Field evaluation of 64 rootstocks for growth and yield of 'Kensington Pride' mango

Despite an abundance of polyembryonic genotypes and the need for rootstocks that improve scion yield and productivity, simultaneous field testing of a wide range of mango (Mangifera indica L.) genotypes as rootstocks has not previously been reported. In this experiment, we examined the growth and yield of 'Kensington Pride' on 64 mango genotypes of diverse origin during the first four seasons of fruit production to identify those worth longer-term assessment. We also recorded morphological characteristics of seedlings of 46 of these genotypes in an attempt to relate these measures to subsequent field performance. Tree canopy development on the most vigorous rootstocks was almost double that on the least vigorous. Growth rates differed by more than 160%. Cumulative marketable yield ranged from 36 kg/tree for the lowest yielding rootstock to 181 kg/tree for the most productive. Yield efficiency also differed markedly among the 64 rootstocks with the best treatment being 3.5 times more efficient than the poorest treatment. No relationship was found between yield efficiency and tree size, suggesting it is possible to select highly efficient rootstocks of differing vigor. Two genotypes ('Brodie' and 'MYP') stood out as providing high yield efficiency with small tree size. A further two genotypes ('B' and 'Watertank') were identified as offering high yield efficiency and large tree size and should provide high early yields at traditional tree spacing. Efforts to relate the morphology of different genotype seedlings to subsequent performance as a rootstock showed that nursery performance of mango seedlings is no indication of their likely behavior as a rootstock. The economic cost of poor yields and low yield efficiencies during the early years of commercial orchard production provide a rationale for culling many of the rootstock treatments in this experiment and concentrating future assessment on the top ~20% of the 64 treatments. Of these, 'MYP', 'B', 'Watertank', 'Manzano', and 'Pancho' currently show the most promise.

DNA markers linked to yield, yield components, and morphological traits in autotetraploid lucerne (Medicago sativa L.)

We have mapped and identified DNA markers linked to morphology, yield, and yield components of lucerne, using a backcross population derived from winter-active parents. The high-yielding and recurrent parent, D, produced individual markers that accounted for up to 18% of total yield over 6 harvests, at Gatton, south-eastern Queensland. The same marker, AC/TT8, was consistently identified at each individual harvest, and in individual harvests accounted for up to 26% of the phenotypic variation for yield. This marker was located in linkage group 2 of the D map, and several other markers positively associated with yield were consistently identified in this linkage group. Similarly, markers negatively associated with yield were consistently identified in the W116 map, W116 being the low-yielding parent. Highly significant positive correlations were observed between total yield and yield for harvests 1-6, and between total yield and stem length, tiller number, leaf yield/plant, leaf yield/5 stems, stem yield/plant, and stem yield/5 stems. Highly significant QTL were located for all these characters as well as for leaf shape and pubescence.

Row spacing and planting density effects on the growth and yield of sugarcane. 1. Responses in fumigated and non-fumigated soil.

It has been reported that high-density planting of sugarcane can improve cane and sugar yield through promoting rapid canopy closure and increasing radiation interception earlier in crop growth. It is widely known that the control of adverse soil biota through fumigation (removes soil biological constraints and improves soil health) can improve cane and sugar yield. Whether the responses to high-density planting and improved soil health are additive or interactive has important implications for the sugarcane production system. Field experiments established at Bundaberg and Mackay, Queensland, Australia, involved all combinations of 2-row spacings (0.5 and 1.5 m), two planting densities (27 000 and 81 000 two-eyed setts/ha), and two soil fumigation treatments (fumigated and non-fumigated). The Bundaberg experiment had two cultivars (Q124, Q155), was fully irrigated, and harvested 15 months after planting. The Mackay experiment had one cultivar (Q117), was grown under rainfed conditions, and harvested 10 months after planting. High-density planting (81 000 setts/ha in 0.5-m rows) did not produce any more cane or sugar yield at harvest than low-density planting (27 000 setts/ha in 1.5-m rows) regardless of location, crop duration (15 v. 10 months), water supply (irrigated v. rainfed), or soil health (fumigated v. non-fumigated). Conversely, soil fumigation generally increased cane and sugar yields regardless of site, row spacing, and planting density. In the Bundaberg experiment there was a large fumigation x cultivar x density interaction (P<0.01). Cultivar Q155 responded positively to higher planting density in non-fumigated soil but not in fumigated soil, while Q124 showed a negative response to higher planting density in non-fumigated soil but no response in fumigated soil. In the Mackay experiment, Q117 showed a non-significant trend of increasing yield in response to increasing planting density in non-fumigated soil, similar to the Q155 response in non-fumigated soil at Bundaberg. The similarity in yield across the range of row spacings and planting densities within experiments was largely due to compensation between stalk number and stalk weight, particularly when fumigation was used to address soil health. Further, the different cultivars (Q124 and Q155 at Bundaberg and Q117 at Mackay) exhibited differing physiological responses to the fumigation, row spacing, and planting density treatments. These included the rate of tiller initiation and subsequent loss, changes in stalk weight, and propensity to lodging. These responses suggest that there may be potential for selecting cultivars suited to different planting configurations.

Row spacing and planting density effects on the growth and yield of sugarcane. 2. Strategies for the adoption of controlled traffic.

Controlled traffic (matching wheel and row spacing) is being promoted as a means to manage soil compaction in the Australian sugar industry. However, machinery limitations dictate that wider row spacings than the standard 1.5-m single row will need to be adopted to incorporate controlled traffic and many growers are reluctant to widen row spacing for fear of yield penalties. To address these concerns, contrasting row configuration and planting density combinations were investigated for their effect on cane and sugar yield in large-scale experiments in the Gordonvale, Tully, Ingham, Mackay, and Bingera (near Bundaberg) sugarcane-growing regions of Queensland, Australia. The results showed that sugarcane possesses a capacity to compensate for different row configurations and planting densities through variation in stalk number and individual stalk weight. Row configurations ranging from 1.5-m single rows (the current industry standard) to 1.8-m dual rows (50 cm between duals), 2.1-m dual (80 cm between duals) and triple ( 65 cm between triples) rows, and 2.3-m triple rows (65 cm between triples) produced similar yields. Four rows (50 cm apart) on a 2.1-m configuration (quad rows) produced lower yields largely due to crop lodging, while a 1.8-m single row configuration produced lower yields in the plant crop, probably due to inadequate resource availability (water stress/limited radiation interception). The results suggest that controlled traffic can be adopted in the Australian sugar industry by changing from a 1.5-m single row to 1.8-m dual row configuration without yield penalty. Further, the similar yields obtained with wider row configurations (2 m or greater with multiple rows) in these experiments emphasise the physiological and environmental plasticity that exists in sugarcane. Controlled traffic can be implemented with these wider row configurations (>2 m), although it will be necessary to carry out expensive modifications to the current harvester and haul-out equipment. There were indications from this research that not all cultivars were suited to configurations involving multiple rows. The results suggest that consideration be given to assessing clones with different growth habits under a range of row configurations to find the most suitable plant types for controlled traffic cropping systems.

Pre-cropping with canola decreased Pratylenchus thornei populations, arbuscular mycorrhizal fungi, and yield of wheat.

Root-lesion nematode (Pratylenchus thornei) significantly reduces wheat yields in the northern Australian grain region. Canola is thought to have a 'biofumigation' potential to control nematodes; therefore, a field experiment was designed to compare canola with other winter crops or clean-fallow for reducing P. thornei population densities and improving growth of P. thornei-intolerant wheat (cv. Batavia) in the following year. Immediately after harvest of the first-year crops, populations of P. thornei were lowest following various canola cultivars or clean-fallow (1957-5200 P. thornei/kg dry soil) and were highest following susceptible wheat cultivars (31 033-41 294/kg dry soil). Unexpectedly, at planting of the second-year wheat crop, nematode populations were at more uniform lower levels (<5000/kg dry soil), irrespective of the previous season's treatment, and remained that way during the growing season, which was quite dry. Growth and grain yield of the second-year wheat crop were poorest on plots previously planted with canola or left fallow due to poor colonisation with arbuscular mycorrhizal (AM) fungi, with the exception of canola cv. Karoo, which had high AM fungal colonisation and low wheat yields. There were significant regressions between growth and yield parameters of the second-year wheat and levels of AMF following the pre-crop treatments. Thus, canola appears to be a good crop for reducing P. thornei populations, but AM fungal-dependence of subsequent crops should be considered, particularly in the northern Australian grain region.

Microbial indicators related to yield and disease and changes in soil microbial community structure with ginger farm management practices

TRFLP (terminal restriction fragment length polymorphism) was used to assess whether management practices that improved disease suppression and/or yield in a 4-year ginger field trial were related to changes in soil microbial community structure. Bacterial and fungal community profiles were defined by presence and abundance of terminal restriction fragments (TRFs), where each TRF represents one or more species. Results indicated inclusion of an organic amendment and minimum tillage increased the relative diversity of dominant fungal populations in a system dependant way. Inclusion of an organic amendment increased bacterial species richness in the pasture treatment. Redundancy analysis showed shifts in microbial community structure associated with different management practices and treatments grouped according to TRF abundance in relation to yield and disease incidence. ANOVA also indicated the abundance of certain TRFs was significantly affected by farming system management practices, and a number of these TRFs were also correlated with yield or disease suppression. Further analyses are required to determine whether identified TRFs can be used as general or soil-type specific bio-indicators of productivity (increased and decreased) and Pythium myriotylum suppressiveness.

Wheat biomass and yield increased when populations of the root-lesion nematode (Pratylenchus thornei) were reduced through sequential rotation of partially resistant winter and summer crops

The root-lesion nematode, Pratylenchus thornei, can reduce wheat yields by >50%. Although this nematode has a broad host range, crop rotation can be an effective tool for its management if the host status of crops and cultivars is known. The summer crops grown in the northern grain region of Australia are poorly characterised for their resistance to P. thornei and their role in crop sequencing to improve wheat yields. In a 4-year field experiment, we prepared plots with high or low populations of P. thornei by growing susceptible wheat or partially resistant canaryseed (Phalaris canariensis); after an 11-month, weed-free fallow, several cultivars of eight summer crops were grown. Following another 15-month, weed-free fallow, P. thornei-intolerant wheat cv. Strzelecki was grown. Populations of P. thornei were determined to 150 cm soil depth throughout the experiment. When two partially resistant crops were grown in succession, e.g. canaryseed followed by panicum (Setaria italica), P. thornei populations were <739/kg soil and subsequent wheat yields were 3245 kg/ha. In contrast, after two susceptible crops, e.g. wheat followed by soybean, P. thornei populations were 10 850/kg soil and subsequent wheat yields were just 1383 kg/ha. Regression analysis showed a linear, negative response of wheat biomass and grain yield with increasing P. thornei populations and a predicted loss of 77% for biomass and 62% for grain yield. The best predictor of wheat yield loss was P. thornei populations at 0-90 cm soil depth. Crop rotation can be used to reduce P. thornei populations and increase wheat yield, with greatest gains being made following two partially resistant crops grown sequentially.

Stay-green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns

* Stay-green is an integrated drought adaptation trait characterized by a distinct green leaf phenotype during grain filling under terminal drought. We used sorghum (Sorghum bicolor), a repository of drought adaptation mechanisms, to elucidate the physiological and genetic mechanisms underpinning stay-green. * Near-isogenic sorghum lines (cv RTx7000) were characterized in a series of field and managed-environment trials (seven experiments and 14 environments) to determine the influence of four individual stay-green (Stg1–4) quantitative trait loci (QTLs) on canopy development, water use and grain yield under post-anthesis drought. * The Stg QTL decreased tillering and the size of upper leaves, which reduced canopy size at anthesis. This reduction in transpirational leaf area conserved soil water before anthesis for use during grain filling. Increased water uptake during grain filling of Stg near-isogenic lines (NILs) relative to RTx7000 resulted in higher post-anthesis biomass production, grain number and yield. Importantly, there was no consistent yield penalty associated with the Stg QTL in the irrigated control. * These results establish a link between the role of the Stg QTL in modifying canopy development and the subsequent impact on crop water use patterns and grain yield under terminal drought.

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum

Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

Effect of biochar amendment on yield and photosynthesis of peanut on two types of soils

Abstract Biochar has significant potential to improve crop performance. This study examined the effect of biochar application on the photosynthesis and yield of peanut crop grown on two soil types. The commercial peanut cultivar Middleton was grown on red ferrosol and redoxi-hydrosol (Queensland, Australia) amended with a peanut shell biochar gradient (0, 0.375, 0.750, 1.50, 3.00 and 6.00 %, w/w, equivalent up to 85 t ha−1) in a glasshouse pot experiment. Biomass and pod yield, photosynthesis-[CO2] response parameters, leaf characteristics and soil properties (carbon, nitrogen (N) and nutrients) were quantified. Biochar significantly improved peanut biomass and pod yield up to 2- and 3-folds respectively in red ferrosol and redoxi-hydrosol. A modest (but significant) biochar-induced improvement of the maximumelectron transport rate and saturating photosynthetic rate was observed for red ferrosol. This response was correlated to increased leaf N and accompanied with improved soil available N and biological N fixation. Biochar application also improved the availability of other soil nutrients, which appeared critical in improving peanut performance, especially on infertile redoxihydrosol. Our study suggests that application of peanut shell derived biochar has strong potential to improve peanut yield on red ferrosol and redoxi-hydrosol. Biochar soil amendment can affect leaf N status and photosynthesis, but the effect varied with soil type.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

Simulating crop-parasitic weed interactions using APSIM: Model evaluation and application

The parasitic weed Orobanche crenata inflicts major damage on faba bean, lentil, pea and other crops in Mediterranean environments. The development of methods to control O. crenata is to a large extent hampered by the complexity of host-parasite systems. Using a model of host-parasite interactions can help to explain and understand this intricacy. This paper reports on the evaluation and application of a model simulating host-parasite competition as affected by environment and management that was implemented in the framework of the Agricultural Production Systems Simulator (APSIM). Model-predicted faba bean and O. crenata growth and development were evaluated against independent data. The APSIM-Fababean and -Parasite modules displayed a good capability to reproduce effects of pedoclimatic conditions, faba bean sowing date and O. crenata infestation on host-parasite competition. The r(2) values throughout exceeded 0.84 (RMSD: 5.36 days) for phenological, 0.85 (RMSD: 223.00 g m(-2)) for host growth and 0.78 (RMSD: 99.82 g m(-2)) for parasite growth parameters. Inaccuracies of simulated faba bean root growth that caused some bias of predicted parasite number and host yield loss may be dealt with by more flexibly simulating vertical root distribution. The model was applied in simulation experiments to determine optimum sowing windows for infected and non-infected faba bean in Mediterranean environments. Simulation results proved realistic and testified to the capability of APSIM to contribute to the development of tactical approaches in parasitic weed control.

Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.