Thesis (M. A. (Agricultural Management)) -- University of Limpopo, 2020 / Field experiments were conducted at two locations; University of Limpopo (Syferkuil) and University of Venda (Thohoyandou) during 2015 and 2016 winter cropping seasons. The objectives of this study were to determine; the effect of genotype (ACC# 1, 3, 4 and 7) and planting density (33, 25 and 20 plants/m2) on four chickpea genotypes having contrasting growth patterns and also to determine the effect genotype and planting density on water use and water use efficiency of four chickpea genotypes having contrasting growth patterns. The experimental design was randomized complete block design in factorial arrangement with three replications. Plant height, number of primary and secondary branches, grain yield and yield components (number of pods per plant, number of seeds per pod, Harvest Index and 100 seed weight [100-SW] and above ground biomass, and were determined at different growth stages. Data obtained was subjected to analyses of variance using the general linear model of Genstat 17th edition. Significant differences between the treatments means were compared using the standard error of difference (LSD) of the means at 5% level. Correlation analyses were performed to assess the relationship between parameters. Plant height varied with genotype from 41 cm (84 DAE) to 44 cm (118 cm) at Syferkuil and 41 (56 DAE) to 44 cm (63 DAE) at Thohoyandou. Primary branches was not significantly affected by genotype and planting density at both locations and seasons. Planting density had significant effect on number of secondary branches, greater number was recorded at low (32, 6) density at Syferkuil in 2016. Above ground biomass was significantly affected by planting density at Syferkuil during in 2015 (5344 kg ha-1) and 2016 (3701 kg ha-1) growing seasons. Genotype and planting density did not affect number of pods plant-1, number of seeds plant-1, 100 SW (100 seed weight), and Harvest index were not significant at both locations and seasons. Grain yield was significantly affected by planting density at Syferkuil in 2015 and Thohoyandou in 2016. Grain yield increased with the increase in planting density at both locations. Two field experiments were conducted at University of Venda (Thohoyandou) during 2015 and 2016 winter cropping seasons. This study aimed at assessing the effect of genotype v and planting density on water use efficiency of four chickpea genotypes with contrasting growth patterns. Crop water use (WU) was determined by monitoring soil water content at 7-day intervals using a neutron probe and, water use efficiency (WUE) was determined as a ratio of crop biomass and grain yield to WU. Genotype and planting density had no significant effect on WU in 2015 and 2016. Genotype and planting density had no significant effect on biomass production (WUEb) and grain yield production (WUEg) in 2015. In contrast, WUEb and WUEg was significantly affected by planting density in 2016. WUEb was 43.2% greater at high density compared to low density. Similarly, WUEg was 39.3% greater at high density compared to low density. WUEb and WUEg increased with the increase with planting density. Therefore, manipulation of management practices such as planting density may increase chickpea production. Keywords: Planting density, genotype, grain yield and yield components, water use efficiency. / National Research Foundation (NRF) and University of Venda Capacity Development

No description available.

MSCAGR (Plant Production) / Department of Plant Production / Agricultural production under rain-fed conditions is largely dependent on the availability of water stored in the soil during rainfall events. The production of cassava (Manihot esculenta Crantz) under rain-fed conditions in the north-eastern part of South Africa is constrained by low and erratic rainfall events. Improving cassava production in the area requires the use of cassava varieties which are efficient in the use of limited soil moisture. The current climate change and increasing population growth on the planet will place more pressure on agriculture to produce more food using less water. Therefore, previously under-researched and underutilised crop like cassava could be used to bridge the food gap in the future. Although the crop currently occupies low levels of utilisation in South Africa and it is cultivated by smallscale farmers in the Low-veld of Mpumalanga, Limpopo and Kwazulu-Natal provinces using landraces with no improved varieties available in the country. Information on the actual pattern of water extraction, water use and water use efficiency of cassava landraces grown in the dry environments of South Africa is limited. Therefore, the objective of the study was to determine the differences in water use efficiency, gaseous exchange and yield among four cassava landraces grown under rain-fed conditions. Two field experiments were conducted during the wetter (2016/2017) and drier (2017/2018) cropping season at the University of Venda's experimental farm. The trials were laid in a Randomized Complete Block Design (RCBD) consisting of four cassava landraces (ACC#1, ACC#2, ACC#3, and ACC#4) replicated three times. Mature cassava stem cuttings of 30 cm long, were planted manually at a spacing of 1 m x 1 m in both seasons. Each experimental unit consisted of six plant rows of 6 m length (36 m2) and 8 rows of 8 m length (64 m2) in the 2016/17 and 2017/2018 cropping season, respectively. The experiments were under rain-fed conditions without fertilizer additions and the plots were kept weed-free throughout the experimental period. Data collected in the field included soil moisture content, gaseous exchange parameters (net leaf ܥܱଶ uptake, stomatal conductance, and intracellular carbon dioxide concentration), chlorophyll content index (CCI), maximum photochemical quantum yield of PSII (Fv/Fm), effective quantum yield of PSII (ФPSII) and photosynthetic active radiation (PAR). Yield and yield components (root length (cm), root girth (cm), number of storage roots and mean root weight (g plant-1), root yield and aboveground biomass), as well as water use efficiency (WUE), were determined at harvest. Soil moisture content was measured at seven-day interval from sowing until harvest using a neutron probe. Soil moisture data were used to determine crop water use using the water balance approach. There was no variation in the root yield and yield components amongst the landraces in 2017/2018 cropping season but, genotypes affected aboveground biomass, root girth, number of roots per plant and root yield in 2016/2017 cropping season. There was a significant difference (P<0.01) in number of roots (per plant) 81% and 62% greater in ACC#3 and ACC#2 (6.7 & 6.0, respectively) compared with ACC#1 and ACC#4, which both recorded 4 roots per plant. Similarly, root girth was greater in ACC#3 (17.8 cm) and ACC#2 (18.2 cm) compared to ACC#1 (14.1 cm) and ACC#4 (12.9 cm), which were statistically the same. In contrast, total biomass (P<0.01) and root yield (P<0.05) were greater in ACC#3 (20.7 and 11.9 t ha-1, respectively) and ACC#1 (22.0 and 11.3 t ha-1, respectively) compared to ACC#2 and ACC#4 with root yields of 10.2 and 9.5 t ha-1, biomass of 17.1 and 16.3 t ha-1, respectively. Although the genotype x cropping season interaction did not affect root yield and yield components, root yield (by 33.8%; 2.7 t ha-1) and yield components were greater in the wetter compared to the drier season as expected. Water use efficiency of root yield (WUErt) and water use efficiency of biomass production (WUEb) varied with landraces in season I from 37.0 kg ha-1 mm-1 (ACC#4) to 46.60 kg ha-1 mm-1 (ACC#3), and between 71.30 kg ha-1 mm-1 (ACC#2) and 86.0 kg ha-1 mm-1 (ACC#1), respectively. Landraces did not differ in their water use and soil moisture extraction in both seasons but differed in season. However, there was a significant positive correlation between water use efficiency of root yield (WUErt) (0.963***) and water use efficiency of biomass production (WUEb) (0.847***). WUE of biomass production was greater in the drier than the wetter season partly because of dry matter accumulation per evapotranspiration within the landraces. Photosynthesis did not vary with landraces, however, stomatal conductance varied with landraces from 0.08 mmol m-2 s-1 (ACC#4) to 0.2 mmol m-2 s-1 (ACC#2). In contrast, ACC#1 and ACC#3 recorded the same value of stomatal conductance, which is 0.1 mmol m-2 s-1. The effective quantum yield of PSII photochemistry (ΦPSII) did not vary with landraces but the maximum photochemical quantum yield of PSII (Fv/Fm) varied with landraces from 0.652 (ACC#4) to 0.792 (ACC#3) in season II. The proportion of intercepted radiation was affected by landraces in 2017/2018 cropping season. Highest proportion of intercepted radiation was observed in ACC#3 and the lowest in ACC#2. Proportion of intercepted radiation varied with landraces from 22.62% (ACC#2) to 86.45% (#ACC#3). There were significant genotypic variations in chlorophyll content recorded in both season. Chlorophyll content varied with landraces from 33.1 CCI (ACC4) to 55.4 CCI (#ACC3) in the 2016/2017, and in 2017/2018 cropping season chlorophyll content varied with landraces from 36.9 CCI (ACC4) to 78.7 CCI (#ACC3). The highest genotypic variation in chlorophyll content was observed in ACC#3, whilst the lowest chlorophyll content was recorded in ACC#4 in both seasons. / NRF

Drought and salt stress are the main global factors that reduce the average yield of most major crops. In order to meet global demands, we will need to double food production by 2050 (Tilman, Balzer, Hill, & Befort, 2011). Plant growth-promoting bacteria (PGPB) are a group of bacteria that alleviate the harmful effects of abiotic stresses such as salt, heat and drought stress on plants and decrease the global dependence on hazardous agricultural chemicals. We identified that beneficial microbes isolated from desert plants (indigfera argentea) from Jizan region, in 2012 enhance the tolerance of a variety of crop plants to drought and salt stresses under laboratory conditions and in field trials. We analyzed the interaction of these bacteria with the plants by genetic, biochemical and imaging techniques. The goal of this dissertation is to ultimately improve our understanding of the mechanisms of drought and salt stress tolerance conferred by beneficial microbes that can be used as a sustainable solution for plants and crops in degrading lands (deserts) and land affected by abiotic stresses. Outlines how each of chapter of this dissertation will contribute to the discovery of novel drought and salt stress tolerance strategies using a desert-specific bacterial endophyte.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第21147号 / 農博第2273号 / 新制||農||1058(附属図書館) / 学位論文||H30||N5121(農学部図書室) / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 北山 兼弘, 教授 小杉 緑子, 教授 北島 薫 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Student Number : 9511039F - MSc Dissertation - School of Animal, Plant and Environmental Sciences - Faculty of Science / An estimated 91 % of South Africa’s total land area is considered dryland and susceptible to desertification. In response, South Africa has prepared a National Action Programme to combat land degradation, and this requires assessment and monitoring to be conducted in a systematic, cost effective, objective, timely and geographically-accurate way. Despite a perception-based assessment of land degradation conducted in 1999, and a land-cover mapping exercise conducted for 2000/2001, there are few national scientifically rigorous degradation monitoring activities being undertaken, due largely to a lack of objective, quantitative methods for use in large-scale assessments. This study therefore tests a satellitederived index of degradation for the Limpopo Province in South Africa, which is perceived to be one of the most degraded provinces in the country. The long-term average maximum normalized difference vegetation index (NDVI), calculated from a time series (1985-2004) of NOAA AVHRR satellite images, as a proxy for vegetation productivity, was related to water balance datasets of mean annual precipitation (MAP) and growth days index (GDI), using both linear and non-linear functions. Although the linear regressions were highly significant (p<0.005), a non-linear four parameter Gompertz curve was shown to fit the data more accurately. The curve explained only a little of the variance in the data in the relationship between NDVI and GDI, and so GDI was excluded from further analysis. All pixels that fell below a range of threshold standard deviations less than the fitted curve were deemed to represent degraded areas, where productivity was less than the predicted value. The results were compared qualitatively to existing spatial datasets. A large proportion of the degraded areas that were mapped using the approach outlined above occurred on areas of untransformed savanna and dryland cultivation. However the optical properties of dark igneous derived soils with high proportions of smectitic minerals and therefore low reflectance, were shown to lower NDVI values substantially. Overall, there was an acceptable agreement between the mapped degradation and the validation datasets. While further refinement of the methodology is necessary, including a rigorous field-based resource condition assessment for validation purposes, and research into the biophysical effects on the NDVI values, the methodology shows promise for regional assessment in South Africa.

<div>Increasing the capability of maize hybrids to use nitrogen (N) more efficiently is a common goal that contributes to reducing farmer costs and limiting negative environmental impacts. However, development of such hybrids is costly and arduous due to the repeated need for laborious field and laboratory measurements of whole-plant biomass and N uptake in large early-stage breeding programs. This research evaluated alternative in-season methodologies, including field-based physiological measurements and hyperspectral remote imagery, as surrogate or predictive measures of important end-of-season N efficiency parameters. </div><div><br></div><div>Differences in the genetic potential of 285 hybrids (derived from test crosses to a single tester) with respect to N Internal Efficiency (NIE, grain yield per unit of accumulated plant N) were investigated at two Indiana locations in 2015. The hybrids (representing both early and late maturity groups) were grown at one low N rate and a single plant density. Germplasm sources included USDA, Dow AgroSciences, and “control” checks. Various secondary traits (plant height, stalk diameter, LAI, green leaf counts, and SPAD measurements) were evaluated for their potential role as surrogate measurements for N metrics at maturity (R6) such as plant N content or NIE. Four band (RGB, NIR) multispectral airborne remote sensing imagery at R1 and R3/R4 was also collected. The key findings were: 1) identification of the 10 highest and 10 lowest ranked hybrids for each maturity group in both grain yield and NIE categories, 2) the discovery of 5 top performing hybrids which had both high NIE and high yield, 3) strong correlations of leaf SPAD (at R1 and R2/R3) to grain yield or plant N at R6, 4) none of the surrogate measurements were significantly correlated to NIE, and 5) vegetation indices (NDVI and SR) from the remote imaging were not predictive of hybrid differences in yields or whole plant N content at R6. From these results we concluded genetic potential exists among current maize germplasm for NIE breeding improvements, but that more in-depth investigations were needed into other surrogate measures of relevant N efficiency traits in hybrid comparisons. </div><div><br></div><div>Next, hyperspectral imaging was investigated as a potential predictor of agronomic parameters related to N Use Efficiency (NUE, understood here as grain yield relative to applied N fertilizer input). Hyperspectral vegetation indices (HSI) were used to extract the image features for predicting N concentration (whole plant N at R6, %N), Nitrogen Conversion Efficiency (biomass per unit of plant N at R6, NCE), and NIE. Images were collected at V16/V18 and R1/R2 by manned aircraft and unmanned aerial vehicles (UAVs) at 50 cm spatial resolution. Nine maize hybrids, or a subset, were grown under N stress conditions with two plant densities over three site years in either 2014 or 2017. Forty HSI-based mixed models were analyzed for their predictability relative to the ground reference values of %N, NCE, and NIE. Two biomass and structural indices (HBSI1_682,855 and HBSI2_682,910 at R1) were predictive of NCE values and capably differentiated the highest and lowest ranked NCE hybrids. The highest prediction accuracy for NIE was achieved by two biochemical indices (HBCI_8515,550 at both V16 and R1, and HBCI9_490,550 at R1). These also allowed for hybrid differentiation of the highest and lowest ranked NIE hybrids. From these results, we concluded that accurate end-season prediction of hybrid differences in NCE and NIE was possible from mid-season hyperspectral imaging (yet not for %N). Furthermore, the quality of the predictions was dependent on image timing, actual HSI, and the targeted N parameter at maturity. </div><div><br></div><div>One benefit to hyperspectral imaging is that it can provide greater discrimination of imaged materials through its narrow, contiguous bands. However, the data are highly correlated in some ranges. This problem was mitigated through the use of partial least squares regressions (PLSR) to predict the three N parameters from the field data described previously. Data were divided into train and test; then ten-fold cross validation was performed. The twelve models evaluated included those with 89 image bands of 5 nm widths and a selected, reduced set of hyperspectral bands as predictors. The key findings were that PLSR models based on V16 and R1 images provided accurate predictions for final whole-plant %N (R² = 0.73, CV = 11%; R² = 0.68, CV = 10%) and NCE at R6 (R² = 0.71, CV = 10%; R² = 0.73, CV = 12%) but not NIE. Additionally, accurate hybrid differentiation was possible with the combination of hyperspectral imaging and PLSR at R1 to predict %N and NCE values at R6 stage. </div><div><br></div><div>The PLSR and HSI results from this research showed that hyperspectral imaging has the potential for prediction of NUE parameters through non-destructive remote sensing at a broad scale. Additional validation is needed through the study of other genotypes and locations. Nevertheless, practical application of these methods through the integration into early stage breeding programs may allow the early identification of the highest and lowest ranked hybrids providing data-driven decisions for selecting genotypes. Implementation of improved imaging approaches may drive the increased development of maize hybrids with superior NUE. </div><div><br></div>

Perennial ryegrass (Lolium perenne L.) is a cool-season turfgrass susceptible to low temperature injury. Wilt-based (WB) irrigation is a common practice in scheduling turf irrigation as an alternative to well-watered (WW). Moisture stress has been shown to promote cold hardiness but this has not been investigated in response to WB irrigation. Measurements of 13C isotope discrimination (DELTA) are useful predictors of water use efficiency (WUE), drought resistance, evapotranspiration (ET) and salinity tolerance but the relevance to turfgrass cold hardiness has not been determined. DELTA analyses may enable more efficient screening protocols in breeding for improved cold hardiness. Objectives of this study were to examine perennial ryegrass genotypes in relation to cold hardiness, DELTA and WUE in response to WW and WB irrigation schedules, to compare genetic diversity between top-performing (TP) and bottom-performing (BP) perennial ryegrass genotypes, and to assess the predictive value of DELTA of for cold hardiness. Six genotypes were selected based on turf quality from the most northern NTEP location (Orono, ME) and included three TP (‘All Star 2’, ‘Mach I’ and ‘Sunkissed’) and three BP (‘APR-1234’, ‘Buccaneer’ and ‘WVPB-R-82’) genotypes. ET, yield, WUE, shoot water content, rooting potential, wilting tendency, DELTA and median lethal temperatures (LT50) using whole-plant survival were measured from greenhouse samples grown in weighing lysimeters in 2007 and 2008. Plant measurements in both years were based on sampling conducted at the last cycle after 68-d of irrigation with 100% of ET applied at leaf-roll (WB) versus ET replacement every 4-d (WW). Lower LT50 values were generally associated with low yield, low WUE and low shoot water content, whether the result of irrigation treatment or genotypic variation. TP genotypes demonstrated significantly lower LT50 temperatures (greater cold hardiness) in comparison to BP genotypes in both years. Modest cold hardiness enhancement with WB irrigation was highest for TP genotypes. Wilting tendency and DELTA were not reliable predictors of cold hardiness, although individual TP genotypes exhibited responses distinctly different than some BP genotypes. Further research is needed to investigate the physiological mechanisms of enhanced turfgrass cold hardiness in response to moisture stress.

No description available.

Current maximum efficiency of phosphorus (P) fertilizers that is utilized by plants in the same year of application ranges from near zero to thirty percent. Despite low utilization of P in crop production, yields are often limited by P deficiencies. Innovative technology is requisite to achieve greater efficiency as fertilizer demands are increasing, while phosphorus mineral resources are rapidly being depleted. A growing environmental concern for nutrient pollution of surface waters also carries significant weight. A novel new product, Carbond® P, is promising technology to increase P use efficiency. Research is needed to understand its capabilities and the functioning mechanisms imbedded within its technology. Several research studies were conducted to evaluate Carbond® P (CBP) against traditional fertilizers ammonium polyphosphate (APP) and monoammonium phosphate (MAP). A soil column leaching study was conducted to determine P mobility through three soils, at two rates (20 and 30 kg P ha-1) in either a banded or mixed soil application. Mobility of P was evaluated at 24, 48, 110 and 365 d after fertilization. CBP showed significantly greater total P leachate values across all soil types and application rates averaged across all readings taken until 365 daf for both application types. In the banded applications, CBP generally produced significantly greater solubility than MAP or APP up until 110 daf. For applications mixed with soil, CBP and MAP had greater solubility than APP at 24 days after application, but by the later evaluation dates (48 and 110 daf) the CBP was significantly higher than both MAP and APP. No statistical significance was found in the leachate P 365 daf in either the banded or mixed applications. One glasshouse study on maize (Zea mays L.) grown in three soils were conducted at 0, 5, 10, 20, 40, 80, and 160 kg P ha-1 comparing CBP and APP fertilizer impacts on early season growth. CBP produced significantly more biomass in two soils when averaged across rates (and at the 20 kg P ha-1 rate in a third soil), increased petiole P in one soil and thicker stems in another. Two field trials showed similar physiological advantages with CBP over APP at later growth stages. CBP maize responded with significantly more biomass and P uptake at the V12-V18 growth stages in one field, as well as plant height in another. At the R2-R3 growth stages, CBP also produced thicker stalks in both fields than APP. These growth enhancements were strongest in medium to highly calcareous soil (6-12 %) low in P (7 mg kg-1). These observations warrant the use of CBP and further investigation to understand its benefits and limitations.