Modified Atmosphere Packaging (MAP) for Control of Black Spot Formation in Chilled Prawns

The marketing of organically labeled prawns is predominately in a cooked or raw frozen form to avoid the development of melanosis (black spot). Certification for organic status prohibits the use of any added chemicals. The application of 60% CO2/40%N2 modified atmosphere to chilled (raw) prawns using two species of prawn was investigated for the ability to control black spot formation. Sensory assessment and microbiological counts were used to determine the end of product shelf life. Modified atmosphere packaged (MAP) prawns exhibited no melanosis for up to 16 days. The high quality life was retained for 12 days; shelf life of 16 days, according to standard microbiological criteria, was achieved, which is more than twice previously reported for non-MAP prawns. Results suggest MAP may be an effective method for the marketing of organically grown prawns as well as those produced by conventional prawn aquaculture without application of the normal chemicals used to prevent black spot. Copyright © 2014 Crown Copyright.

Post-head-emergence frost in wheat and barley: defining the problem, assessing the damage, and identifying resistance

Radiant frost is a significant production constraint to wheat (Triticum aestivum) and barley (Hordeum vulgare), particularly in regions where spring-habit cereals are grown through winter, maturing in spring. However, damage to winter-habit cereals in reproductive stages is also reported. Crops are particularly susceptible to frost once awns or spikes emerge from the protection of the flag leaf sheath. Post-head-emergence frost (PHEF) is a problem distinct from other cold-mediated production constraints. To date, useful increased PHEF resistance in cereals has not been identified. Given the renewed interest in reproductive frost damage in cereals, it is timely to review the problem. Here we update the extent and impacts of PHEF and document current management options to combat this challenge. We clarify terminology useful for discussing PHEF in relation to chilling and other freezing stresses. We discuss problems characterizing radiant frost, the environmental conditions leading to PHEF damage, and the effects of frost at different growth stages. PHEF resistant cultivars would be highly desirable, to both reduce the incidence of direct frost damage and to allow the timing of crop maturity to be managed to maximize yield potential. A framework of potential adaptation mechanisms is outlined. Clarification of these critical issues will sharpen research focus, improving opportunities to identify genetic sources for improved PHEF resistance.

Post-head-emergence frost in wheat and barley: defining the problem, assessing the damage, and identifying resistance

Radiant frost is a significant production constraint to wheat (Triticum aestivum) and barley (Hordeum vulgare), particularly in regions where spring-habit cereals are grown through winter, maturing in spring. However, damage to winter-habit cereals in reproductive stages is also reported. Crops are particularly susceptible to frost once awns or spikes emerge from the protection of the flag leaf sheath. Post-head-emergence frost (PHEF) is a problem distinct from other cold-mediated production constraints. To date, useful increased PHEF resistance in cereals has not been identified. Given the renewed interest in reproductive frost damage in cereals, it is timely to review the problem. Here we update the extent and impacts of PHEF and document current management options to combat this challenge. We clarify terminology useful for discussing PHEF in relation to chilling and other freezing stresses. We discuss problems characterizing radiant frost, the environmental conditions leading to PHEF damage, and the effects of frost at different growth stages. PHEF resistant cultivars would be highly desirable, to both reduce the incidence of direct frost damage and to allow the timing of crop maturity to be managed to maximize yield potential. A framework of potential adaptation mechanisms is outlined. Clarification of these critical issues will sharpen research focus, improving opportunities to identify genetic sources for improved PHEF resistance.

Stem anatomy and adventitious root formation in cuttings of Angophora, Corymbia and Eucalyptus

Many plantation eucalypts are difficult to propagate from cuttings, and their rooted cuttings often possess very few adventitious roots. We microscopically examined the stem anatomy of cuttings from 12 species of eucalypts and we determined whether adventitious root formation in auxin-treated cuttings of four species was limited to particular positions around the vascular tissue. Most species contained a central pith that was arranged in a four-pointed stellate pattern. The surrounding vascular tissue was also arranged in a stellate pattern near the shoot apex but it developed a more rectangular shape at the outer phloem as the stems enlarged radially. Adventitious roots formed at, or slightly peripheral to, the vascular cambium, and they formed at both the corners and the sides of the rectangular-shaped vascular tissue. The study highlighted that auxin-treated eucalypt cuttings can produce roots at multiple positions around the vascular tissue and so propagation methods can aim to produce more than four adventitious roots per rooted cutting. Higher numbers of adventitious roots could improve the root system symmetry, stability, survival and growth rate of clonal eucalypt trees. © 2015 by the authors; licensee MDPI, Basel, Switzerland.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

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.