Mid-season Drought Research Articles

Bundling Genetic and Financial Technologies for More Resilient and Productive Small-Scale Farmers in Africa

Abstract Using a multi-year, spatially diversified randomised controlled trial spanning two African countries, this paper explores whether a complementary bundle of genetic and financial technologies can boost the resilience and productivity of small-scale farmers. The analysis shows that both moderate droughts and more severe yield losses undermine the resilience of control-group households, and that these shocks have long-lasting effects as farmers invest and produce less following shocks. Severe yield shocks also increase hunger and food insecurity. The genetic technology—drought-tolerant seeds—provides economically significant protection against mid-season drought and mitigates the long-term drop in farm productivity seen in the control group. The financial technology—satellite-based index insurance—offsets the long-term consequences of severe yield losses that are not mitigated by the drought-tolerant seeds. Finally, the analysis shows that treatment-group farmers who experienced shocks and saw the technologies in action subsequently increased their agricultural investment beyond pre-shock levels, an effect we call the resilience dividend. Unfortunately, this apparent experiential learning cuts both ways. Farmers who did not experience the efficacy of the risk management technologies backed away from using them. Our findings thus showcase how genetic and financial risk-mitigating technologies can offer farmers more complete protection, as well as the challenge of inducing sustained uptake of technologies that are midway between experience and credence goods and only infrequently reveal their benefits.

Drought Timing Modulates Soil Moisture Thresholds for CO2 Fluxes and Vegetation Responses in an Experimental Alpine Grassland

Drought timing determines the degree to which dry events impact ecosystems, with the ability of key processes to withstand change differing between drought periods. Findings indicate that drought timing effects vary across ecosystems, with few studies focusing on alpine grasslands. We conducted a mesocosm experiment using small grassland monoliths collected in September from the high Alps and left to overwinter at 0 °C until the experiment began in lowland Italy under late-winter outdoor conditions. Together with watered controls, we imposed three different drought treatments (zero precipitation): (1) one-month early-drought immediately after simulated snowmelt; (2) one-month mid-drought a month after melt-out; and (3) continuous two-month drought across the entire experimental period. Ecosystem responses were assessed by measuring CO2 fluxes, while vegetation responses were investigated by measuring aboveground net primary production (ANPP) of graminoids and forbs and post-harvest resprouting after one-month rehydration. We found that ecosystem respiration and gross ecosystem production (GEP) during the day were more negatively affected by mid-season drought compared to drought starting early in the season. By the end of treatments, GEP reduction under mid-season drought was similar to that of a continuous two-month drought. ANPP reduction was similar in early- and mid-drought treatments, showing a greater decrease under an enforced two-month period without precipitation. Plant resprouting, however, was only reduced in full- and mid-season drought pots, with forbs more negatively affected than graminoids. Seasonal soil moisture variation can account for these patterns: remaining winter moisture allowed almost full canopy development during the first month of the season, despite precipitation being withheld, while soil moisture depletion in the second month, resulting from higher temperatures and greater biomass, caused a collapse of gas exchange and diminished plant resprouting. Our data illustrates the importance of the timing of zero-precipitation periods for both plant and ecosystem responses in alpine grasslands.

Phenotyping RIL Population to Identify Water Deficit Tolerant Lines in Groundnut (Arachis hypogaea L.)

Background: Genotype sensitivity to mid-season drought suggests the possibility of identifying genotypes with high yield potential and low sensitivity to mid-season droughts. The overall objective of the present research was to select genotypes with high tolerance to mid-season moisture stress. This effort includes assessing the variation of physiological and productive traits among RIL population lines, assessing the range of correlation for physiological and productive traits across two seasons and identifying a set of contrasting material under drought stress conditions. Methods: To assess the recombinant inbred lines (RIL) under moisture stress, we screened RIL population of groundnut with 432 lines and parents under mid-season drought stress conditions in rabi for two years. During the drought stress period, soil moisture content (SMC) and temperatures were measured. SPAD chlorophyll meter reading (SCMR), specific leaf area (SLA), relative water content (RWC), visual wilting rate (VWR) and canopy temperature (CT) were recorded at the end of the stress period. Pod yield per plant (PYPP), kernel yield per plant (KYPP) and shelling percent (SP) were recorded at harvest. Result: Physiological traits and yield attributes varied significantly among the RIL population. The Genotype by Trait biplot (GT biplot) revealed that the yield attributes showed a positive association with RWC, SCMR and a negative association with SLA, VWR and CT. The inbred lines were classified as visually healthy with high physiological and high or moderate yield traits; visually wilting with low physiological and low yield traits under a drought environment. The identified superior and inferior lines werefurther utilized to analyze genomic regions and genes for drought tolerance in groundnut.

Development of green energy based micro-sprinkler irrigation system for small holdings of SAT region

The Indian agriculture in the region of semi-arid tropics (SAT), characterized by small holders, small water harvesting and recycling system assumes a significant potential to sustain agricultural productivity by providing supplemental as well aslifesaving irrigation and mitigating mid-season drought. In Indian Agriculture, major energy consuming activities include on-farm water management. Efficient and cost-effective irrigation system matching the small-scale water harvesting and storage, are anot available in this region. In view of this, a carry-and-irrigate type micro-sprinkler irrigation system was designed and developedin order to achieve the holistic utilization of water resources and niche-potential of solar energy and gravity. The performance was measured on various parameters of application rate, Christiansen uniformity coefficient and pattern efficiency and were quantified as 14.2 mm/h, 91.3% and 89.01% respectively. The develop irrigation system qualified the performance criteria as standardized by ASAE, 1996. Given the characteristics of low cost and portability, it can considerably substantiate the vegetable production at household scale. Though, this system is developed exclusively for the location representing typical dryland agriculture of India, it can be easily and effectively replicated in other part of the world having similar agro-ecosystem. This simple water management technique utilizing the niche potential of gravity and solar energy can significantly contribute to the various objectives of sustainable development goal.

Bundling Stress Tolerant Seeds and Insurance for More Resilient and Productive Small-Scale Agriculture

Risk often inhibits on-farm investment by smallholder farmers. Recent evidence indicates that index insurance and stress tolerant seeds can separately and partially offset this risk effect. In this study, we explore whether the complementarities between these two risk management technologies can be harnessed to underwrite a resilient, high productivity small farm sector. Utilizing a multi-year randomized control trial that spanned two countries and exploits natural variation in weather shocks, we find that drought tolerant maize seeds mitigate the impact of mid-season drought. Compared to farms in control villages, where shocks have persistent effects that reduce future investment and productivity, those with access to both drought tolerant seeds and multi-peril index insurance show greater resilience and immediately bounce back from shocks. Experiential learning is key to realizing this resilience effect: Farmers who experienced shocks intensify their subsequent use of the technologies and exhibit what we call resilience-plus, while those who did not experience shocks disadopt. Together these findings showcase important complementarities between these risk mitigating technologies and the crucial role learning plays in tapping their potential stochastic and dynamic benefits to small farmers.

Real Time Contingency Measures to Mitigate Mid-season Drought Situation for Rainfed Maize in Kandi Region of Punjab

Real Time Contingency Measures to Mitigate Mid-season Drought Situation for Rainfed Maize in Kandi Region of Punjab

A Variable-Rate Irrigation Decision Support System for Corn in the U.S. Eastern Coastal Plain

HighlightsA decision support system using the USDA-ARS Irrigation Scheduling and Supervisory Control and Data Acquisition (ISSCADA) system was evaluated for spatially managing corn irrigation in the U.S. Eastern Coastal Plain.The ISSCADA system was compared to traditional scheduling methods based on measured soil water potentials.The ISSCADA system with feedback on allowable soil water depletion shows potential as a tool for growers for managing variable-rate irrigation systems.Abstract. Variable-rate irrigation (VRI) systems are capable of applying different water depths both in the direction of travel and along the length of the irrigation system. VRI systems maybe useful for improving crop water management and efficiency. Although VRI technology is available and has high grower interest, it has had limited adoption. To address this, researchers have developed a decision support system that uses remote sensing of plant, soil, and microclimate to schedule VRI irrigations. In this research, we evaluated the use of the USDA-ARS Irrigation Scheduling and Supervisory Control and Data Acquisition (ISSCADA) system for spatially managing corn irrigation in the U.S. Eastern Coastal Plain. The ISSCADA system consists of center pivot mounted infrared thermometers (IRT) to measure crop canopy temperatures and in situ soil water sensors. An integrated crop water stress index (iCWSI) was calculated from the canopy temperatures. The ISSCADA system analyzes the iCWSI and soil water measurements to provide an irrigation recommendation. The ISSCADA system was evaluated using (1) iCWSI values and (2) a hybrid ISSCADA system that incorporated both iCWSI values and soil water depletion criteria. These ISSCADA treatments were compared to traditional irrigation management using measured soil water potentials. The ISSCADA system was evaluated for four years. In 2016 and 2017, corn yields and water use efficiency were not significantly different between the irrigation treatments due to adequate rainfall during the growing season. In 2018 and 2019, mid-season drought conditions and sporadic rainfall patterns required frequent irrigations. In both years, the irrigation treatment corn yields were not significantly different from each other but were greater than the rainfed yields. In 2018, the irrigation treatments produced corn yields of 10.7, 10.4, and 10.1 Mg ha-1 for the hybrid, ISSCADA, and SWP treatments, respectively. Over the four-year study, the water use efficiencies of the irrigation treatments were not significantly different from each other or the rainfed treatment and ranged from 16.6 to 22.7 kg ha-1 mm-1. In the two years that the hybrid ISSCADA system was used for managing irrigations, it produced higher corn yields and required less irrigation than the standard ISSCADA treatments. Results from this experiment will help to evaluate and refine the ISSCADA system to provide a tool for growers to use in managing spatial irrigation with VRI systems. Keywords: Crop water stress, Decision support system, Variable rate irrigation.

Resource Management Domains of Kharif and Rabi Season Fallows in Central Plateau Region of India: A Strategy for Accelerated Agricultural Development

Over last few decades, acreage of total fallow lands (Kharif and Rabi seasons) in India has remained almost unchanged around 25Mha. The acreage of Kharif (summer) and Rabi (winter) Fallows in Madhya Pradesh (MP) are 1.98Mha and 5.51Mha, respectively. In the semi-arid agroclimatic zones of the states, Fallow-Wheat/Gram/Indian-Mustard cropping systems are practiced. After harvest of Kharif rice, kodo-kutki, maize or sorghum, farmers generally practice post-rainy season Rabi fallows in the sub-humid regions, south of Narmada River. Kharif fallowing is largely the result of the inability of the farmers to make planting dates independent of monsoon forecasts, and make efficient use of rain water. It appears that factors responsible for Kharif and Rabi fallows are distinctly different and a general consequence of distinctly different soil moisture regimes prevailing in the two crop seasons. Kharif and Rabi fallows have two distinct resource management domains. Whereas, Kharif fallows can be tackled with “PMP-dry seeding” agronomy, production constraints of Rabi fallows can be substantively tackled by shifting from tilled to zero-till agriculture with residue management to make efficient use of the conserved rain water. Some irrigation support will prove useful to tackle mid-season droughts in both situations. Conservation agricultural practices can significantly improve and stabilize crop yields in black soils and other associated soils of in the semi-arid tropics region of the Central India.

Towards applying N balance as a sustainability indicator for the US Corn Belt: realistic achievable targets, spatio-temporal variability and policy implications

Gains in nitrogen use efficiency in the production of corn (Zea mays L.) remain low due to management constraints and difficulties in accurately predicting the optimum fertilizer application rate. Retailers and consumers are looking for robust sustainability indicators to help drive the industry towards more sustainable food production, including the simple input-output based ‘N balance’ metric. Seven-year simulations for 25 locations across five US Corn Belt States (NE, IA, MN, IL, IN) were conducted using the biogeochemical Adapt-N® model to determine (i) realistically achievable N balance values when N rates are optimized, (ii) the effects of climate and soil type on achievable N balance values, and (iii) the relative importance of N application timing (fall, spring, split in-season) and formulation (+/− nitrapyrin) in reducing N balance. Split in-season applications reduced N rates by 39% and 22% over fall and spring applications and N balance by 36% and 22%, respectively. Adding nitrapyrin to fall or spring preplant applications modestly reduced N inputs by 9% and 4% and N balance by 18% and 12%. Split N management reduced N losses by 52% and 31% of total area-scaled N losses compared to fall and spring N applications and adding nitrapyrin by 13% and 10%, respectively. Benefits from improved timing and formulation were greater in the more humid eastern part of the region. Split in-season N management allows farmers to reach sustainable N balance levels in 88% of cases, with the remainder mostly affected by mid-season droughts. Economic assessment found partial profit to be enhanced with lower N balance, suggesting that N balance reductions may be achieved through voluntary approaches. The model simulations offered ranges of realistic N balance values that can be used to inform policy discussions. It appears that N balance is best applied when averaged over multiple seasons and threshold levels should be guided by characteristics of the production environment, including soil type and climate.

Recognizing the Famine Early Warning Systems Network: Over 30 Years of Drought Early Warning Science Advances and Partnerships Promoting Global Food Security

AbstractOn a planet with a population of more than 7 billion, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow-onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the U.S. Agency for International Development’s Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model, and predict food insecurity. Here we provide an overview of FEWS NET’s DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET’s monitoring system, it draws from many disciplines—remote sensing, climate prediction, agroclimatic monitoring, and hydrologic modeling. Here we describe FEWS NET’s multiagency multidisciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Midseason droughts are monitored using multiple cutting-edge Earth-observing systems. Crop and hydrologic models can translate these observations into impacts. The resulting information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Reduction in primary production followed by rapid recovery of plant biomass in response to repeated mid-season droughts in a semiarid shrubland

The frequency and severity of extreme weather events, including droughts, are expected to increase due to the climate change. Climate manipulation field experiments are widely used tools to study the response of key parameters like primary production to the treatments. Our study aimed to detect the effect of drought on the aboveground biomass and primary production both during the treatments as well as during the whole growing seasons in semiarid vegetation. We estimated aboveground green biomass of vascular plants in a Pannonian sand forest-steppe ecosystem in Hungary. We applied non-destructive field remote sensing method in control and drought treatments. Drought treatment was carried out by precipitation exclusion in May and June, and was repeated in each year from 2002. We measured NDVI before the drought treatment, right after the treatment, and at the end of the summer in 2011 and 2013. We found that the yearly biomass peaks, measured in control plots after the treatment periods, were decreased or absent in drought treatment plots, and consequently, the aboveground net primary production was smaller than in the control plots. At the same time, we did not find general drought effects on all biomass data. The studied ecosystem proved resilient, as the biomass in the drought-treated plots recovered by the next drought treatment. We conclude that the effect of drought treatment can be overestimated with only one measurement at the time of the peak biomass, while multiple within-year measurements better describe the response of biomass.

Transcriptome profiling and identification of differentially expressed transcripts in response to mid season drought in groundnut Arachis hypogeae L

Transcriptome profiling and identification of differentially expressed transcripts in response to mid season drought in groundnut Arachis hypogeae L

Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these already endangered forest ecosystems and should be further monitored using both ground and satellite approaches.

Characterising production environments for maize in eastern and southern Africa using the APSIM Model

Maize is a staple food crop in eastern and southern Africa with significant contribution for food security of this vast region. Efforts to breed superior maize cultivars for the region are challenged by high genotype x environment interactions arising mainly due to variable soil moisture supply caused by high temporal and spatial variability in rainfall. Information on major drought patterns and their frequencies, which can assist in dealing with such interactions in the region, however, is not available. The objectives of this study were therefore to (i) identify major drought patterns and their frequencies, (ii) identify iso-environments based on the similarity of drought patterns and (iii) explore scope for yield improvement through optimising genotype and management in various drought patterns. We used the well validated APSIM model to characterise major drought patterns and their frequencies experienced by maize cropping systems in the target population of environments spread across six countries of the region including Ethiopia, Kenya, Tanzania, Malawi, Mozambique and Zimbabwe. The data-base used for the model simulations consisted of 35 locations, 17–86 years of daily climate records and three cultivars. The dynamic changes in water supply-demand ratio in each season was simulated against the thermal time for each cultivar across the 35 locations and clustering analysis was used to cluster the major drought patterns. The analysis identified four major drought patterns characterised by low-stress, mid-season drought, late terminal drought and early-terminal drought patterns, occurring at 46%, 11%, 22% and 21% of the years, respectively. The frequencies of these patterns varied in relation to locations, genotypes and management. Yield reduction of up to 80% was observed for early terminal drought compared with low-stress drought pattern. There was significant scope for yield improvement through manipulating genotype and management. These results have important implications for germplasm enhancement and deployment over similar environments in the region.

Impacts of supplemental irrigation as a climate change adaptation strategy for maize production: a case of the Eastern Cape Province of South Africa

Dry spells and climatic hazards are responsible for maize output decline, sometimes to levels below potential yield levels. There is a pressing need to reduce the gap between actual and potential maize yield/ha, especially among farmers in semi-arid regions. This present study examines the potential role of supplemental irrigation and its differential impact on maize yield in the Eastern Cape Province of South Africa. In this study, maize yield data were generated from information recorded over a period of 20 years by farmers in Ntabankulu through cross-sectional interviews with 124 randomly-selected farming households. Maize yields for interviewed farmers were analysed for each of the experienced climatic hazards, for yield decline per ha and preferable adaptation strategies. Maize yield analyses show a maximum ceiling/attainable yield of 0.234 t/ha and average farm yield of 0.146 t/ha. Floods or hailstorms cause 75% decline in maize yield/ha and there was no significant difference between farmers practising irrigation and those practising dryland farming ( P > 0.05). Low/no rains throughout the season; delay or low onset of rainfall and a rain-break for a week or more in a season results in 75%; 54% and 50.5% decline in maize yield/ha, respectively. On a scale of 1 to 10, farmers highly rank practicing supplementary irrigation (8.4) and change of planting date (7.8) as important adaptation strategies. Rescheduling planting date from the traditional planting times to earlier or later planting dates, assisted by use of weather reports and forecasting, to some extent curbs the impact of delays or slow onset of rainfall on yield. Supplemental irrigation is instrumental in reducing the impact of mid-season drought (rains break for a week) and light rainfall throughout the season. Analyses of actual yields and yield decline against each of the experienced climatic hazards provided insight into management possibilities to stabilize maize output. Keywords: agronomic practices, climatic hazards, supplemental irrigation, semi-arid areas

Spatial analysis of rainfall variability and rainfed rice crop using GIS Technique in West Bengal (India)

The rainfed areas receive mean annual precipitation in range of 500-1500 mm with high degree of variability and are beset with problems of mid-season drought and associated impacts on the crop productivity. In this paper, analysis of weekly, monthly, annual rainfall and weekly rainfall probabilities in relation to crop productivity has been carried out for all the stations of the study area in West Bengal where rain-fed agriculture is predominant. However, duration of dry spells and its probabilities, climatic derivatives like commencement and cessation of rainy season, length of growing period (LGP) and estimates of water balance parameters have been carried out, in respect of all blocks in the identified three districts in West Bengal. The mean productivity during kharif season indicated that, highest productivity values of 3 to 3.5 t/ha are noticed in the block of central districts of Burdwan, Bankura, Birbhum, Hoogly districts. Perhaps, irrigation facilities in these districts might have helped in arriving at such high productivity rates. Low productivity of 1 to 1.5 t/ha have been noticed in two to three blocks of South 24-Paraganas and in Jalpaiguri districts. The productivity levels of northern districts, viz., Jalpaiguri, Coochbehar, West Dinajpur, South 24-Paranagas vary from 1.5 to 2.0 t/ha. The lowest productivity of 11.28 q /ha in Jaldha and 14.89 q /ha in Manbazar in 1996 can be due to heavy rainfall conditions in June and again in August. The mean productivity pattern of rice crop during kharif season in identified districts was analyzed with respect to occurrence of number of dry spells at different growth stages and average MAI values. The productivity was also related to monthly rainfall (July) and correlations have been mentioned for Jaldha block (0.22) and Manbazar block (0.64). The highest productivity of 2-3 t/ha are recorded in hot sub-humid to humid regions of West Bengal where LGP vary from 150 to 200 days. From the study of the probability of dry and wet spells and MAI during different crop phenophases, the most vulnerable phases can be identified in each region.

Adaptation to mid-season drought in a sweetpotato (Ipomoea batatas [L.] Lam) germplasm collection grown in Mozambique

Abstract Drought has negative effects on sweetpotato production. Two experiments with two watering treatments (irrigated and water-stressed) were conducted at Umbeluzi Research Station in 2015. The objectives were to (i) determine response of 48 sweetpotato germplasms to mid-season drought, (ii) determine best traits for improvement of storage root yield under mid-season drought and (iii) assess the selection criteria for identifying drought tolerance in sweetpotato germplasms. The irrigated and water- stressed trials received 640 and 400 mm of water, respectively, throughout the season. Water stress was imposed from 30 to 70 days after planting. Each treatment had two replicates arranged in a randomized complete block design. Data collected on storage root and vine yield and derived drought tolerance indices including harvest index were subjected to analysis of variance in R. Sweetpotato germplasms with high storage root yield under mid-season drought were associated with a high harvest index. Harvest index stability and the geometric mean are key to identifying cultivars with high and stable storage root yield under both treatments. MUSGP0646-126, Irene and Ivone combined both low TOL, SSI, HI and high yield storage root yield across the treatments and over seasons. The use of drought and harvest indices is encouraged for selecting improved cultivars for varied production environments and their regular use in accelerated breeding schemes is suggested.

Change of arginine content and some physiological traits under midseason drought in peanut genotypes with different levels of drought resistance

Peanut production areas frequently suffer from drought, which can cause severe yield losses, increased aflatoxin, and compositional changes in seed. Midseason drought is generally the most detrimental to seed yields and in altering seed protein composition. The purpose of this study was to investigate the effect of midseason drought on arginine content in peanut genotypes with different levels of drought resistance. The experiment was conducted under field conditions for 2 years. Two water regimes (well-watered conditions and no irrigation during 30-60 days after planting) were assigned as main plots, and five peanut genotypes were arranged in subplots. Arginine content of mature peanut seed was analyzed at harvest. Midseason drought increased arginine content in all genotypes in both years. Variation in arginine content among peanut genotypes also indicated the possibility for breeding programs to improve arginine content in peanut.

Water deficit stress affects photosynthesis and the sugar profile in source and sink tissues of groundnut ( Arachis hypogaea L.) and impacts kernel quality

Water deficit stress conditions disturb photosynthetic activity of plants and thereby affect further growth and the mobilization of assimilates towards sink tissues. The influence of mid-season drought on sugar metabolism in both source and sink tissues and its sustained effect on kernel quality across three different habit groups of groundnut was investigated. The experiment was conducted in Kharif 2012 and water deficit stress was created by withholding irrigation for 40 days between 30−70 days after sowing under rain-out shelter to simulate mid-season drought condition. Imposition of water deficit stress reduced net photosynthesis rate, which significantly altered the sugar profiles in leaf. The content of glucose, fructose and sucrose decreased in the leaf tissue, whereas the content of sugar alcohol (inositol and mannitol) and trehalose increased. The sugar profile of the sink tissue (kernel) was also altered under stress but changes were slightly different. The sugar alcohol and oligosaccharides (RFOs) showed significant increase, but the level of mono- and di-saccharides did not show significant change. The results suggest different drought tolerance strategies in source and sink tissues. The kernel quality was also affected under stress with lower oil and higher protein content. The content of oleic acid was reduced, while linoleic acid increased resulting in a decrease of the O/L ratio and oil stability. Alteration of quality traits was least in Spanish genotypes, suggesting a relatively better tolerance of this group for water deficit stress.

Effect of mid season drought on phenolic compounds in peanut genotypes with different levels of resistance to drought

Drought is a major constraint in peanut production. Drought not only reduces pod yield but also may affect phenolic compounds in peanut. This experiment was conducted for two years under field conditions. Soil moisture levels (field capacity and mid season drought stress) were assigned as main plots, and five peanut genotypes were assigned as sub plots. Peanut seeds were analyzed for phenolic compounds at harvest. Leaves and stems were also analyzed at 30 and 60 days after planting (DAP), and at harvest. Water regimes did not result in significant differences for phenolic compounds in seeds, whereas peanut genotypes were significantly different for this trait. Drought increased phenolic contents in leaves at 60 DAP and phenolic contents were reduced during the recovery period. The production of leaf phenolic compounds differed among genotypes. Mid season drought increased phenolic compounds in stems during the drought period and levels of phenolic production were different depending on peanut genotype. Breeding for high phenolic content and drought tolerance in peanut should be possible because mid season drought did not affect phenolic content in seeds.