Wheat straw is a potential cellulosic feedstock for bioethanol. This study was conducted to evaluate straw yield potential and its relationship with grain yield for wheat ( spp.) grown in the United States. The specific objective was to determine if differences in straw yield and harvest index (HI) exist between and within regions and/or wheat classes. Using on-going variety performance trials in eight states, a total of 255 varietal trial entriess from five classes of wheat were surveyed for above-ground biomass. Averaged over all wheat classes and regions the HI was 0.45. Soft red winter wheat in Kentucky had, on average, the highest HI and lowest straw yield among regions and wheat classes. Soft white winter wheat under irrigation in the Pacific Northwest produced the highest straw yield. Hard red winter wheat in the southern plain states of Texas and Oklahoma had, on average, the lowest HI. Differences in the amount of precipitation and cultivars were the major contributors to the variation detected within wheat classes. The amount of wheat straw available as cellulosic feedstock in a state or wheat class can be estimated using the grain yield estimates provided by the National Agricultural Statistics Service and the class specific HI.
Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.
The expansion of the world's population requires the development of high production agriculture. For this purpose, it is essential to identify target points conditioning crop responsiveness to predicted [CO 2 ]. The aim of this study was to determine the relevance of ear sink strength in leaf protein and metabolomic profiles and its implications in photosynthetic activity and yield of durum wheat plants exposed to elevated [CO 2 ]. For this purpose, a genotype with high harvest index (HI) (Triticum durum var. Sula) and another with low HI (Triticum durum var. Blanqueta) were exposed to elevated [CO 2 ] (700 μmol mol -1 versus 400 μmol mol -1 CO 2 ) in CO 2 greenhouses. The obtained data highlighted that elevated [CO 2 ] only increased plant growth in the genotype with the largest HI; Sula. Gas exchange analyses revealed that although exposure to 700 μmol mol -1 depleted Rubisco content, Sula was capable of increasing the light-saturated rate of CO 2 assimilation (A sat ) whereas, in Blanqueta, the carbohydrate imbalance induced the down-regulation of A sat . The specific depletion of Rubisco in both genotypes under elevated [CO 2 ], together with the enhancement of other proteins in the Calvin cycle, revealed that there was a redistribution of N from Rubisco towards RuBP regeneration. Moreover, the down-regulation of N, NO 3 - , amino acid, and organic acid content, together with the depletion of proteins involved in amino acid synthesis that was detected in Blanqueta grown at 700 μmol mol -1 CO 2 , revealed that inhibition of N assimilation was involved in the carbohydrate imbalance and consequently with the down-regulation of photosynthesis and growth in these plants.
Field-based next generation phenotyping has become of great interest to plant breeders and agricultural researchers in recent years, particularly for circumventing destructive or impractical phenotyping methods commonly used for certain traits. The non-destructive estimation of one such trait, above ground biomass (AGB), has been investigated repeatedly using 2D imagery, though little research has been conducted on 3D methods. The aims of the current study were to (i) investigate the use of readily-available consumer level digital cameras and software to estimate AGB, canopy height (CH) and harvest index (HI) of wheat plots, (ii) investigate the suitability of this data as a replacement for destructive sampling methods within a wheat breeding programme, and (iii) identify the point cloud density required for accurate estimation of AGB. To achieve this, a small plot trial of a single wheat cultivar was conducted in an irrigated nursery, at Roseworthy, South Australia. At physiological maturity plots were measured for CH and whole plots were harvested to attain AGB and threshed to measure grain yield and calculate HI. Prior to harvesting each plot was imaged using a digital camera, with these images being processed into 3D point clouds, which were subsequently used to estimate plot volume and CH. Strong correlations were observed between actual measurements of AGB, CH and HI to those estimated from point clouds. Images were processed in subset batches to determine an optimal number of images for processing. Stronger correlations between AGB and plot volume were observed when more images were processed, though as few as 48 images provided sufficiently accurate estimates of AGB. These methods were shown to be effective at estimating AGB, CH and HI and could be adopted by small scale research programmes. This study shows that a higher-throughput adaptation of this photogrammetry method could be used in phenotype intensive research such as plant breeding programmes.
Rice is a staple food for nearly half of the world's population, but rice paddies constitute a major source of anthropogenic CH 4 emissions. Root exudates from growing rice plants are an important substrate for methane‐producing microorganisms. Therefore, breeding efforts optimizing rice plant photosynthate allocation to grains, i.e., increasing harvest index (HI), are widely expected to reduce CH 4 emissions with higher yield. Here we show, by combining a series of experiments, meta‐analyses and an expert survey, that the potential of CH 4 mitigation from rice paddies through HI improvement is in fact small. Whereas HI improvement reduced CH 4 emissions under continuously flooded (CF) irrigation, it did not affect CH 4 emissions in systems with intermittent irrigation (II). We estimate that future plant breeding efforts aimed at HI improvement to the theoretical maximum value will reduce CH 4 emissions in CF systems by 4.4%. However, CF systems currently make up only a small fraction of the total rice growing area (i.e., 27% of the Chinese rice paddy area). Thus, to achieve substantial CH 4 mitigation from rice agriculture, alternative plant breeding strategies may be needed, along with alternative management. Breeding efforts optimizing photosynthate allocation to grains, i.e., increasing harvest index (HI), are widely expected to reduce CH 4 emissions from rice cultivation. Here we show, by combining a series of experiments, meta‐analyses, and an expert assessment, that the potential of CH 4 mitigation from rice paddies through HI improvement is actually small. We estimate that future HI improvement will reduce CH 4 emissions in continuously flooded systems (CF) by 4.4% at most. Furthermore, HI improvement did not affect CH 4 emissions in systems with intermittent irrigation (II); these systems make up a large part of the China's rice growing area and are becoming increasingly popular.
Spikelet fertility (seed-set) is an important component of yield that is sensitive to high temperature. The objectives of this research were (a) to quantify the effects of high temperature on spikelet fertility and harvest index of rice; (b) to determine if there were species, ecotype, and/or cultivar differences in response to high temperature; and (c) to understand the reasons for lower and/or differential spikelet fertility and harvest index of rice cultivars at high temperatures. Fourteen rice cultivars of different species ( and ), ecotypes ( and ) and origin (temperate and tropical) were exposed to ambient and high temperature (ambient + 5 °C) at Gainesville, Florida. High temperature significantly decreased spikelet fertility across all cultivars, but effects varied among cultivars. Based on decreases in spikelet fertility at high temperature, cultivar N-22 was most tolerant, while cultivars L-204, M-202, Labelle, Italica Livorna, WAB-12, CG-14 and CG-17 were highly susceptible and cultivars M-103, S-102, Koshihikari, IR-8 and IR-72 were moderately susceptible to high temperature. There were no clear species or ecotype differences, as some cultivars in each species or within ecotypes of tropical and temperature origin were equally susceptible to high temperature (for example M-202 temperate , Labelle tropical , CG-14 , and WAB-12 interspecific). Decreased spikelet fertility and cultivar difference at high temperature were due mainly to decreased pollen production and pollen reception (pollen numbers on stigma). Lower spikelet fertility at elevated temperature resulted in fewer filled grains, lower grain weight per panicle, and decreased harvest index. There is a potential for genetic improvement for heat tolerance, thus it is important to screen and identify heat-tolerant cultivars. Spikelet fertility at high temperature can be used as a screening tool for heat tolerance during the reproductive phase.
Improving biomass is an important goal for future genetic gains in yield potential in wheat, but it will also be crucial to identify physiological traits to maximize harvest index (HI, proportion of aboveground biomass in grain). Increased grain partitioning will require increased dry-matter (DM) partitioning to the spikes at anthesis as well as enhanced fruiting efficiency (FE, grains per g spike dry matter at anthesis or chaff dry matter at harvest), whilst optimizing the partitioning amongst the non-grain components to maintain post-anthesis photosynthetic capacity and soluble carbohydrate translocation. The objectives of this study were to: i) quantify genetic variation in DM partitioning among plant organs at anthesis (GS65) + 7 days and associations with spike growth and FE and ii) identify optimized partitioning traits associated with enhanced HI and grain yield, in CIMMYT elite spring wheat backgrounds. Two field experiments were conducted in 2011-12 and 2012-13 testing 26 CIMMYT spring wheat cultivars in NW Mexico in irrigated conditions in which DM partitioning was assessed in plant organs at anthesis + 7 days, and within-spike (glume, palea, lemma, rachis and awn) partitioning was assessed at harvest for a subset of 17 cultivars. Grain yield, yield components, HI and FE were assessed at harvest. Our results identified new traits for HI (decreased DM partitioning to stem internodes 2 (top down, peduncle -1) and 3, and decreased rachis DM partitioning and rachis specific weight (rachis DM per rachis unit length) and increased lemma DM partitioning), potentially allowing breeders to maximize the exploitation of enhanced carbon assimilation for grain biomass. Further work will focus on understanding the role of soluble carbohydrate re-translocation in these relationships and establishing high-throughput and cost-effective phenotyping methods for these traits for deployment in breeding.
Simulating yield response to different irrigation scenarios is important for agricultural production, especially in the arid region where agriculture depends heavily on irrigation. To better predict yield under different irrigation scenarios, the variation of normalized water productivity (WP ) over the whole growing period of maize for seed production and the effect of different irrigation treatments on harvest index (HI) were investigated using field experiments from 2012 to 2015 in an arid region of northwest China. Two new non-linear dynamic WP (WP and WP ) models derived from the Logistic and Sigmoid equations, and four new HI (HI , HI , HI and HI ) models developed on the basis of water deficit multiplicative or additive models at different growth stages were compared with the measurements and the WP (WP ) and HI sub-model (HI ) in the original AquaCrop model (Version 4.0). In addition, the WP and HI models in the original AquaCrop model were replaced by the optimal WP and HI models to build the AquaCrop-KR model. Then the yield simulated by the AquaCrop-KR model was compared with the measured yield and the yield simulated by the original AquaCrop model. The results show that both WP and WP models improved the simulation of final biomass, especially for the WP model. The tested HI sub-models, namely HI , HI , HI and HI models had good performance to simulate HI under different irrigation scenarios, and the HI model was the best among all tested sub-models. When both WP and HI sub-models were embedded into Aquacrop, the performance of the AquaCrop model was improved significantly to simulate yield, especially under severe water stress condition, with R increased from 0.496 to 0.653, NRMSE decreased from 26.2% to 16.1% and EF increased from 0.055 to 0.642.
The aim of this study was to verify if the harvest index (HI) of common bean is higher in modern lines, to verify if its estimate varies with the cycle of the plant and environmental conditions, and to obtain information concerning its genetic control (through diallel crossing). For this purpose, six lines were crossed in a diallel. Evaluations were carried out in three crop seasons/generations - F-2, F-3, and F-4. A receptacle was used to collect leaves, pods, and other plant parts that fell before harvest. Diallel analysis was performed using Griffing's method II. It found that the HI was higher in modern lines and was not affected by the cycle; the estimated HI heterosis was negative, indicating the occurrence of dominance in order to reduce trait expression.
Background: Harvest index (HI), the ratio of grain yield to total biomass, is considered as a measure of biological success in partitioning assimilated photosynthate to the harvestable product. While crop production can be dramatically improved by increasing HI, the underlying molecular genetic mechanism of HI in rapeseed remains to be shown. Results: In this study, we examined the genetic architecture of HI using 35,791 high-throughput single nucleotide polymorphisms (SNPs) genotyped by the Illumina BrassicaSNP60 Bead Chip in an association panel with 155 accessions. Five traits including plant height (PH), branch number (BN), biomass yield per plant (BY), harvest index (HI) and seed yield per plant (SY), were phenotyped in four environments. HI was found to be strongly positively correlated with SY, but negatively or not strongly correlated with PH. Model comparisons revealed that the A-D test (ADGWAS model) could perfectly balance false positives and statistical power for HI and associated traits. A total of nine SNPs on the C genome were identified to be significantly associated with HI, and five of them were identified to be simultaneously associated with HI and SY. These nine SNPs explained 3.42 % of the phenotypic variance in HI. Conclusions: Our results showed that HI is a complex polygenic phenomenon that is strongly influenced by both environmental and genotype factors. The implications of these results are that HI can be increased by decreasing PH or reducing inefficient transport from pods to seeds in rapeseed. The results from this association mapping study can contribute to a better understanding of natural variations of HI, and facilitate marker-based breeding for HI.