Coupling DSSAT and HYDRUS-1D for simulations of soil water dynamics in the soil-plant-atmosphere system

Abstract Accurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A “tipping bucket” water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of the d index for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively high d index values for both models (0.94–0.99)

Genetic Variability Heritability and Expected Genetic Advance in Peanut (Arachis hypogaea L.) Genotypes at Pawe, Northwestern Ethiopia

Peanut (Arachis hypogaea L.) is one of the most significant oil seed crop of the world and the second most important source of vegetable oil in Ethiopia. But productivity is insufficient as compared to the world average productivity because of low genetic variability, biotic and abiotic stress, and poor seed system. This experiment was designed to evaluate genetic variability for 64 groundnut genotypes using 8x8 simple lattice design at Pawe northwestern Ethiopia, in 2021/22.The objectives of the study were to estimate the genetic variability among the genotypes. Analysis of variance revealed that, there was highly significant difference among the sixty four genotypes for all traits studied. Kernel yield showed the highest GCV and PCV values, while the lowest was seen in the shelling %.Harvest index (41.13), number of branches per plant (39.79), number of pods per plant (42.96), hundred seed weight (42.70), kernel yield (41.97), biomass yield (41.78), and pod yield (42.96) all showed moderate heritability and high genetic progress as a percentage of the mean (35.55). The results of this study showed that the genotypes had enough variation, therefore there was a good chance of identifying genotypes for future breeding programs that would be promising.DOI: 10.7176/JNSR/14-7-04 Publication date:May 31st 2023

Genetic analysis and improvement of groundnut (Arachis hypgaea L.) for drought tolerance and seed yield in Malawi.

Master of Science in Plant Breeding. University of KwaZulu-Natal, Pietermaritzburg, 2018.Groundnut (Arachis hypogaea L,) is one of the major sources of food and income for smallholder farmers in Malawi. It is a valuable food security crop that supplies fats and proteins to the predominantly maize–based Malawian diet. Although, groundnut production is a profitable venture for smallholder farmers in Malawi, its productivity is low averaging 250 – 800 kg/ha as compared to a yield of about 4.0 t/ha obtained at research stations. The decline in productivity of groundnuts is due to several abiotic and biotic constraints that smallholder farmers encounter, among them drought due to inadequate and highly variable rainfall in the country. Information on response of different genotypes to drought stress and the explanation of these variabilities is an important requirement in breeding for drought tolerance improvement in groundnut. The main objectives of the study were: (i) to determine the effect of drought stress on the growth performance of groundnut genotypes with respect to morpho-physiological traits,(ii) to identify the relevant traits related to drought tolerance and their relationship to seed yield under drought stress conditions, (iii) to estimate the relative importance of additive and non-additive gene action in controlling the inheritance of drought tolerance traits under moisture stressed conditions and (iv) to investigate the genetic variation existing among genotypes in relation to morpho-physiological traits related to drought tolerance. Twenty-five genotypes from the International Crops Research Institute for Semi-Arid Tropics (ICRISAT) Malawi were evaluated during 2016/17 under rainfed field condition at the drought-testing site of Ngabu Agricultural Research Station. The results indicated high genotypic coefficient of variation (GCV) coupled with high genetic advance (GA), genetic advance as percent of mean (GAM) and heritability estimates for days to maturity (DM), seed yield (SY), relative water content (RWC), biomass (BM), number of filled pods (FP) and pod yield (PY). Seed yield was highly significant and positively correlated with shelling percentage (SHP), hundred seed weight (HSW), SPAD chlorophyll meter reading (SCMR), days to maturity (DM), biomass (BM), relative water content (RWC) and harvest index (HI). Furthermore, path analysis showed that harvest index, biomass, pod yield, shelling percentage, SPAD chlorophyll meter reading, relative water content and days to maturity had the highest direct and indirect effects on seed yield. General combining ability effects were significant for almost all studied traits indicating the importance of additive gene action. Specific combining ability effects were also significant for days to maturity, seed yield, biomass, harvest index, number of field pod and pod yield indicating importance of non-additive gene action controlling the inheritance of these traits. This suggests that both additive and non-additive gene action were important in controlling the majority of the traits. However, additive gene action was more predominant for all traits studied as it was evidenced by its significant (P0.5) ranging from 0.78 to 0.96 for all measured traits. Among male parents, ICGV-SM 02724 and ICGV-SM 94139 were identified as good combiners, whereas among females, CG 7 and ICGV-SM 01721 were good combiners. These parents have outstanding breeding value as proven by their high and significant GCA effects. The crosses Pendo x Akwa, ICGV-SM 99555 x ICGV-SM 02724, ICGV – SM 99551 x Baka and ICGV-SM 01721 x ICGV-SM 94139 had significant SCA effects for seed yield, number of filled pod, harvest index and pod yield. The cross, Pendo x ICGV-SM 02724 was identified as potentially useful for developing early maturing varieties. These crosses could be used for further selection in breeding programmes for developing drought tolerant cultivars. Genotypes also showed different degrees of tolerance where seven genotypes with high yield, favourable adaptive traits and useful for breeding were selected. The principal component analysis under moisture stressed condition also showed that specific leaf area, days to maturity, biomass, number of filled pod, hundred seed weight and pod yield had more influence during selection. Based on the current results, breeding for drought tolerance for the material studied will be possible by focussing on relative water content, shelling percentage, number of filled pod, SPAD chlorophyll meter reading, pod yield and hundred seed weight as selection criteria, accompanied with extensive evaluation of the material under multi-located trials

Peanut agronomy experiments with five varieties in the Bundaberg and Kingaroy regions in the 2021-22 season

This report summarises the results of the peanut agronomy experiments conducted at Bundaberg and Kingaroy during the 2021-22 season as part of the above project. The experiments were laid out in a split-plot design with three replications at each location. Five peanut varieties, including Holt, Alloway, Kairi, Wheeler and P85-p112-151 (P85), were assigned to main plots, and four plant populations, 6, 12, 18, and 24 plants per m2, were assigned to subplots. All varieties were runner types except Wheeler, which represented a 'Virginia' type. Planting was done by the precision planting 20/20® and vSet® electronic seed metering system. The experiments were irrigated using irrigation scheduling software Aquaman via the web-based 'Yield Prophet'

Genetic variability, path coefficient and marker-trait association analysis for resistance to rosette disease in groundnut.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.Several abiotic, biotic and socio-economic aspects constrain the production of groundnut (Arachis hypogea L.). Groundnut rosette disease (GRD) which can cause yield losses of up to 100% in susceptible cultivars, is among the most important biotic stresses. The use of resistant cultivars is the most viable method to control the disease, therefore, breeding for high yielding and GRD resistant cultivars is needed and should be a priority. The present study was conducted to: (i) determine genetic variability for GRD response and yield traits in selected groundnut accessions under natural infestation, (ii) assess the relationship between seed yield and its related traits, and analyse agro-morphological diversity in selected groundnut accessions under natural GRD infestation and (iii) evaluate groundnut recombinant inbred lines for resistance to GRD and perform SNP marker-trait association analysis. Twentyfive groundnut accessions and three controls were evaluated under natural GRD infestation to assess genetic variability for GRD response and yield related traits. Seed yield, number of pods per plant, plant height, GRD incidence and number of secondary branches showed high phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV), while moderate variation (PCV and GCV) was observed for days to flowering and pod width. A combination of high heritability and genetic advance was recorded for number of secondary branches, plant height, seed yield and GRD incidence, indicating that phenotypic selection based on the mean would be successful in improving these traits. Phenotypic correlations and sequential path analysis indicated that high seed yield was directly associated with taller genotypes, higher number of pods per plant and hundred seed weight, which were a result of higher pod width and lower GRD incidence. Based on morphological traits, the evaluated accessions were grouped into four clusters. Days to flowering and maturity, number of branches, plant height, number of pods per plant, pod width and length, seed yield and GRD incidence, largely influenced this variation. Principal component analysis (PCA) biplot was effective in showing the genetic distance among the accessions with results consistent to those of the cluster analysis. Moreover, Shannon-Weaver diversity indices (0.949-0.9996) for qualitative traits also indicated the existence of high diversity among the accessions. A total of 25 groundnut genotypes, which comprised 21 RILs derived from a bi-parental cross, both parents, and two susceptible controls (CG7 and JL24) were evaluated and used to perform SNP marker-trait association analysis for resistance to GRD. There were significant differences among the lines in all recorded traits, indicating the existence of genetic variability and possibility of effective selection. Interaction of genotype and environment was significant for disease incidence and the glasshouse environment had higher disease pressure, providing the best discrimination among the tested genotypes. ICGV-SM 15605, ICGV-SM 15621, ICGV-SM 15618, ICGV-SM 15604 and ICGV-SM 15615 were among the resistant and high yielding RILs. Twenty-two highly significant marker-trait associations were identified, which will add to previously reported genomic regions influencing GRD and the aphid vector resistance. Overall, the study showed that taller genotypes, higher number of pods per plant and hundred seed weight can be used to improve seed yield in groundnut, particularly under GRD infestation. The genetic diversity among the accessions provides an opportunity for parent selection that can be used for breeding high yielding and GRD resistant cultivars. In addition, the SNP markers will be useful in classifying groundnut germplasm based on the GRD response and for their use in marker-assisted selection, once validated

Marker-assisted introgression of a QTL region to improve rust resistance in three elite and popular varieties of peanut (Arachis hypogaea L.)

Leaf rust, caused by Puccinia arachidis Speg, is one of the major devastating diseases in peanut (Arachis hypogaea L.). One QTL region on linkage group AhXV explaining upto 82.62 % phenotypic variation for rust resistance was validated and introgressed from cultivar ‘GPBD 4’ into three rust susceptible varieties (‘ICGV 91114’, ‘JL 24’ and ‘TAG 24’) through marker-assisted backcrossing (MABC). The MABC approach employed a total of four markers including one dominant (IPAHM103) and three co-dominant (GM2079, GM1536, GM2301) markers present in the QTL region. After 2–3 backcrosses and selfing, 200 introgression lines (ILs) were developed from all the three crosses. Field evaluation identified 81 ILs with improved rust resistance. Those ILs had significantly increased pod yields (56–96 %) in infested environments compared to the susceptible parents. Screening of selected 43 promising ILs with 13 markers present on linkage group AhXV showed introgression of the target QTL region from the resistant parent in 11 ILs. Multi-location field evaluation of these ILs should lead to the release of improved varieties. The linked markers may be used in improving rust resistance in peanut breeding programmes

Establishing Defoliation Thresholds in Peanut (Arachis Hypogaea (L.)) in Mississippi

Foliage feeding insects like fall armyworm (FAW) [Spodoptera frugiperda (J. E. Smith)], granulate cutworm (GCW) [Feltia subterranean (F.)], velvetbean caterpillar (VBC) [Anticarsia gemmatalis (Hübner)] and corn earworm (CEW) [Helicoverpa zea (Boddie)] in peanut (Arachis hypogaea (L.)) and their effects on canopy defoliation and the resultant yield loss is outdated and essentially non-existent in Mississippi. With the expansion of peanuts throughout the state since 2012, growers struggle to manage foliageeeding pests in peanut. The lack of current information regarding insect pressure and economic injury levels is troublesome; especially with newer, high yielding, disease resistant cultivars. Research was required to understand how peanuts respond to complete canopy removal at different times during the growing season. Consequently, we evaluated the severity of canopy defoliation causing significant levels of yield loss during key physiological growth periods. This information will assist growers and extension personnel streamline management decisions for canopy defoliation in peanut throughout Mississippi

Effect of elevated CO2 on peanut performance in a semi-arid production region

With the intensification and frequency of heat waves and periods of water deficit stress, along with rising atmospheric carbon dioxide [CO2], understanding the seasonal leaf-gas-exchange responses to combined abiotic factors will be important in predicting crop performance in semi-arid production systems. In peanut (Arachis hypogaea L.), the availability of developmental stage physiological data on the response to repeated water deficit stress periods in an elevated [CO2] (EC) environment is limited and necessary to improve crop model predictions. Here, we investigated the effects of season-long EC (650 µmol CO2 m−2 s−1) on the physiology and productivity of peanut in a semi-arid environment. This study was conducted over two-growing seasons using field-based growth chambers to maintain EC conditions, and impose water-stress at three critical developmental stages. Our results showed that relative to ambient [CO2] (AC), long-term EC during water-stress episodes, increased leaf-level light-saturated CO2 assimilation (Asat), transpiration efficiency (TE), vegetative biomass, and pod yield by 58%, 73%, 58%, and 39%, respectively. Although leaf nitrogen content was reduced by 16%, there was 41% increase in maximum Rubisco carboxylation efficiency in EC, indicating that there was minimal photosynthetic down-regulation. Furthermore, long-term EC modified the short-term physiological response (Asat) to rapid changes in [CO2] during the water-stress episodes, generating a much greater change in EC (54%) compared to AC (10%). Additionally, long-term EC generated a 23% greater Asat compared to the short-term EC during the water-stress episodes. These findings indicate high levels of physiological adjustment in EC, which may increase drought resilience. We concluded that EC may reduce the negative impacts of repeated water-stress events at critical developmental stages on rain-fed peanut in semi-arid regions. These results can inform current models to improve the projections of peanut response to future climates

Variations and Phenetic Analysis of Peanut Cultivars (Arachis hypogaea L.) Based on Morphological Characteristics

Peanut (Arachis hypogaea L.) is a food commodity that is widely cultivated in Indonesia. At present there has been no analysis of the relationship between peanut cultivars with phenetic methods based on the morphological properties of the plants. Four cultivars of Arachis hypogaea L. Tuban, Talam 1, Talam 2, and Talam 3 used in this research. Morphological characters data was analyzed by description to construct identification key. Similarity index was counted by Simple Matching Coefficient (SSm) formula based on morphological scoring. Cluster analysis was conducted by UPGMA (Unweighted Pair Group Methods using Arithmetic Averages) method to construct dendrogram. PCA (Principal Component Analysis) were performed to defined role of each morphological character in grouping of accessions with MVSP (Multivariate Statistical Program) v. 3.1 software.  The dendrogram showed that four cultivars of Arachis hypogaea L. divided into two main clusters, 4 sub-clusters. The similarity index of clusters is 0.85%