Accelerating leaf area measurement using a volumetric approach.

BACKGROUND: Despite the advances in the techniques of indirect estimation of leaf area, the destructive measurement approaches have still remained as the reference and the most accurate methods. However, even utilizing the modern sensors and applications usually requires the laborious and time-consuming practice of unfolding and analyzing the single leaves, separately. In the present study, a volumetric approach was tested to determine the pile leaf area based on the ratio of leaf volume divided by thickness. For this purpose, the suspension technique was used for volumetry, which is based on the simple practice and calculations of the Archimedes' principle. RESULTS: Wheat volumetric leaf area (VLA), had a high agreement and approximately 1:1 correlation with the conventionally measured optical leaf area (OLA). Exclusion of the midrib volume from calculations, did not affect the estimation error (NRMSE < 2.61%); however, improved the slope of the linear model by about 6%, and also reduced the bias between the methods. The error of sampling for determining mean leaf thickness of the pile, was also less than 2% throughout the season. Besides, a more practical and facilitated version of pile volumetry was tested using Specific Gravity Bench (SGB), which is currently available as a laboratory equipment. As an important observation, which was also expectable according to the leaf 3D expansion (i.e., in a given 2D plane), it was evidenced that the variations in the OLA exactly follows the pattern of the changes in the leaf volume. Accordingly, it was suggested that the relative leaf areas of various experimental treatments might be compared directly based on volume, and independently of leaf thickness. Furthermore, no considerable difference was observed among the OLAs measured using various image resolutions (NRMSE < 0.212%); which indicates that even the superfast scanners with low resolutions as 200 dpi may be used for a precision optical measurement of leaf area. CONCLUSIONS: It is expected that utilizing the reliable and simple concept of volumetric leaf area, based on which the measurement time might be independent of sample size, facilitate the laborious practice of leaf area measurement; and consequently, improve the precision of field experiments.

Wheat grain width: a clue for re-exploring visual indicators of grain weight.

BACKGROUND: Mean grain weight (MGW) is among the most frequently measured parameters in wheat breeding and physiology. Although in the recent decades, various wheat grain analyses (e.g. counting, and determining the size, color, or shape features) have been facilitated, thanks to the automated image processing systems, MGW estimations have been limited to using few number of image-derived indices; i.e. mainly the linear or power models developed based on the projected area (Area). Following a preliminary observation which indicated the potential of grain width in improving the predictions, the present study was conducted to explore more efficient indices for increasing the precision of image-based MGW estimations. For this purpose, an image archive of the grains was processed, which were harvested from a 2-year field experiment carried out with 3 replicates under two irrigation conditions and included 15 cultivar mixture treatments (so the archive was consisted of 180 images including more than 72,000 grains). RESULTS: It was observed that among the more than 30 evaluated indices of grain size and shape, indicators of grain width (i.e. Minor & MinFeret) along with 8 other empirical indices had a higher correlation with MGW, compared with Area. The most precise MGW predictions were obtained using the Area × Circularity, Perimeter × Circularity, and Area/Perimeter indices. Furthermore, it was found that (i) grain width and the Area/Perimeter ratio were the common factors in the structure of the superior predictive indices; and (ii) the superior indices had the highest correlation with grain width, rather than with their mathematical components. Moreover, comparative efficiency of the superior indices almost remained stable across the 4 environmental conditions. Eventually, using the selected indices, ten simple linear models were developed and validated for MGW prediction, which indicated a relatively higher precision than the current Area-based models. The considerable effect of enhancing image resolution on the precision of the models has been also evidenced. CONCLUSIONS: It is expected that the findings of the present study, along with the simple predictive linear models developed and validated using new image-derived indices, could improve the precision of the image-based MGW estimations, and consequently facilitate wheat breeding and physiological assessments.

The Potential of the Synthetic Strigolactone Analogue GR24 for the Maintenance of Photosynthesis and Yield in Winter Wheat under Drought: Investigations on the Mechanisms of Action and Delivery Modes.

Strigolactones (SLs) have been implicated in many plant biological and physiological processes, including the responses to abiotic stresses such as drought, in concert with other phytohormones. While it is now clear that exogenous SLs may help plants to survive in harsh environmental condition, the best, most effective protocols for treatment have not been defined yet, and the mechanisms of action are far from being fully understood. In the set of experiments reported here, we contrasted two application methods for treatment with a synthetic analog of SL, GR24. A number of morphometric, physiological and biochemical parameters were measured following foliar application of GR24 or application in the residual irrigation water in winter wheat plants under irrigated and drought stress conditions. Depending on the concentration and the method of GR24 application, differentiated photosynthesis and transpiration rate, stomatal conductance, leaf water potential, antioxidant enzyme activities and yield in drought conditions were observed. We present evidence that different methods of GR24 application led to increased photosynthesis and yield under stress by a combination of drought tolerance and escape factors, which should be considered for future research exploring the potential of this new family of bioactive molecules for practical applications.

Physiological and antioxidant responses of winter wheat cultivars to strigolactone and salicylic acid in drought.

Strigolactones are considered as important regulators of plant growth and development. Recently positive regulatory influence of strigolactones in plant in response to drought and salt stress has been revealed. Salicylic acid, a phytohormone, has reported to be involved in a number of stress responses such as pathogen infection, UV irradiation, salinity and drought. Considering the concealed role of strigolactones in agronomic crops drought tolerance and possible interaction among salicylic acid and strigolactone, we investigated the effects of exogenous application of GR24 and salicylic acid on two winter wheat cultivars under drought conditions. Foliar GR24 and salicylic acid were applied on drought sensitive and drought tolerant winter wheat cultivars at tillering and anthesis stages in 40% and 80% of field capacity moisture levels. Strigolactones and salicylic acid treated plants showed higher tolerance to drought stress with regard to lower electrolyte leakage and higher relative water content, leaf stomatal limitation, membrane stability index and antioxidant enzyme activities. Salicylic acid application dampened malondialdehyde content in wheat plants. Drought tolerance of wheat plants were intensified in most of the cases when theses phytohormones were used together, suggesting a possible interaction between salicylic acid and strigolactones in drought situations.

Determining the most important physiological and agronomic traits contributing to maize grain yield through machine learning algorithms: a new avenue in intelligent agriculture.

Prediction is an attempt to accurately forecast the outcome of a specific situation while using input information obtained from a set of variables that potentially describe the situation. They can be used to project physiological and agronomic processes; regarding this fact, agronomic traits such as yield can be affected by a large number of variables. In this study, we analyzed a large number of physiological and agronomic traits by screening, clustering, and decision tree models to select the most relevant factors for the prospect of accurately increasing maize grain yield. Decision tree models (with nearly the same performance evaluation) were the most useful tools in understanding the underlying relationships in physiological and agronomic features for selecting the most important and relevant traits (sowing date-location, kernel number per ear, maximum water content, kernel weight, and season duration) corresponding to the maize grain yield. In particular, decision tree generated by C&RT algorithm was the best model for yield prediction based on physiological and agronomical traits which can be extensively employed in future breeding programs. No significant differences in the decision tree models were found when feature selection filtering on data were used, but positive feature selection effect observed in clustering models. Finally, the results showed that the proposed model techniques are useful tools for crop physiologists to search through large datasets seeking patterns for the physiological and agronomic factors, and may assist the selection of the most important traits for the individual site and field. In particular, decision tree models are method of choice with the capability of illustrating different pathways of yield increase in breeding programs, governed by their hierarchy structure of feature ranking as well as pattern discovery via various combinations of features.

Root hydraulics in salt-stressed wheat.

The aim of the present study was to test whether salinity, which can impact through its osmotic stress component on the ability of plants to take up water, affects root water transport properties (hydraulic conductivity) in bread wheat (Triticum aestivum L). Hydroponically grown plants were exposed to 100mM NaCl when they were 10-11 days old. Plants were analysed during the vegetative stage of development when they were 15-17 days old and the root system consisted entirely of seminal roots, and when they were 22-24 days old, by which time adventitious roots had developed. Root hydraulic conductivity (Lp) was determined through exudation experiments (osmotic Lp) on individual roots and the entire plant root system, and through experiments involving intact, transpiring plants (hydrostatic Lp). Salt stress caused a general reduction (40-80%) in Lp, irrespective of whether individual seminal and adventitious roots, entire root systems or intact, transpiring plants were analysed. Osmotic and hydrostatic Lp were in the same range. The data suggest that most radial root water uptake in wheat grown in the presence and absence of NaCl occurs along a pathway that involves the crossing of membranes. As wheat plants develop, a nonmembraneous (apoplast) pathway contributes increasingly to radial water uptake in control but not in NaCl-stressed plants.