Effect of crop establishment methods and weed control treatments on weed management, and rice yield

Lower water availability coupled with labor shortage has resulted in the increasing inability of growers to cultivate puddled transplanted rice (PTR). A field study was conducted in the wet season of 2012 and dry season of 2013 to evaluate the performance of five rice establishment methods and four weed control treatments on weed management, and rice yield. Grass weeds were higher in dry-seeded rice (DSR) as compared to PTR and nonpuddled transplanted rice (NPTR). The highest total weed density (225-256plantsm-2) and total weed biomass (315-501gm-2) were recorded in DSR while the lowest (102-129plantsm-2 and 75-387gm-2) in PTR. Compared with the weedy plots, the treatment pretilachlor followed by fenoxaprop plus ethoxysulfuron plus 2,4-D provided excellent weed control. This treatment, however, had a poor performance in NPTR. In both seasons, herbicide efficacy was better in DSR and wet-seeded rice. PTR and DSR produced the maximum rice grain yields. The weed-free plots and herbicide treatments produced 84-614% and 58-504% higher rice grain yield, respectively, than the weedy plots in 2012, and a similar trend was observed in 2013.

Evaluation of a systems approach to control Queensland fruit fly (Bactrocera tryoni)in stonefruit as an alternative to fenthion

Queensland fruit fly (Bactrocera tryoni) is a significant quarantine pest of stonefruit. To access domestic markets within Australia stonefruit require treatment to ensure they are free of fruit flies. Due to the recent restriction of the organophosphate pesticides, fenthion and dimethoate, the stonefruit industry now faces a significant challenge to control fruit flies. In this field trial we quantified the level of control achieved by a 'best case' systems approach that relied on currently available and registered control measures. This system included protein bait sprays, Male Annihilation Technique, insecticide cover sprays of trichlorfon, maldison and spinetoram and inspection and culling of damaged fruit. We found that in two out of the three trial orchards, packed fruit samples from Gatton (QLD) and Bangalow (NSW) had low levels of fruit fly infestation; 1.47 and 2.97% respectively. However, at the third property located at Alstonville (NSW) a high level of infestation (51.63%) was found in packed nectarines, which was likely attributed to the late implementation of the systems approach. This trial has demonstrated the potential for fruit fly control without relying on fenthion, however further modification of the system is needed to refine and increase efficacy.

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.

Development of cyanide for feral pig and fox control

This report provides an overview of a series of pig- and fox-baiting research projects conducted 2005–2010. It is intended to collate and summarise the outcomes of these unpublished projects, including the completed pen and field trials, and provide recommendations for future research. This review will provide a useful reference document to support further research.

Rain Damage to Strawberries Grown in Southeast Queensland: Evaluation and Genetic Control.

In Queensland, Australia, strawberries (Fragaria xananassa Duchesne) are grown in open fields and rainfall events can damage fruit. Cultivars that are resistant to rain damage may reduce losses and lower risk for the growers. However, little is known about the genetic control of resistance and in a subtropical climate, unpredictable rainfall events hamper evaluation. Rain damage was evaluated on seedling and clonal trials of one breeding population comprising 645 seedling genotypes and 94 clones and on a second clonal population comprising 46 clones from an earlier crossing to make preliminary estimates of heritability. The incidence of field damage from rainfall and damage after laboratory soaking was evaluated to determine if this soaking method could be used to evaluate resistance to rain damage. Narrow-sense heritability of resistance to rain damage calculated for seedlings was low (0.21 +/- 0.15) and not significantly different from zero; however, broad-sense heritability estimates were moderate in both seedlings (0.49 +/- 0.16) and clones (0.45 +/- 0.08) from the first population and similar in clones (0.56 +/- 0.21) from the second population. Immersion of fruit in deionized water produced symptoms consistent with rain damage in the field. Lengthening the duration of soaking of 'Festival' fruit in deionized water exponentially increased the proportion of damage to fruit ranging in ripeness from immature to ripe during the first 6-h period of soaking. When eight genotypes were evaluated, the proportion of sound fruit after soaking in deionized water in the laboratory for up to 5 h was linearly related (r(2) = 0.90) to the proportion of sound fruit in the field after 89 mm of rain. The proportion of sound fruit of the breeding genotype '2008-208' and 'Festival' under soaking (0.67, 0.60) and field (0.52, 0.43) evaluations, respectively, is about the same and these genotypes may be useful sources of resistance to rain damage.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

Pythium soft rot of ginger: Detection and identification of the causal pathogens, and their control

Ginger is considered by many people to be the outstanding member among 1400 other species in the family Zingiberaceae. Not only it is a valuable spice used by cooks throughout the world to impart unique flavour to their dishes but it also has a long track record in some Chinese and Indian cultures for treating common human ailments such as colds and headaches. Ginger has recently attracted considerable attention for its anti-inflammatory, antibacterial and antifungal properties. However, ginger as a crop is also susceptible to at least 24 different plant pathogens, including viruses, bacteria, fungi and nematodes. Of these, Pythium spp. (within the kingdom Stramenopila, phyllum Oomycota) are of most concern because various species can cause rotting and yield loss on ginger at any of the growth stages including during postharvest storage. Pythium gracile was the first species in the genus to be reported as a ginger pathogen, causing Pythium soft rot disease in India in 1907. Thereafter, numerous other Pythium spp. have been recorded from ginger growing regions throughout the world. Today, 15 Pythium species have been implicated as pathogens of the soft rot disease. Because accurate identification of a pathogen is the cornerstone of effective disease management programs, this review will focus on how to detect, identify and control Pythium spp. in general, with special emphasis on Pythium spp. associated with soft rot on ginger.

Cotton root systems and recovery of applied P and K fertilisers

With potential to accumulate substantial amounts of above-ground biomass, at maturity an irrigated cotton crop can have taken up more than 20 kg/ha phosphorus and often more than 200 kg/ha of potassium. Despite the size of plant accumulation of P and K, recovery of applied P and K fertilisers by the crop in our field experiment program has poor. Processing large amounts of mature cotton plant material to provide a representative sample for chemical analysis has not been without its challenges, but the questions regarding mechanism of where, how and when the plant is acquiring immobile nutrients remain. Dry matter measured early in the growing season (squaring, first white flower) have demonstrated a 50% increase in crop biomass to applied P (in particular), but it represents only 20% of the total P accumulation by the plant. By first open boll (and onwards), no response in dry matter or P concentration could be detected to P application. A glasshouse study indicated P recovery was greater (to FOB) where it was completely mixed through a profile as opposed to a banded application method suggesting cotton prefers a more diffuse distribution. The relative effects of root morphology, mycorrhizal fungi infection, seasonal growth patterns and how irrigation is applied are areas for future investigation on how, when and where cotton acquires immobile nutrients.