Estimation of leaf water potential by thermal imagery and spatial analysis.

Canopy temperature has long been recognized as an indicator of plant water status and as a potential tool for irrigation scheduling. In the present study, the potential of using thermal images for an in-field estimation of the water status of cotton under a range of irrigation regimes was investigated. Thermal images were taken with a radiometric infrared video camera. Specific leaves that appeared in the camera field of view were sampled, their LWP was measured and their temperature was calculated from the images. Regression models were built in order to predict LWP according to the crop canopy temperature and to the empirical formulation of the crop water stress index (CWSI). Statistical analysis revealed that the relationship between CWSI and LWP was more stable and had slightly higher correlation coefficients than that between canopy temperature and LWP. The regression models of LWP against CWSI and against leaf temperatures were used to create LWP maps. The classified LWP maps showed that there was spatial variability in each treatment, some of which may be attributed to the difference between sunlit and shaded leaves. The distribution of LWP in the maps showed that irrigation treatments were better distinguished from each other when the maps were calculated from CWSI than from leaf temperature alone. Furthermore, the inclusion of the spatial pattern in the classification enhanced the differences between the treatments and was better matched to irrigation amounts. Optimal determination of the water status from thermal images should be based on an overall view of the physical status as well as on the analysis of the spatial structure. Future study will involve investigating the robustness of the models and the potential of using water status maps, derived from aerial thermal images, for irrigation scheduling and variable management in commercial fields.

QTL analysis of genotype x environment interactions affecting cotton fiber quality.

Cotton is unusual among major crops in that large acreages are grown under both irrigated and rainfed conditions, making genotype x environment interactions of even greater importance than usual in designing crop-improvement strategies. We describe the impact of well-watered versus water-limited growth conditions on the genetic control of fiber quality, a complex suite of traits that collectively determine the utility of cotton. Fiber length, length uniformity, elongation, strength, fineness, and color (yellowness) were influenced by 6, 7, 9, 21, 25 and 11 QTLs (respectively) that could be detected in one or more treatments. The genetic control of cotton fiber quality was markedly affected both by general differences between growing seasons ("years") and by specific differences in water management regimes. Seventeen QTLs were detected only in the water-limited treatment while only two were specific to the well-watered treatment, suggesting that improvement of fiber quality under water stress may be even more complicated than improvement of this already complex trait under well-watered conditions. In crops such as cotton with widespread use of both irrigated and rainfed production systems, the need to manipulate larger numbers of genes to confer adequate quality under both sets of conditions will reduce the expected rate of genetic gain. These difficulties may be partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers, including those identified herein.

Genomic dissection of genotype x environment interactions conferring adaptation of cotton to arid conditions.

The interaction of genotype with environment is of primary importance in many aspects of genomic research and is a special priority in the study of major crops grown in a wide range of environments. Water deficit, the major factor limiting plant growth and crop productivity worldwide, is expected to increase with the spread of arid lands. In genetically equivalent cotton populations grown under well-watered and water-limited conditions (the latter is responsible for yield reduction of approximately 50% relative to well-watered conditions), productivity and quality were shown to be partly accounted for by different quantitative trait loci (QTLs), indicating that adaptation to both arid and favorable conditions can be combined in the same genotype. QTL mapping was also used to test the association between productivity and quality under water deficit with a suite of traits often found to differ between genotypes adapted to arid versus well-watered conditions. In this study, only reduced plant osmotic potential was clearly implicated in improved cotton productivity under arid conditions. Genomic tools and approaches may expedite breeding of genotypes that respond favorably to specific environments, help test roles of additional physiological factors, and guide the isolation of genes that protect crop performance under arid conditions toward improved adaptation of crops to arid cultivation.

Lycopersicon esculentum lines containing small overlapping introgressions from L. pennellii.

The objective of this project was to introgress small overlapping chromosome segments which cover the genome of L. pennellii into Lycopersicon esculentum lines. The interspecific hybrid was backcrossed to L. esculentum, and a map of 981 cM, based on 146 molecular markers covering the entire genome, was produced. A similar backcross 1 population was selfed for six generations, under strong selection for cultivated tomato phenotypes, to produce 120 introgression lines. The introgression lines were assayed for the above-mentioned molecular markers, and 21 lines covering 936 cM of L. pennellii, with an average introgression of 86 cM, were selected to provide a resource for the mapping of new DNA clones. The rest of the lines have shorter introgressions consisting of specific regions with an average size of 38 cM. The proportion of the L. pennellii genome in the introgression lines was lower than expected (252 cM) because of strong selection against the wild-parent phenotype. The mean introgression rate for ends of linkage groups in the 120 lines was 3 times higher than for other regions of the genome. The introgression lines can assist in RFLP-based gene cloning by allowing the rapid selection of DNA markers that map to specific chromosome segments. The introgression lines also provide a base population for the mapping and breeding for quantitative traits such as salt and drought tolerance that characterize the wild species L. pennellii.

Breeding tomatoes for salt tolerance: inheritance of salt tolerance and related traits in interspecific populations.

Interspecific segregating populations derived from a cross between tomato (Lycopersicon esculentum) cv 'M82-1 -8' (M82) and the wild species L. pennellii accession LA-716 (Lpen716) were used to study the genetic basis of salt tolerance and its implications for breeding. BC1 (M82 x (M82 x Lpen716)) and BC1 S1 (progenies of selfed BC1 plants) populations were grown under arid field conditions and irrigated with water having electrical conductivities of 1.5 (control), 10 and 20 dSm(-1). The evaluation of salt tolerance was based on total fruit yield (TY), total dry matter (TD) and TD under salinity relative to the control (RD). Sodium, potassium and chloride concentrations were measured in the leaves and stems. The methods for estimating heritability were adapted to BC1 plants and BC1S1 families. TY, TD and RD had heritability estimates of 0.3-0.45, indicating that salt tolerance can be improved by selection. Genetic correlations between traits indicated that high yield may be combined with salt tolerance and that ion contents are not likely to provide an efficient selection criteria for salt tolerance. Genetic correlations between performances under various salinity levels suggested that similar mechanisms affect the responses to salinity treatments of 10 and 20 dSm(-1). Responses to "paper" selection confirmed that salt tolerance of the tomato may be improved by selection, and that this selection should be based on dry matter and yield parameters under salinity.