High-throughput shoot phenotyping reveals temporal growth responses to nitrogen and inorganic and organic phosphorus sources in tomato.

The application of nitrogen (N) and phosphorus (P) fertilizers to soils is required to maintain crop yields, so the sufficient and timely delivery of nutrients to match crop demand is important in fertilizer management. We quantified temporal growth responses of tomato plants with different rates of N and P application using high-throughput shoot phenotyping. The tomato plants were grown in soil that had organic, inorganic or a combination of sources of P incorporated. Additional N was added to each pot at low and high rates, 13 days after planting. At the same rate of total P application, the inorganic P source resulted in greater shoot growth at the early time points. Later on, the plants supplied with organic or mixed P sources grew faster than those that received the inorganic P source, resulting in comparable shoot biomass in all treatments at the time of destructive harvest. The shoot phenotyping data demonstrated that readily available soil P was important for early tomato growth while available N was more important in later stages of vegetative growth. These results suggest that a fertilizer formulation of combined inorganic and organic P sources may be able to sustain rapid and great shoot growth in tomato plants, while also reducing additional N input.

Improved Salinity Tolerance-Associated Variables Observed in EMS Mutagenized Wheat Lines.

Salinity tolerance-associated phenotypes of 35 EMS mutagenized wheat lines originating from BARI Gom-25 were compared. Vegetative growth was measured using non-destructive image-based phenotyping. Five different NaCl concentrations (0 to 160 mM) were applied to plants 19 days after planting (DAP 19), and plants were imaged daily until DAP 38. Plant growth, water use, leaf Na+, K+ and Cl- content, and thousand kernel weight (TKW) were measured, and six lines were selected for further analysis. In saline conditions, leaf Na+, K+, and Cl- content variation on a dry weight basis within these six lines were ~9.3, 1.4, and 2.4-fold, respectively. Relative to BARI Gom-25, two (OA6, OA62) lines had greater K+ accumulation, three (OA6, OA10, OA62) had 50-75% lower Na+:K+ ratios, and OA62 had ~30% greater water-use index (WUI). OA23 had ~2.2-fold greater leaf Na+ and maintained TKW relative to BARI Gom-25. Two lines (OA25, OA52) had greater TKW than BARI Gom-25 when grown in 120 mM NaCl but similar Na+:K+, WUI, and biomass accumulation. OA6 had relatively high TKW, high leaf K+, and WUI, and low leaf Na+ and Cl-. Phenotypic variation revealed differing associations between the parameters measured in the lines. Future identification of the genetic basis of these differences, and crossing of lines with phenotypes of interest, is expected to enable the assessment of which combinations of parameters deliver the greatest improvement in salinity tolerance.

Identifying the genetic control of salinity tolerance in the bread wheat landrace Mocho de Espiga Branca.

Salinity tolerance in bread wheat is frequently reported to be associated with low leaf sodium (Na+) concentrations. However, the Portuguese landrace, Mocho de Espiga Branca, accumulates significantly higher leaf Na+ but has comparable salinity tolerance to commercial bread wheat cultivars. To determine the genetic loci associated with the salinity tolerance of this landrace, an F2 mapping population was developed by crossing Mocho de Espiga Branca with the Australian cultivar Gladius. The population was phenotyped for 19 salinity tolerance subtraits using both non-destructive and destructive techniques. Genotyping was performed using genotyping-by-sequencing (GBS). Genomic regions associated with salinity tolerance were detected on chromosomes 1A, 1D, 4B and 5A for the subtraits of relative and absolute growth rate (RGR, AGR respectively), and on chromosome 2A, 2B, 4D and 5D for Na+, potassium (K+) and chloride (Cl-) accumulation. Candidate genes that encode proteins associated with salinity tolerance were identified within the loci including Na+/H+ antiporters, K+ channels, H+-ATPase, calcineurin B-like proteins (CBLs), CBL-interacting protein kinases (CIPKs), calcium dependent protein kinases (CDPKs) and calcium-transporting ATPase. This study provides a new insight into the genetic control of salinity tolerance in a Na+ accumulating bread wheat to assist with the future development of salt tolerant cultivars.

Effect of Rice GDP-L-Galactose Phosphorylase Constitutive Overexpression on Ascorbate Concentration, Stress Tolerance, and Iron Bioavailability in Rice.

Ascorbate (vitamin C) is an essential multifunctional molecule for both plants and mammals. In plants, ascorbate is the most abundant water-soluble antioxidant that supports stress tolerance. In humans, ascorbate is an essential micronutrient and promotes iron (Fe) absorption in the gut. Engineering crops with increased ascorbate levels have the potential to improve both crop stress tolerance and human health. Here, rice (Oryza sativa L.) plants were engineered to constitutively overexpress the rice GDP-L-galactose phosphorylase coding sequence (35S-OsGGP), which encodes the rate-limiting enzymatic step of the L-galactose pathway. Ascorbate concentrations were negligible in both null segregant (NS) and 35S-OsGGP brown rice (BR, unpolished grain), but significantly increased in 35S-OsGGP germinated brown rice (GBR) relative to NS. Foliar ascorbate concentrations were significantly increased in 35S-OsGGP plants in the vegetative growth phase relative to NS, but significantly reduced at the reproductive growth phase and were associated with reduced OsGGP transcript levels. The 35S-OsGGP plants did not display altered salt tolerance at the vegetative growth phase despite having elevated ascorbate concentrations. Ascorbate concentrations were positively correlated with ferritin concentrations in Caco-2 cells - an accurate predictor of Fe bioavailability in human digestion - exposed to in vitro digests of NS and 35S-OsGGP BR and GBR samples.

Tolerance of Combined Drought and Heat Stress Is Associated With Transpiration Maintenance and Water Soluble Carbohydrates in Wheat Grains.

Wheat (Triticum aestivum L.) production is increasingly challenged by simultaneous drought and heatwaves. We assessed the effect of both stresses combined on whole plant water use and carbohydrate partitioning in eight bread wheat genotypes that showed contrasting tolerance. Plant water use was monitored throughout growth, and water-soluble carbohydrates (WSC) and starch were measured following a 3-day heat treatment during drought. Final grain yield was increasingly associated with aboveground biomass and total water use with increasing stress intensity. Combined drought and heat stress immediately reduced daily water use in some genotypes and altered transpiration response to vapor pressure deficit during grain filling, compared to drought only. In grains, glucose and fructose concentrations measured 12 days after anthesis explained 43 and 40% of variation in final grain weight in the main spike, respectively. Starch concentrations in grains offset the reduction in WSC following drought or combined drought and heat stress in some genotypes, while in other genotypes both stresses altered the balance between WSC and starch concentrations. WSC were predominantly allocated to the spike in modern Australian varieties (28-50% of total WSC in the main stem), whereas the stem contained most WSC in older genotypes (67-87%). Drought and combined drought and heat stress increased WSC partitioning to the spike in older genotypes but not in the modern varieties. Ability to maintain transpiration, especially following combined drought and heat stress, appears essential for maintaining wheat productivity.

High-throughput, image-based phenotyping reveals nutrient-dependent growth facilitation in a grass-legume mixture.

This study used high throughput, image-based phenotyping (HTP) to distinguish growth patterns, detect facilitation and interpret variations to nutrient uptake in a model mixed-pasture system in response to factorial low and high nitrogen (N) and phosphorus (P) application. HTP has not previously been used to examine pasture species in mixture. We used red-green-blue (RGB) imaging to obtain smoothed projected shoot area (sPSA) to predict absolute growth (AG) up to 70 days after planting (sPSA, DAP 70), to identify variation in relative growth rates (RGR, DAP 35-70) and detect overyielding (an increase in yield in mixture compared with monoculture, indicating facilitation) in a grass-legume model pasture. Finally, using principal components analysis we interpreted between species changes to HTP-derived temporal growth dynamics and nutrient uptake in mixtures and monocultures. Overyielding was detected in all treatments and was driven by both grass and legume. Our data supported expectations of more rapid grass growth and augmented nutrient uptake in the presence of a legume. Legumes grew more slowly in mixture and where growth became more reliant on soil P. Relative growth rate in grass was strongly associated with shoot N concentration, whereas legume RGR was not strongly associated with shoot nutrients. High throughput, image-based phenotyping was a useful tool to quantify growth trait variation between contrasting species and to this end is highly useful in understanding nutrient-yield relationships in mixed pasture cultivations.

Smoothing and extraction of traits in the growth analysis of noninvasive phenotypic data.

BACKGROUND: Non-destructive high-throughput plant phenotyping is becoming increasingly used and various methods for growth analysis have been proposed. Traditional longitudinal or repeated measures analyses that model growth using statistical models are common. However, often the variation in the data is inappropriately modelled, in part because the required models are complicated and difficult to fit. We provide a novel, computationally efficient technique that is based on smoothing and extraction of traits (SET), which we compare with the alternative traditional longitudinal analysis methods. RESULTS: The SET-based and longitudinal analyses were applied to a tomato experiment to investigate the effects on plant growth of zinc (Zn) addition and growing plants in soil inoculated with arbuscular mycorrhizal fungi (AMF). Conclusions from the SET-based and longitudinal analyses are similar, although the former analysis results in more significant differences. They showed that added Zn had little effect on plants grown in inoculated soils, but that growth depended on the amount of added Zn for plants grown in uninoculated soils. The longitudinal analysis of the unsmoothed data fitted a mixed model that involved both fixed and random regression modelling with splines, as well as allowing for unequal variances and autocorrelation between time points. CONCLUSIONS: A SET-based analysis can be used in any situation in which a traditional longitudinal analysis might be applied, especially when there are many observed time points. Two reasons for deploying the SET-based method are (i) biologically relevant growth parameters are required that parsimoniously describe growth, usually focussing on a small number of intervals, and/or (ii) a computationally efficient method is required for which a valid analysis is easier to achieve, while still capturing the essential features of the exhibited growth dynamics. Also discussed are the statistical models that need to be considered for traditional longitudinal analyses and it is demonstrated that the oft-omitted unequal variances and autocorrelation may be required for a valid longitudinal analysis. With respect to the separate issue of the subjective choice of mathematical growth functions or splines to characterize growth, it is recommended that, for both SET-based and longitudinal analyses, an evidence-based procedure is adopted.