A systematic and quantitative approach to improve water use efficiency in agriculture

As the competition for the finite water resources on earth increases due to growth in population and affluence, agriculture is faced with intensifying pressure to improve the efficiency of water used for food production. The causes for the relatively low water use efficiency in agriculture are numerous and complex, including environmental, biological, engineering, management, social, and economic facets. The complexity of the problem, with its myriads of local variations, requires a comprehensive conceptual framework of the underlying physical and biological processes as the basis to analyze the existing situation and quantify the efficiencies, and to plan and execute improvements. This paper proposes such a framework, based on the simple fact that the overall efficiency of any process consisting of a chain of sequential step is the product of the efficiency (i.e., output/input ratio) of its individual component steps. In most cases of water use, a number of process chains, both branching and merging, are involved. Means to integrate the diverging and converging chains are developed and presented as equations. Upscaling from fields to regions and beyond are discussed. This chain of efficiencies approach is general and can be applied to any process composed of chains of sequential steps. Here the framework is used to analyze the systems of irrigated and dryland crop production, and animal production on rangeland. Range of plausible efficiencies of each step is presented as tables, with values separately for the poor and for the good situation of circumstances, management and technology. Causes of the differences in efficiency of each step, going from water delivery to soil water extraction, transpiration, photosynthesis, and conversion to crop biomass and yield, and to animal product are briefly discussed. Sample calculations are made to demonstrate how modest differences in the efficiencies of the component steps are manifested as large to huge differences in the overall efficiency. Based on an equation quantifying the impact of changes in efficiency of component steps on the overall efficiency, it is concluded that generally, it is more effective to made modest improvements in several or more steps than to concentrate efforts to improve one or two steps. Hence, improvement efforts should be systematic and not overly concentrated on one or two components. The potential use of the same equation as the point of departure to optimize the allocation of economic resource among the component steps to maximize the improvement in the overall water use efficiency is elaborated on. The chain of efficiencies framework provides the means to examine the current levels of efficiency along the pathways of agricultural water use, to analyze where inefficiencies lie by comparing with the range of known efficiency values in the tables presented, to assess the potential improvements that may be achieved in various parts and their impact on the overall efficiency, and to aid in the optimal allocation of resources for improvements.

---

Identifying and exploring significant genomic regions associated with soybean yield,seed fatty acids,protein and oil

Soybean [Glycine max (L.) Merrill] yield and seed fatty acids, protein, and oil content are important traits for which an improved understanding of significant genomic regions would be useful. To accomplish this, a soybean population consisting of 203 F5 derived recombinant inbred lines (RILs) was developed and genotyped with 11,633 polymorphic single nucleotide polymorphisms (SNPs). Each RIL was grown in a single plot at Knoxville, TN in 2010; followed by replicated, multi-location field trials in 2013 and 2014. The data from 2010, 2013, and 2014 were analyzed together in order to detect quantitative trait loci (QTL) for these traits, and 30 total QTLs were detected. Five QTLs are candidates for confirmed status and one QTL is a candidate for positional confirmation. Many of the genes with mutations in close proximity to the fatty acid QTLs are involved in biological processes for fatty acids and/or lipids and could be considered possible candidate genes. Similarly, genes with mutations in genomic regions near yield, protein, and oil QTLs were plentiful and may contribute to the variation observed in these traits. Except for yield and stearic acid, each trait displayed pleiotropic effects with other traits in this study. Notable are the pleiotropic effects for oleic and linolenic acid on chromosomes 9, 13, and 19. Overall, the findings from this research contribute new information to the genetic understanding of soybean yield and seed fatty acids, protein and oil content. This understanding will be useful in making trait improvements.     

Geospatial delineation of South Korea for adjusted barley cultivation under changing climate

Determining effective measures to alleviate the impact of climate change on crops under various regional environments is one of the most urgent issues facing agriculture. In this study, geographic regions of South Korea for future-adjusted barley cultivation were outlined and the impact of climate change on barley production in the next 100 years was evaluated under two greenhouse gas concentration trajectory scenarios: the representative concentration pathway (RCP) 4.5 and RCP 8.5. To achieve our intended study goals, a geospatial crop simulation modeling (GCSM) scheme was formulated using CERES-barley model of Decision Support System for Agricultural Technology (DSSAT) crop model package version 4.6 to simulate grid-based geospatial crop yields. Two experiments were carried out at an open field to obtain model coefficients for the nation and at temperature gradient field chambers to evaluate the performance of the CERES-barley model under elevated temperature conditions. Suitable cultivation regions for three different types of barley (naked, hooded, and malting) under changing climate were projected to expand to the northern regions under both RCP 8.5 and RCP 4.5. However, they were projected to expand more rapidly under RCP 8.5 than those under RCP 4.5. Projected yields of four barley varieties were increased with a slow phase as year progressed under RCP 4.5 scenario. However, they were rapidly increased under RCP 8.5 scenario. It appears that geospatial variation in barley yield under changing climate can be effectively outlined. Therefore, GCSM system might be useful for determining impacts of climate change on geospatial variations of crops, potentially providing means to impede food insecurity.     

Identification of favorable alleles in the <Emphasis Type="Italic">non</Emphasis>-<Emphasis Type="Italic">yellow coloring 1</Emphasis> gene by association mapping in maize

Association mapping was conducted to explore favorable alleles of the chlorophyll-related non-yellow coloring 1 (NYC1) gene under light and dark using an association panel of 146 maize inbred lines. A total of 14 polymorphic sites were identified to be significantly associated with at least one of the chlorophyll-related traits at the seedling stage. Four single nucleotide polymorphisms (SNPs) (S320, S2951, S3901, and S3355) from the NYC1 gene were respectively strongly associated with chlorophyll b (chlb), the ratio of chlorophyll a to chlorophyll b (chl_ratio), chlorophyll a degradation (chla_deg), and total chlorophyll degradation (total_chl_deg). SNPs S320 (C/A) in exon 1, and S2951 (A/G) in intron 8 was related to chlb, with 6.01 and 8.89% of phenotypic variation under light treatment, respectively. Under dark treatment, SNP S3901 (C/T), located in 3′ untranslated region (3′UTR), was associated with chl_ratio, explaining 7.01% of the observed phenotypic variation, whereas SNP S3355 (C/G) in intron 9 explained 6.48 and 5.18% of phenotypic variations in chla_deg and total_chl_deg, respectively. Taken together, these results indicated that the NYC1 gene plays an important role in chlorophyll content and other related traits, and different sites act on chlorophyll metabolism under different light intensities in maize seedlings. Furthermore, these findings improve our understanding of the genetic basis of chlorophyll metabolism under different light conditions.     

Transformation of <Emphasis Type="Italic">Campanula</Emphasis> by wild type <Emphasis Type="Italic">Agrobacterium rhizogenes</Emphasis>

Compact growth is an important quality criterion in horticulture. Many Campanula species and cultivars exhibit elongated growth which is suppressed by chemical retardation and cultural practice during production to accommodate to the consumer’s desire. The production of compact plants via transformation with wild type Agrobacterium rhizogenes is an approach with great potential to produce plants that are non-GMO. Efficient transformation and regeneration procedures vary widely among both plant genera and species. Here we present a transformation protocol for Campanula. Hairy roots were produced on 26–90% of the petioles that were used for transformation of C. portenschlagiana (Cp), a C. takesimana × C. punctata hybrid (Chybr) and C. glomerata (Cg). Isolated hairy roots grew autonomously and vigorously without added hormones. The Cg hairy roots produced chlorophyll and generated plantlets in response to treatments with cytokinin (42 µM 2iP) and auxin (0.67 µM NAA). In contrast, regeneration attempts of transformed Cp and Chybr roots lead neither to the production of chlorophyll nor to the regeneration of shoots. Agropine A. rhizogenes strains integrate split T-DNA in T_L- and T_R-DNA fragments into the plant genome. In this study, regenerated plants of Cg did not contain T_R-DNA, indicating that a selective pressure against this T-DNA fragment may exist in Campanula.     

Molecular markers for improving control of soil-borne pathogen <Emphasis Type="Italic">Fusarium oxysporum</Emphasis> in sugar beet

Fusarium spp. cause severe damage in many agricultural crops, including sugar beet, with Fusarium oxysporum historically being considered as the most damaging of all species. Sugar beet needs to be protected from this class of soil-borne pathogens in order to ensure an optimal sugar yield in the field. Genetic control of the disease is crucial in managing these pathogens. Identification of single nucleotide polymorphism (SNP) markers linked to resistance can be a powerful tool for the introgression of valuable genes needed to develop Fusarium-resistant varieties. A candidate gene approach was carried out to identify SNP markers linked to putative Fusarium resistance sources in sugar beet. Five resistant analogue genes (RGAs) were screened by means of high resolution melting (HRM) analysis in a set of sugar beet lines, considered as resistant and susceptible to Fusarium oxysporum. HRM polymorphisms were observed in 80% of amplicons. Two HRM polymorphisms were significantly associated with Fusarium resistance (P < 0.05). The amplicons that showed association were sequenced and two SNPs were identified. The association was further validated on 96 susceptible and 96 resistant plants using competitive allele-specific PCR (KASPar) technology. The selected SNPs could be used for marker-assisted breeding of Fusarium resistance in sugar beet.     

Identification of quantitative trait locus and prediction of candidate genes for grain mineral concentration in maize across multiple environments

Trace metal elements are essential in daily diets for human health and normal growth. Maize is staple food for people in many countries. However, maize has low mineral concentration which makes it difficult to meet human requirements for micronutrients. The objective of this study was to identify quantitative trait locus (QTL) and predict candidate genes associated with mineral concentration in maize grain. Here, a recombinant inbred line population was used to test phenotype of zinc (Zn), iron (Fe), copper (Cu) and manganese (Mn) concentrations in six environments and then a QTL analysis was conducted using single environment analysis along with multiple environment trial (MET) analysis. These two strategies detected a total of 64 and 67 QTLs for target traits, respectively. Single environment analysis revealed 13 QTL bins distributed on seven chromosomes. We found that five candidate genes associated with mineral concentration were located in the same intervals identified by Comparative mapping of meta-QTLs in our previous study. The genetic and phenotypic correlation coefficients were depended on the nutrient traits and they were significant between Fe and Zn, Fe and Cu, Fe and Mn in all environments. The results of this study illustrated the genetic correlation between maize grain mineral concentrations, and identified some promising genomic regions and candidate genes for further studies on the biofortification of mineral concentration in maize grain.     

Assessing freeze-tolerance in St. Augustinegrass: temperature response and evaluation methods

Winter hardiness is a major-limiting factor for St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] grown in the transitional climatic region of the United States. Lab-based freeze tests that mimic the range of field winter survivability in St. Augustinegrass can contribute to the selection of cold hardy genotypes. This study used a whole container method, four freezing temperatures, and two data collection systems to evaluate the freezing response of nine St. Augustinegrass genotypes ranging in their winter hardiness. Results indicated ?3 and ?4 °C with average regrowth ratings of 33.6 and 17.8% respectively, were more suitable temperatures for evaluating freeze survival in St. Augustinegrass than ?5 and ?6 °C with average regrowth ratings of 0.4 and 0%, respectively. Visual ratings of surviving green tissue and regrowth were generally well correlated when evaluated over a six week period post-freeze with Pearson correlation coefficients ranging of 0.17–0.62  for ?3 °C freeze tests and 0.79–0.93 for ?4 °C freeze tests. Additionally, measurement of percent green cover using digital imaging techniques commonly utilized in turfgrass field studies were significantly correlated (0.66) with visual ratings averaged across weekly post-freeze evaluation measurements for both ?3 and ?4 °C freezing temperatures. These results provide evidence that digital imaging analyses are useful in estimating surviving green tissue and regrowth in lab-based freeze tests. This study provides additional information regarding freezing temperatures, genotype responses, and data collection methods in St. Augustinegrass, which should aid breeders in the improvement of freeze tolerance in the species.