Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: An integrated modelling approach in maize.

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

Estimation of light interception in research environments: A joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions

Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Status assessment of water use research in turf growth and maintenance.

The strategic objectives of Turf Australia (formerly the Turf Producers Association (TPA)) relating to water use in turf are to: • Source and collate information to support the case for adequate access to water for the Turf production and maintenance sectors and • Compile information generated into a convincing communication package that can be readily used by the industry in its advocacy programs (to government, regulators, media etc) More specifically, the turfgrass industry needs unbiased scientific evidence of the value of healthy grass in our environment. It needs to promote the use of adequate water even during drought periods to maintain quality turfgrass, which provides many benefits to the broader community including cooling the environment, saving energy and encouraging healthy lifestyles. The many environmental, social and health benefits of living turfgrass have been the subject of numerous investigations beyond the scope of this review. However further research is needed to fully understand the economic returns achievable by the judicious use of water for the maintenance of healthy turfgrass. Consumer education, backed by scientific evidence will highlight the “false economy” in allowing turfgrass to wither and die during conditions which require high level water restrictions. This report presents a review of the literature pertaining to research in the field of turf water use. The purpose of the review was to better understand the scope and nature of existing research results on turf water relations so that knowledge gaps could be identified in achieving the above strategic objectives of the TPA. Research to date has been found to be insufficient to compile a convincing communication package as described. However, identified knowledge gaps can now be addressed through targeted research. Information derived from targeted research will provide valuable material for education of the end user of turfgrass. Recommendations have been developed, based on the results of this desktop review. It was determined that future research in the field of turf irrigation needs to focus on a number of key factors which directly or indirectly affect the relationship between turfgrass and water use. These factors are: • Climate • Cultivar • Quality • Site use requirements • Establishment and management The overarching recommendation is to develop a strategic plan for turfgrass water relations research based around the five determinants of turf water use listed above. This plan should ensure research under these five categories is integrated into a holistic approach by which the consumer can be guided in species and/or cultivar choices as well as best management practices with respect to turfgrass water relations. Worsening drought cycles and limited supply of water for irrigation were the key factors driving every research project reviewed in this report. Subsidence of the most recent (or current) drought conditions in Australia should not be viewed by the turf industry as a reason to withdraw support or funding for research in this area. Drought conditions, limited domestic water availability and urban water restrictions will return in Australia albeit in 5, 10 or 20 years time and the turf industry has an opportunity to prepare for that time.

Re-thinking mango disease management in Australia; the rationale and approach

The shelf life of mangoes is limited by two main postharvest diseases when not consistently managed. These are anthracnose ( Colletotrichum gloeosporioides) and stem end rots (SER) ( Fusicoccum parvum). The management of these diseases has often relied mainly on the use of fungicides either as field spray treatments or as postharvest dips. These have done a fairly good job at serving the industry and allowing fruits to be transported, stored and sold at markets distant from the areas of production. There are however concerns on the continuous use of these fungicides as the main or only tool for the management of these diseases. This has necessitated a re-think of how these diseases could be sustainably managed into the future using a systems approach that focuses on integrated crop management. It is a holistic approach that considers all the crop protection management strategies including the genetics of the plant and its ability to naturally defend itself from infection with plant activators and growth regulators. It also considers other cultural or agronomic management tools such as the use of crop nutrition, timely application of irrigation water and the pruning of trees on a regular basis as a means of reducing inoculum levels in the orchards. The ultimate aim of this approach is to increase yields and obtain long term sustainable production. It is guided by the sustainable crop production principle which states that producers should apply as little inputs as possible but as much as needed.

A transcriptome approach towards understanding the development of ripening capacity in 'Bartlett' pears (Pyrus communis L.)

Background: The capacity of European pear fruit (Pyrus communis L.) to ripen after harvest develops during the final stages of growth on the tree. The objective of this study was to characterize changes in 'Bartlett' pear fruit physico-chemical properties and transcription profiles during fruit maturation leading to attainment of ripening capacity. Results: The softening response of pear fruit held for 14days at 20°C after harvest depended on their maturity. We identified four maturity stages: S1-failed to soften and S2- displayed partial softening (with or without ET-ethylene treatment); S3 - able to soften following ET; and S4 - able to soften without ET. Illumina sequencing and Trinity assembly generated 68,010 unigenes (mean length of 911bp), of which 32.8% were annotated to the RefSeq plant database. Higher numbers of differentially expressed transcripts were recorded in the S3-S4 and S1-S2 transitions (2805 and 2505 unigenes, respectively) than in the S2-S3 transition (2037 unigenes). High expression of genes putatively encoding pectin degradation enzymes in the S1-S2 transition suggests pectic oligomers may be involved as early signals triggering the transition to responsiveness to ethylene in pear fruit. Moreover, the co-expression of these genes with Exps (Expansins) suggests their collaboration in modifying cell wall polysaccharide networks that are required for fruit growth. K-means cluster analysis revealed that auxin signaling associated transcripts were enriched in cluster K6 that showed the highest gene expression at S3. AP2/EREBP (APETALA 2/ethylene response element binding protein) and bHLH (basic helix-loop-helix) transcripts were enriched in all three transition S1-S2, S2-S3, and S3-S4. Several members of Aux/IAA (Auxin/indole-3-acetic acid), ARF (Auxin response factors), and WRKY appeared to play an important role in orchestrating the S2-S3 transition. Conclusions: We identified maturity stages associated with the development of ripening capacity in 'Bartlett' pear, and described the transcription profile of fruit at these stages. Our findings suggest that auxin is essential in regulating the transition of pear fruit from being ethylene-unresponsive (S2) to ethylene-responsive (S3), resulting in fruit softening. The transcriptome will be helpful for future studies about specific developmental pathways regulating the transition to ripening. © 2015 Nham et al.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14 and 28 days after the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP = 2.6 and R2 = 0.88), followed by 28 DAE (RMSEP = 3.2 and R2 = 0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.