In agriculture, early detection of plant stresses is advantageous in preventing crop yield losses. Remote sensors are increasingly being utilized for crop health monitoring, offering non-destructive, spatialized detection and the quantification of plant diseases at various levels of measurement. Advances in sensor technologies have promoted the development of novel techniques for precision agriculture. As in situ techniques are surpassed by multispectral imaging, refinement of hyperspectral imaging and the promising emergence of light detection and ranging (LIDAR), remote sensing will define the future of biotic and abiotic plant stress detection, crop yield estimation and product quality. The added value of LIDAR-based systems stems from their greater flexibility in capturing data, high rate of data delivery and suitability for a high level of automation while overcoming the shortcomings of passive systems limited by atmospheric conditions, changes in light, viewing angle and canopy structure. In particular, a multi-sensor systems approach and associated data fusion techniques (i.e., blending LIDAR with existing electro-optical sensors) offer increased accuracy in plant disease detection by focusing on traditional optimal estimation and the adoption of artificial intelligence techniques for spatially and temporally distributed big data. When applied across different platforms (handheld, ground-based, airborne, ground/aerial robotic vehicles or satellites), these electro-optical sensors offer new avenues to predict and react to plant stress and disease. This review examines the key sensor characteristics, platform integration options and data analysis techniques recently proposed in the field of precision agriculture and highlights the key challenges and benefits of each concept towards informing future research in this very important and rapidly growing field.

Consistency of fruit quality is extremely important in horticulture. Fruit growth and quality in nectarine are affected by fruit position in the canopy, related to the tree shape. The “open shaped” training systems, such as Tatura Trellis, improve fruit growth and quality. The Index of Absorbance Difference (IAD) is a new marker that characterizes climacteric fruit during ripening. A study on fruit ripening was performed by using theIADon nectarine to monitor fruit maturity stages of two cultivars trained as Tatura Trellis in Victoria, Australia. Fruit of cv “Summer Flare 34” (“SF34”) grown in different positions on the tree showed high ripening homogeneity. Fruit harvested at a similar ripening stage showed fruit firmness and soluble solid content homogeneity. Fruits from hand-thinned variety “Summer Flare 26” (“SF26”) were larger in size, had advanced ripening, and showed greater homogeneity. For “SF26”, a weak correlation betweenIADand SSC was observed. The experiment showed that the Tatura Trellis training system is characterized by high homogeneity of nectarine fruit when coupled with a proper management of fruit density. It also confirmed that theIADcould be used as new nondestructive maturity index for nectarine fruit quality assessment in the field.

In organic apple production systems, orchard floor management is of prime importance because it determines weed management and soil fertility. In this experiment, we evaluated the response of the cultivar Pacific Gala on three rootstocks of different vigor: M.9 NAKB 337, M.9 RN 29, and Supporter 4 (in respective order of vigor from dwarfing to semivigorous). The rootstocks were also evaluated for the response to three orchard floor management systems (OFMSs): mulching using alfalfa hay, flame burning, and shallow strip tillage using the Swiss sandwich system (SSS). The experiment was conducted in an experimental orchard planted in 2000.

The triggers of biennial bearing are thought to coincide with embryonic development in apple and occurs within the first 70 days after full bloom (DAFB). Strong evidence suggests hormonal signals are perceived by vegetative apple spur buds to induce flowering. The hormonal response is typically referred to as the floral induction (FI) phase in bud meristem development. To determine the metabolic pathways activated in FI, young trees of the biennial bearing cultivar ‘Nicoter’ and the less susceptible cultivar ‘Rosy Glow’ were forced into an alternate cropping cycle over five years and an inverse relationship of crop load and return bloom was established. Buds were collected over a four-week duration within 70 DAFB from trees that had maintained a four-year biennial bearing cycle. Metabolomics profiling was undertaken to determine the differentially expressed pathways and key signalling molecules associated with biennial bearing. Marked metabolic differences were observed in trees with high and low crop load treatments. Significant effects were detected in members of the phenylpropanoid pathway comprising hydroxycinnamates, salicylates, salicylic acid biosynthetic pathway intermediates and flavanols. This study identifies plant hormones associated with FI in apples using functional metabolomics analysis.