Macadamia Regional Variety Trials Series 3 - Phase 2

Regional variety trials (RVT) established in 1983 and again in 1997 identified superior varieties for the macadamia industry. From the 1983 trials, guidelines were developed to assist growers to select the most appropriate new varieties for their particular orchards and many of these superior varieties have been enthusiastically adopted by industry. This is also being done for varieties in the 1997 trials. Many of the best cultivars have already been adopted by growers on the basis of annual reports of yield and quality. Industry development over the next 10 to 20 years will be largely dependent on new, superior varieties selected in these RVT5, including new selections from the macadamia industry breeding program.

Variety Performance Trialling for the National Variety Trials

Conducting National Variety Testing for wheat, barley, durum and chickpea throughout Queensland.

Oat Variety Trials, 2010 and 2011

Oat is the major spring-sown, small grain crop in Iowa. Spring-sown small grains can be used for grain and straw production, as a companion crop to establish hay and pastures, or as a source of early-season forage as hay or haylage. Because small grains generally mature before the end of July, a forage legume, cover crop, or green manure crop can follow oats, or animal manure can be spread on the field in which oats were grown.

A methodology for analysis of sugarcane productivity trends - 2. Comparing variety trials with commercial productivity

Previous research has reported both agreements and serious anomalies in relationships between production attributes of sugarcane varieties in variety trials (VTs) and commercial production (CP). This paper examines VT and CP data for tonnes of cane per hectare (TCH) and sugar content (CCS). Data, analysed by REML, included 107 VTs and 54 CP mill years for 9 varieties from the mill districts of Mulgrave, Babinda, and Tully for harvest years 1982-99. Important consistencies included high TCH of Q152, high CCS of Q117 and Q120, and low CCS of H56-752. Significant anomalies existed with respect to TCH for Q113, Q117, Q120, Q122, Q138, and H56-752 and to CCS for Q113 and Q124. Investigation of these anomalies was assisted by access to independent REML analyses of CP data for 65692 individual Tully cane blocks from 1988 to 1999 and by the knowledge of persons familiar with the preferential uses of varieties by farmers. Minor anomalies were due to limited year or mill area data. Q124 TCH was deemed to be decreased and its CCS increased by severe disease in Babinda CP in the extremely wet 1998 and 1999 seasons. Other serious anomalies have credible but unsubstantiated explanations. The most convincing, for Q113, Q117, Q138, and H56-752, are that these varieties were deployed unevenly with regard to late season harvesting, predominant use or avoidance on high fertility soils, or use confined to low fertility sandy soils, respectively. Uneven deployment results in confounding of these effects in the varietal CP statistics at mill area level. It is concluded that VTs cannot be enhanced to anticipate or evaluate most effects of uneven deployment. They give adequate predictions of relative CP performance for varieties deployed evenly across confounding influences. Routine analyses of individual block CP data would be useful and enhanced by addition of relevant information to the block records.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Variance-balanced designs under interference for dependent observations

It is shown that variance-balanced designs can be obtained from Type I orthogonal arrays for many general models with two kinds of treatment effects, including ones for interference, with general dependence structures. These designs can be used to obtain optimal and efficient designs. Some examples and design comparisons are given. (C) 2002 Elsevier B.V. All rights reserved.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

Some results on the design of field experiments for comparing unreplicated treatments

In early generation variety trials, large numbers of new breeders' lines need to be compared, and usually there is little seed available for each new line. A so-called unreplicated trial has each new line on just one plot at a site, but includes several (often around five) replicated check or control (or standard) varieties. The total proportion of check plots is usually between 10% and 20%. The aim of the trial is to choose some good performing lines (usually around 1/3 of those tested) to go on for further testing, rather than precise estimation of their mean yield. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis. Some possible design criteria are discussed, and efficient layouts under spatial dependence are considered.

Efficient experimental designs when most treatments are unreplicated

In early generation variety trials, large numbers of new breeders' lines (varieties) may be compared, with each having little seed available. A so-called unreplicated trial has each new variety on just one plot at a site, but includes several replicated control varieties, making up around 10% and 20% of the trial. The aim of the trial is to choose some (usually around one third) good performing new varieties to go on for further testing, rather than precise estimation of their mean yields. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis and an efficiency criterion. Common optimal design criteria values depend on the usual C-matrix, which is very large, and hence it is time consuming to calculate its inverse. Since most varieties are unreplicated, the variety incidence matrix has a simple form, and some matrix manipulations can dramatically reduce the computation needed. However, there are many designs to compare, and numerical optimisation lacks insight into good design features. Some possible design criteria are discussed, and approximations to their values considered. These allow the features of efficient layouts under spatial dependence to be given and compared. (c) 2006 Elsevier Inc. All rights reserved.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

Assessment of permeable covers for odour reduction in piggery effluent ponds. 1. Laboratory-scale trials

A variety of materials were trialed as supported permeable covers using a series of laboratory-scale anaerobic digesters. Efficacy of cover performance was assessed in terms of impact on odour and greenhouse gas emission rate, and the characteristics of anaerobic liquor. Data were collected over a 12-month period. Initially the covers reduced the rate of odour emission 40-100 times relative to uncovered digesters. After about three months, this decreased to about a threefold reduction in odour emission rate, which was maintained over the remainder of the trial. The covers did not alter methane emission rates. Carbon dioxide emission rates varied according to cover type. Performance of the covers was attributed to the physical characteristics of the cover materials and changes in liquor composition. The reductions in odour emission indicate that these covers offer a cost-effective method for odour control.

DNA binders in clinical trials and chemotherapy

Cancer has always been a dreadful disease and continues to attract extensive research investigations. Various targets have been identified to restrain cancer. Among these DNA happens to be the most explored one. A wide variety of small molecules, often referred to as `ligands', has been synthesized to target numerous structural features of DNA. The sole purpose of such molecular design has been to interfere with the transcriptional machinery in order to drive the cancer cell toward apoptosis. The mode of action of the DNA targeting ligands focuses either on the sequence-specificity by groove binding and strand cleavage, or by identifying the morphologically distinct higher order structures like that of the G-quadruplex DNA. However, in spite of the extensive research, only a tiny fraction of the molecules have been able to reach clinical trials and only a handful are used in chemotherapy. This review attempts to record the journey of the DNA binding small molecules from its inception to cancer therapy via various modifications at the molecular level. Nevertheless, factors like limited bioavailability, severe toxicities, unfavorable pharmacokinetics etc. still prove to be the major impediments in the field which warrant considerable scope for further research investigations. (C) 2014 Published by Elsevier Ltd.

On-farm trials with rice fish cultivation in the west Kano rice irrigation scheme, Kenya

The viability of integrating rice farming with fish culture was studied in ten (10) rice plots. The on-farm research was done during one rice-growing season starting May 2003. The rice variety used was IR 2793-80-1 while the fish species was the Nile tilapia, Oreochromis niloticus. The fish culture period lasted 77 days. An average fish production of 132.4 kg/ha was obtained. The mean recovery rate of tilapia was 43 per cent. Total rice yield from the fields stocked with fish was lower than from unstocked fields. The net returns were not significantly different.