64 resultados para Canopy
Resumo:
The spot or strip application of poisoned protein bait is a lure-and-kill technique used for the management of fruit flies. Knowledge of where flies occur in the crop environment is an important part of maximizing the efficacy of this tool. Bactrocera tryoni is a polyphagous pest of horticulture for which very little is known about its distribution within crops. With particular reference to edge effects, we monitored the abundance of B. tryoni in two crops of different architecture; strawberry and apple. In strawberries, we found more flies on the crop edge early in the fruiting season, which lessened gradually and eventually disappeared as the season progressed. In apple orchards, no such edge effect was observed and flies were found equally throughout the orchard. We postulated these differences may be due to differences in crop height (high vs. short) and/or crop canopy architecture (opened and branched in apple, dense and closed in strawberry). In a field cage trial, we tested these predictions using artificial plants of different height and canopy condition. Height and canopy structure type had no significant effects on fly oviposition and protein feeding, but the 'apple' type canopy significantly influenced resting. We thus postulate that there was an edge effect in strawberry because the crop was not providing resting sites and flies were doing so in vegetation around the field margins. The finding that B. tryoni shows different resting site preferences based on plant architecture offers the potential for strategic manipulation of the fly through specific border or inter-row plantings. © 2013 Blackwell Verlag GmbH.
Resumo:
The goal of this research is to understand the function of allelic variation of genes underpinning the stay-green drought adaptation trait in sorghum in order to enhance yield in water-limited environments. Stay-green, a delayed leaf senescence phenotype in sorghum, is primarily an emergent consequence of the improved balance between the supply and demand of water. Positional and functional fine-mapping of candidate genes associated with stay-green in sorghum is the focus of an international research partnership between Australian (UQ/DAFFQ) and US (Texas A&M University) scientists. Stay-green was initially mapped to four chromosomal regions (Stg1, Stg2, Stg3, and Stg4) by a number of research groups in the US and Australia. Physiological dissection of near-isolines containing single introgressions of Stg QTL (Stg1-4) indicate that these QTL reduce water demand before flowering by constricting the size of the canopy, thereby increasing water availability during grain filling and, ultimately, grain yield. Stg and root angle QTL are also co-located and, together with crop water use data, suggest the role of roots in the stay-green phenomenon. Candidate genes have been identified in Stg1-4, including genes from the PIN family of auxin efflux carriers in Stg1 and Stg2, with 10 of 11 PIN genes in sorghum co-locating with Stg QTL. Modified gene expression in some of these PIN candidates in the stay-green compared with the senescent types has been found in preliminary RNA expression profiling studies. Further proof-of-function studies are underway, including comparative genomics, SNP analysis to assess diversity at candidate genes, reverse genetics and transformation.
Resumo:
This paper discusses the role of mango canopy architecture in mango productivity and orchard management and considers potential increases on production of high density orchards through improved canopy architecture. Lower tree height, reduced vigour and smaller more open canopies are recognised as important aspects of high density orchards. However, vigour management, light relations, flowering and crop load of high density orchards needs to be better understood if we are to developed sustainable highly productive canopy training and pruning systems that are easy to maintain at high planting densities.
Resumo:
Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.