be useful as early biomarkers for ARD, because their expression pattern correlated well with the phenotypic reaction of the Malus genotypes investigated.
Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit
(2017)
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3-4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from -0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date.