A photosynthetically active radiation sensor

A sensor for measuring photosynthetically active radiation was constructed using a silicon photocell in combination with a glass absorption filter. A trimmer potentiometer was used for standardization of sensor output. The sensors were calibrated using a commercially available quantum sensor. Average correlation coefficient between constructed sensors and the standard was 0.94. The sensors had a quantum response, were sensitive only in the wavelengths between 400 and 700 nm, exhibited a linear response to varying PAR light levels, and were inexpensive to construct

Influence of canopy fruit location on morphological, histochemical and biochemical changes in two oil olive cultivars

The influence of different irradiance conditions was evaluated under natural solar radiation by comparing well-exposed (in) and shaded fruit (out) in canopies of olive trees (Olea europaea L). Over a 2-year period, from 50 days after full bloom up to harvest time, “in” and “out” olive samples of two genotypes (“Frantoio Millennio” and “Coratina 5/19”) were periodically collected. Morphological, histochemical, and biochemical analysis were performed to study the changes on fruit morphometric traits, oil body accumulation, and b-glucosidase enzyme activity. Some parameters were modified by shading inside the canopy in which the proportion of incident photosynthetically active radiation intercepted by the crop was 47%. Shaded fruits developed at slow rate and were characterized by late darkgoing time, reduced size, with a tendency toward oblong shape. The rapid histochemical procedure proposed to estimate the oil body accumulation during fruit ripening showed that a reduced irradiance caused a decrease in oil body density. The canopy position influenced, in a different way, the b-glucosidase activity in relation to the fruit-ripening stage in both genotypes. These findings indicate that providing an adequate and uniform lighting of the olive canopy by careful choices of orchard management practices can be a key factor for several yield components

Apoplasmic and simplasmic phloem unloading mechanisms: Do they co-exist in Angeleno plums under demanding environmental conditions?

Biophysical fruit growth depends on a balance among the vascular and transpiration flows entering/exiting the fruit via phloem, xylem and through the epidermis. There is no information on vascular flows of Japanese plums, a species characterized by high-sugar content of its fruit at harvest. Vascular flows of Angeleno plums were monitored by fruit gauges during late fruit development, under the dry environment of the Goulburn Valley, Victoria, Australia. Phloem, xylem flows and skin transpiratory losses were determined, as well as diurnal leaf, stem and fruit pressure potentials. Fruit seasonal development, skin conductance and dry matter accumulation were also monitored. Fruit grew following a double-sigmoid pattern, but fruit size increased only 3.1 g over the last 3 weeks of development. Fruit grew very little in the morning, primarily due to phloem inflows (0.05 g fruit 121 hr 121 ), while water left the fruit via the xylem. Negligible skin transpiration was recorded for vapour pressure deficit (VPD) values below 3 kPa. This growth pattern, in the absence of skin transpiration, suggests apoplastic phloem unloading. However, at VPD values over 3 kPa (e.g. from early afternoon to a peak around 18:00 h), transpiratory losses through the skin (up to 0.25 g fruit 121 hr 121 ) caused fruit to shrink, leading to enhanced phloem and xylem inflows (ca. 0.15 g fruit 121 hr 121 ), a scenario that would correspond to symplastic phloem unloading. Over 24 h the fruit showed a slightly negative total growth, consistent with fruit growth measured in situ during the season at weekly intervals. A few fruit species are known to alter their phloem unloading mechanism, switching from symplastic to apoplastic during the season. Our data support the coexistence in Japanese plum of different phloem unloading strategies within the same day

An integrated approach for increasing breeding efficiency in apple and peach in Europe

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond

Fruit transpiration drives interspecific variability in fruit growth strategies

Fruit growth is a complex mechanism resulting from biochemical and biophysical events leading water and dry matter to accumulate in the fruit tissues. Understanding how fruits choose their growth strategies can help growers optimizing their resource management for a more sustainable production and a higher fruit quality. This paper compares the growth strategies adopted by different fruit crops, at different times during the season and relates their fruit surface conductance to key physiological parameters for fruit growth such as phloem and xylem inflows as well transpiration losses. Our results show how fruits capacity to transpire (determined by their surface conductance) is a key driver in determining the growth strategy adopted by a species and explains the inter-species variability existing among different crops. Indeed, fruits change their surface conductance depending on the species and the phenological stage. This has an impact on the fruit's ability to lose water due to transpiration, affecting fruit pressure potential and increasing the force with which the fruit is able to attract xylem and phloem flows, with a considerable impact on fruit growth rate

Red and blue netting alters leaf morphological and physiological characteristics in apple trees

There is little information about the role of red and blue light on leaf morphology and physiology in fruit trees, and more studies have been developed in herbaceous plants grown under controlled light conditions. The objective of this research was to evaluate the effect of red and blue screens on morpho-anatomy and gas exchange in apple leaves grown under ambient sunlight conditions. Apple trees cv. Fuji were covered by 40% red and blue nets, leaving trees with 20% white net as control. Light relations (photosynthetic photon flux density, PPFD; red to far-red light ratio, R/FR and blue to red light ratio, B/R), morpho-anatomical features of the leaf (palisade to spongy mesophyll ratio, P/S, and stomata density, SD) and leaf gas exchange (net photosynthesis rate, An; stomatal conductance, gs; transpiration rate, E; and intrinsic water use efficiency, IWUE) were evaluated. Red and blue nets reduced 27% PPFD, reducing by 20% SD and 25% P/S compared to control, but without negative effects on An and gs . Blue net increased gs 21%, leading to the highest E and lowest IWUE by increment of B/R light proportion. These findings demonstrate the potential use of red and blue nets for differential modulation of apple leaf gas exchange through sunlight management under field conditions

Irrigation improves tree physiological performances and nut quality in sweet chestnut

Italy is one of the most important world chestnut producers. The majority of traditional sweet chestnut orchards are still non-irrigated since they are typically located in mountain-hill areas usually characterized by environmental conditions that are not limiting for the vegetative and reproductive growth of this fruit tree crop. Nowadays, the increase of summer temperatures and the decrease of rainfall are affecting negatively chestnut physiological performances and productivity. The adoption of scheduled irrigation practices, in light also of the limited water availability/possibility of storage (e.g., artificial lakes, reservoirs) of these areas, should become part of chestnut orchard management. The aim of the present study was to evaluate the effect of irrigation on sweet chestnut physiology, nut quality and yield. The study was carried out in 2020 in a traditional chestnut orchard of the “Marron Buono di Marradi” ecotype, located in the Tuscan-Emilian Apennines (Marradi, Italy). The experimental design compared trees irrigated between August and September with a non-irrigated control. Leaf gas exchange and plant water status were monitored during the growing season and, nut quality and yield were assessed at harvest. Results showed that irrigated trees exhibited, in middle September, higher photosynthesis, transpiration, stomatal conductance and stem water potentials compared to the non-irrigated control trees. Nut size was significantly smaller in non-irrigated trees than in irrigated ones while the yield was not statistically affected by the irrigation treatment. Despite the favourable mild and rainy weather conditions occurred in 2020, the application of irrigation during the nut filling phase (e.g., late summer) was beneficial for enhancing sweet chestnut physiological performances and for improving nut quality

Single-shot convolution neural networks for real-time fruit detection within the tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms has shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This architecture takes the input image and divides into AxA grid, where A is a configurable hyper-parameter that defines the fineness of the grid. To each grid cell an image detection and localization algorithm is applied. Each of those cells is responsible to predict bounding boxes and confidence score for fruit (apple and pear in the case of this study) detected in that cell. We want this confidence score to be high if a fruit exists in a cell, otherwise to be zero, if no fruit is in the cell. More than 100 images of apple and pear trees were taken. Each tree image with approximately 50 fruits, that at the end resulted on more than 5000 images of apple and pear fruits each. Labeling images for training consisted on manually specifying the bounding boxes for fruits, where (x, y) are the center coordinates of the box and (w, h) are width and height. This architecture showed an accuracy of more than 90% fruit detection. Based on correlation between number of visible fruits, detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Processing speed is higher than 20 FPS which is fast enough for any grasping/harvesting robotic arm or other real-time applications. HIGHLIGHTS: Using new convolutional deep learning techniques based on single-shot detectors to detect and count fruits (apple and pear) within the tree canopy

The effects of chestnut orchard microclimate on burr development

Chestnut crop is regaining its fame worldwide with powerful investment perspectives. Unluckily the climate change effects are posing high threat to its cultivation with less available resources and increased production cost both in traditional and specialized orchards. Additionally, the chestnut physiological knowledge is still limited, especially as concern the burr development (i.e., the economical production target) and its relationship with the environmental parameters. The aim of the present study was to evaluate the seasonal, daily, and hourly burr growth pattern associated to environmental parameters for improving physiological knowledge on this species. The study was carried out in a traditional rainfed sweet chestnut orchard located in the Tuscan-Emilian Apennines (Monterenzio, Italy). The chestnut burr growth was measured, along the entire season, both with a digital calliper and through the use of plant-based sensors (fruit-gauges) that permitted to measure, in real-time, the burr growth pattern. Environmental data were recorded by a weather station placed in the middle of the orchard. Results evidenced a higher burr growth rate, in the last part of the season (from middle-end of August to full fall) while the daily growing pattern was characterized by increased oscillation, along the season, of night-swelling and daily-shrinkage. The night-swelling was found to be influenced by high nocturnal air relative humidity while the daily-shrinkage was influenced by the higher wind speed, solar radiation and vapour pressure deficit. Thus, the burr daily net growth can be associated, depending on the phenological stages, to environmental parameters. Precipitation but especially the atmosphere humidity, in September and October, were the main external drivers of burr daily net growth. These results could be promising for the adoption of sustainable (e.g., late season grass mowing, sprinkler irrigation) and smart practices for improving chestnut management in both traditional and specialized orchards

Fruit maturity and antioxidant activity affecting superficial scald development in ‘Abate Fétel’ pears

Superficial scald (SS) is one of the main physiological disorders affecting postharvest of pears. Its onset is linked to oxidative processes. Antioxidant compounds such as ascorbic acid and phenolics could play a key role in preventing SS. Growing environment and fruit quality also have an influence on SS symptoms occurrence. The aim of this project is to understand the relationship between antioxidant activity, phenolic content, and development of SS in ‘Abate Fétel’ pear. Moreover, the effect on SS of fruit maturity at harvest was assessed using multivariate statistical approach. Data were collected in thirty orchards in the EmiliaRomagna region (Italy) in three seasons (2018, 2019 and 2020), and the fruit were stored in a regular atmosphere for 120 days. Antioxidant capacity was determined by 2,2diphenyl1picrylhydrazy (DPPH) method and total phenol content by FolinCiocalteau colorimetric protocol. The results showed that 340 mg of ascorbate/100 g of FW and 300 mg of gallic ac./100 g of FW at least provide good protection against SS. Multivariate analysis indicated that pulp firmness and index of absorbance difference (IAD) seem to keep low the SS occurrence, when at harvest are higher than 6.3 kg and 1.9, respectively. In conclusion, it would be possible to build a forecasting model to control SS that considers preharvest data and content of antioxidants in different orchards, to improve the postharvest management of ‘Abate Fétel’