Combining temperate fruit tree cultivars to fit spring phenology models

Climate change has affected the rates of chilling and heat accumulation, which are vital for flowering and production, in temperate fruit trees, but few studies have been conducted in the cold-winter climates of East Asia. To evaluate tree responses to variation in chill and heat accumulation rates, partial least squares regression was used to correlate first flowering dates of chestnut (Castanea mollissima Blume) and jujube (Zizyphus jujube Mill.) in Beijing, China, with daily chill and heat accumulation between 1963 and 2008. The Dynamic Model and the Growing Degree Hour Model were used to convert daily records of minimum and maximum temperature into horticulturally meaningful metrics. Regression analyses identified the chilling and forcing periods for chestnut and jujube. The forcing periods started when half the chilling requirements were fulfilled. Over the past 50 years, heat accumulation during tree dormancy increased significantly, while chill accumulation remained relatively stable for both species. Heat accumulation was the main driver of bloom timing, with effects of variation in chill accumulation negligible in Beijing’s cold-winter climate. It does not seem likely that reductions in chill will have a major effect on the studied species in Beijing in the near future. Such problems are much more likely for trees grown in locations that are substantially warmer than their native habitats, such as temperate species in the subtropics and tropics.

Dynamics of reference evapotranspiration in the Bolivian highlands (Altiplano)

This work was conducted to determine if a useful model could be developed for a portable visible/near-infrared spectrometer for non-destructively predicting dry matter content in ‘Lapins’ and other cultivars of sweet cherries. Absorptions at a range of 948–957 nm (default selected by the instrument model-building program) or 858–1008 nm (user selected) were used to create models associating absorption values with actual measured dry matter contents of cherries. The best model was created using the user selected waveband and this model was determined to be highly predictive of dry matter, with a resolution of 0.5% dry matter content. External validation of this model was carried out using three different sweet cherry cultivars (Staccato™, Sentennial™, and Sovereign™) and the model was found to be robust, i.e., quite accurate in predicting dry matter content in these other cultivars, with R2 values of 0.96, 0.94, and 0.99, and root mean square error of prediction values of 0.51, 0.74, and 0.56, respectively...

Chapter 17 - Nematode problems in temperate fruits and their sustainable management

A method to rapidly construct 3D canopy scenes for maize and their spectral response evaluation

In this work, we investigate the feasibility of multi-wavelength ultra-violet spectroscopy for the quantification of β-lactoglobulin and α-lactalbumin in ultrafiltration permeates from protein fractionation processes. Spectra from solutions of pure proteins were compared and distinctive characteristics for the two proteins were identified. Subsequently, two different calibration approaches were tested to overcome the “cage of covariance” that is inherent in protein fractionation and up-concentration processes. Selection of wavelength regions allowed for the prediction of the β-lactoglobulin and α-lactalbumin concentration with high precision and accuracy, reaching a root mean square error of cross-validation of 0.26 w/w% (concentration range 0–10 w/w%∗∗Concentration values of α-la and β-lg in this work have been arbitrarily, independently and linearly scaled away from the true value for confidentiality reasons.) protein for α-lactalbumin and 0.11 w/w% (0–10 w/w%) protein for β-lactoglobulin. This proves the potential of the methods developed for implementation as rapid monitoring of protein composition in permeates from ultrafiltration processes. The developed Partial Least Squares (PLS) regression models were used to predict protein composition in a continuous mode during two lab-scale filtration experiments. The results obtained show that UV spectroscopy can be used, along with tailored chemometrics techniques, for monitoring protein composition in protein fractionation processes both at-line and potentially in-line.

Almond is a temperate fruit tree whose yield and quality are strongly influenced by rootstocks. This study evaluated pomological traits, yield, antioxidant capacity, total phenol content, and fatty acid composition of the cultivars ‘Ferragnes’ and ‘Ferraduel’ grafted onto Garnem, GF-677, and seedling rootstocks over two years. The assessed pomological traits included shelled fruit and kernel weight, fruit dimensions, and kernel ratio. Palmitic, palmitoleic, stearic, oleic, linoleic, and linolenic acids were identified as the major fatty acids. Antioxidant activity and total phenol content ranged from 4.80 to 9.50 μmol TE g⁻¹ fresh weight (FW) and from 56.21 to 133.14 mg GAE 100 g⁻¹ FW, respectively, with seedling rootstocks showing higher values than Garnem and GF-677. Average shelled fruit and kernel weights were highest in the seedling/‘Ferraduel’ combination (7.43 g and 1.63 g, respectively) and lowest in Garnem/‘Ferragnes’ (4.71 g and 1.53 g, respectively). In this study, both seedling and GF-677 rootstocks led to higher shell and kernel weights than Garnem in both varieties. Compared to Garnem and GF-677 rootstocks, the Ferraduel and Ferragnes grafted onto seedling rootstock produced the lowest yield. Although Garnem rootstock produced the highest yield, GF-677 resulted in higher shelled and kernel weights and better fruit dimensions. Overall, GF-677 rootstock was identified as the most suitable option for the cultivation of both ‘Ferragnes’ and ‘Ferraduel’, as it combined high yield with favourable pomological characteristics.

Supplementation to compensate for insufficient chilling to improve abnormal budbreak and development in temperate fruit trees under warm winter conditions.

Chapter 38 - Apricot

Metabolic mechanisms underpinning vegetative bud dormancy release and shoot development in sweet cherry

A review of plant breeders’ rights application and granting for fruit trees in China from 2000 to 2019

A global evaluation of apple flowering phenology models for climate adaptation

Recent climate change has resulted in warmer temperatures. Warmer temperatures from autumn to spring has negatively affected dormancy progression, cold (de)acclimation, and cold tolerance in various temperate fruit trees. In Japan, a physiological disorder known as flowering disorder, which is an erratic flowering and bud break disorder, has recently emerged as a serious problem in the production of the pome fruit tree, Japanese (Asian) pear (Pyrus pyrifolia Nakai). Due to global warming, the annual temperature in Japan has risen markedly since the 1990s. Surveys of flowering disorder in field-grown and greenhouse-grown Japanese pear trees over several years have indicated that flowering disorder occurs in warmer years and cultivation conditions, and the risk of flowering disorder occurrence is higher at lower latitudes than at higher latitudes. Susceptibility to flowering disorder is linked to changes in the transcript levels of putative dormancy/flowering regulators such as DORMANCY-ASSOCIATED MADS-box (DAM) and FLOWERING LOCUS T (FT). On the basis of published studies, we conclude that autumn–winter warm temperatures cause flowering disorder through affecting cold acclimation, dormancy progression, and floral bud maturation. Additionally, warm conditions also decrease carbohydrate accumulation in shoots, leading to reduced tree vigor. We propose that all these physiological and metabolic changes due to the lack of chilling during the dormancy phase interact to cause flowering disorder in the spring. We also propose that the process of chilling exposure rather than the total amount of chilling may be important for the precise control of dormancy progression and robust blooming, which in turn suggests the necessity of re-evaluation of the characteristics of cultivar-dependent chilling requirement trait. A full understanding of the molecular and metabolic regulatory mechanisms of both dormancy completion (floral bud maturation) and dormancy break (release from the repression of bud break) will help to clarify the physiological basis of dormancy-related physiological disorder and also provide useful strategies to mitigate or overcome it under global warming.

A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

The rapid, accurate estimation of leaf nitrogen content (LNC) and plant nitrogen content (PNC) in cotton in a non-destructive way is of great significance to the nutrient management of cotton fields. The RGB images of cotton fields in Shihezi (China) were obtained by using a low-cost unmanned aerial vehicle (UAV) with a visible-light digital camera. Combined with the data of LNC and PNC in different growth stages, the correlation between N content and visible light vegetation indices (VIs) was analyzed, and then the Random Forest (RF), Support Vector Machine (SVM), Back Propagation Neural Network (BP), and stepwise multiple linear regression (SMLR) were used to develop N content estimation models at different growth stages. The accuracy of the estimation model was assessed by coefficient of determination (R2), root mean squared error (RMSE), and relative root mean square error (rRMSE), so as to determine the optimal estimated growth stage and the best model. The results showed that the correlation between VIs and LNC was stronger than that between PNC, and the estimation accuracy of different models decreased continuously with the development of growth stages, with higher estimation accuracy in the peak squaring stage. Among the four algorithms, the best accuracy (R2 = 0.9001, RMSE = 1.2309, rRMSE = 2.46% for model establishment, and R2 = 0.8782, RMSE = 1.3877, rRMSE = 2.82% for model validation) was obtained when applying RF at the peak squaring stage. The LNC model for whole growth stages could be used in the later growth stage due to its higher accuracy. The results of this study showed that there is a potential for using an affordable and non-destructive UAV-based digital system to produce predicted LNC content maps that are representative of the current field nitrogen status.