Assessment of on-farm, market and wild food diversity in three agro-ecological zones of Western Kenya

Poster presented at Tropentag 2014. International Conference on Research on Food Security, Natural Resource Management and Rural Development. "Bridging the Gap between Increasing Knowledge and Decreasing Resources" Prague (Czech Republic) Sep 17-19 2014

Estimation of Soil Moisture in Bare Soils of the Northern Dry Zone of the Deccan Plateau, Karnataka, using Sentinel-1 Band C imagery

Soil moisture information is acritical input to water resource allocation, irrigation scheduling and climate risk management.The date of sowing is an important decision farmers take after initial rainfall occurs based on traditional knowledge and physical estimation of soil moisture. The present study was conducted on bare agriculture fields of Siruguppasub-district in Karnataka state in India to estimate surface soil moisture us in gradar remote sensing with the aim of developing an accurate and scalable methodology

Integrated systems approach for enhancing resilience of arid farming systems in South Asia

This paper aims to share the methods and processes of designing resilient farming systems to improve livelihoods under the drylands in South-Asia. The study is based on 250 randomly selected farm households along the rainfall gradient from Jodhpur- Barmer-Jaisalmer districts in Western Rajasthan in India. Our analysis demonstrates that the dryland smallholder farming systems occur within diverse agro-ecological and socio-economic environments and develop different livelihood strategies driven by opportunities and constraints encountered. Multiple livelihood assets determine different land use patterns and agricultural management practices in dryland systems in south Asia. Well-designed household survey on socio-economic and agroecological variables and statistical approach helped capture the diversity of livelihood assets to categorize households into homogenous farm types. The follow up FDG’s with farmers and stakeholder were equally important to validate farm typologies and prioritization of interventions. Engaging the innovation platform for identification of potential innovation options and their prioritization at district level; involving farmers for each farm typology, and ex-ante assessment of promising options led to the on-farm assessment of farm type specific most appropriate interventions in the action villages. Landscape and community level options were prioritized with the village development committee and proactive farmers. The institutional platforms experimented at village to regional level has strengthened the capacity of the community/stakeholders to innovate to improve the farming systems resilience and economic viability. An ex-post assessment demonstrates significant increase in farming systems productivity, household income and development of value chains as well as sustainable management of natural resource including common pastures. This study contributes to the understanding of how research for development through integrated systems approach can contribute towards stabilizing farm incomes, sustainable intensification and smoothening livelihood of resource poor farmers in vulnerable dry regions

Accuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data

This study describes a semi-empirical model developed to estimate volumetric soil moisture ( v ϑ) in bare soils during the dry season (March–May) using C-band (5.42 GHz) synthetic aperture radar (SAR) imagery acquired from the Sentinel-1 European satellite platform at a 20 m spatial resolution. The semi-empirical model was developed using backscatter coefficient (σ° dB) and in situ soil moisture collected from Siruguppa taluk (sub-district) in the Karnataka state of India. The backscatter coefficients 0 VV σ and 0 VH σ were extracted from SAR images at 62 geo-referenced locations where ground sampling and volumetric soil moisture were measured at a 10 cm (0–10 cm) depth using a soil core sampler and a standard gravimetric method during the dry months (March–May) of 2017 and 2018. A linear equation was proposed by combining 0 VV σ and 0 VH σ to estimate soil moisture. Both localized and generalized linear models were derived. Thirty-nine localized linear models were obtained using the 13 Sentinel-1 images used in this study, considering each polarimetric channel Co-Polarization (VV) and Cross-Polarization(VH) separately, and also their linear combination of VV + VH. Furthermore, nine generalized linear models were derived using all the Sentinel-1 images acquired in 2017 and 2018; three generalized models were derived by combining the two years (2017 and 2018) for each polarimetric channel; and three more models were derived for the linear combination of 0 VV σ and 0 VH σ . The above set of equations were validated and the Root Mean Square Error (RMSE) was 0.030 and 0.030 for 2017 and 2018, respectively, and 0.02 for the combined years of 2017 and 2018. Both localized and generalized models were compared with in situ data. Both kind of models revealed that the linear combination of 0 VV σ + 0 VH σ showed a significantly higher R2 than the individual polarimetric channels

Understanding the response of sorghum cultivars to nitrogen applications in the semi-arid Nigeria using the agricultural production systems simulator

The Agricultural Production Systems simulator (APSIM) model was calibrated and evaluated using two improved sorghum varieties conducted in an experiment designed in a randomized complete block, 2014–2016 at two research stations in Nigeria. The results show that the model replicated the observed yield accounting for yield differences and variations in phenological development between the two sorghum cultivars. For early-maturing cultivar (ICSV-400), the model indicated by low accuracy with root means square error (RMSE) for biomass and grain yields of 20.3% and 23.7%. Meanwhile, Improved-Deko (medium-maturing) cultivar shows the model was calibrated with low RMSE (11.1% for biomass and 13.9% for grain). Also, the model captured yield response to varying Nitrogen (N) fertilizer applications in the three agroecological zones simulated. The N-fertilizer increased simulated grain yield by 26–52% for ICSV-400 and 19–50% for Improved-Deko compared to unfertilized treatment in Sudano-Sahelian zone. The insignificant yield differences between N-fertilizer rates of 60 and 100 kgha−1 suggests 60 kgNha−1 as the optimal rate for Sudano-Sahelian zone. Similarly, grain yield increased by 23–57% for ICSV-400 and 19–59% for Improved Deko compared to unfertilized N-treatment while the optimal mean grain yield was simulated at 80 kgNha−1 in the Sudan savanna zone. In the northern Guinea savanna, mean simulated grain yield increased by 8–20% for ICSV-400 and 12–23% for Improved-Deko when N-fertilizer was applied compared to unfertilized treatment. Optimum grain yield was obtained at 40 kgha−1. Our study suggests a review of blanket recommended fertilizer rates across semi-arid environments for sorghum to maximize productivity and eliminate fertilizer losses, means of adaptation strategies to climate variability

Simulation of Lablab Pastures

The potential of legume-based pastures to address declining soil nitrogen on marginal cropping soils is increasingly recognised in northern Australia, as such there is a need for cost benefit analysis of pastures and crops in a mixed farming system. In highly variable rainfall environments, biophysical modelling may be the best way of identifying and quantifying interactions with mixed crop-livestock systems on a seasonal basis. This paper describes a case study where both animal productivity and lablab pasture production is simulated. Lablab (Lablab purpureus) is an annual tropical legume widely used as a short-term legume phase in crop-pasture rotations, providing high quality forage for animal production and a low risk nitrogen input for crop production

Climate risk, vulnerability and resilience: Supporting livelihood of smallholders in semiarid India

Using panel data from 256 smallholder households from 2006 to 2014 in three semiarid regions India, this study develops a framework for quantifying vulnerability and resilience by accounting for a smallholder household’s ability to adapt and respond to climatic risk. Findings indicate that although smallholders with smaller landholdings are more vulnerable to climatic risk (drought, in our case), they are also more resilient than their counterparts. Results reveal that cropping intensity and crop risk increase the vulnerability of smallholders to climatic risk, but large farms are less vulnerable. Diversification in on-farm enterprises, like livestock units, and off-farm income sources, play significant roles in increasing smallholder households’ resilience to climatic risk. Other drivers of resiliency include the choice of cash and risky crops, borrowing capacity, liquid investments, and the ability to regain yields

Restoring degraded landscapes and fragile food systems in sub-Saharan Africa: synthesis of best practices

Communities in the dryland systems of East Africa regularly suffer from the devastating impacts of climate variability and change, commonly manifested through torrential floods and recurrent droughts. More than 50% of the natural disasters recorded in East African region have occurred during the past decade affecting nearly 30 million people. For instance, in Ethiopia as recently as 2017, more than 5.6 million people were categorized as being in either crisis or emergency situations and requiring urgent humanitarian assistance (WFP, 2017). Such communities, already struggling to cope with the impacts of unpredictable weather, will face a daunting task in adapting to future climate change unless they adapt improved landscape management practices

Indian agriculture: The route post-CoP 26

India’s pledge of Panchamrit (five-fold strategy) to fight climate change, announced during the 26th Conference of the Parties (CoP26) at Glasgow, Scotland, has caught global attention. The country’s new commitments include reaching 500 giga-watt (GW) of non-fossil fuel energy capacity by 2030; producing 50 per cent of energy requirements via renewable energy sources by 2030; a reduction of 1 billion tonnes of carbon by 2030; reducing the carbon emission intensity of the GDP by 45 per cent by 2030; and most importantly, achieving the target of net-zero emissions by 2070. A basket of agreements was signed by groups of countries during the Glasgow Summit. Here, we focus our discussions on agriculture and food systems and how India should prepare and act to fight the challenge of climate change in light of CoP26. As many as 26 countries signed the Sustainable Agriculture Policy Action Agenda at the summit to set a course of action to protect food systems and prevent loss of biodiversity against climate change. The countries laid down their commitments with a pledge “to use land sustainably and put protection and restoration of nature at the heart of all”. India did not sign the agenda as its Mission for Sustainable Agriculture (NMSA), one of the missions within the National Action Plan on Climate Change (NAPCC), is already operational to deal with the issue of climate change in the agriculture sector. At the present inflection point, when the agricultural sector in these countries, and for that matter across the planet, is threatened by the adversities brought by climate change, these initiatives seem to be a good way to reinvigorate efforts to promote and practice sustainable agriculture technologies. While Indian agriculture is adversely impacted by the vicissitudes of climate change, the sector also is a significant contributor to greenhouse gas (GHG) emissions. As per the Third Biennial Update Report submitted by the Government of India in early 2021 to the United Nations Framework Convention on Climate Change (UNFCCC), the agriculture sector contributes 14 per cent of the total GHG emissions (energy 75.01 per cent; industrial process and product use 8 per cent; and waste 2.7 per cent, as per 2016 data). Within the sector, 54.6 per cent of GHG emissions were due to enteric fermentation, followed by 17.5 per cent from rice cultivation, 19.1 per cent from fertiliser applied to agricultural soils, 6.7 per cent from manure management, and 2.2 per cent due to field burning of agricultural residues. Therefore, effective mitigation measures and appropriate adaptation technologies must be taken to reduce GHG emissions from the agriculture sector. India’s approach has been a balancing act between growth and sustainability in its climate change policies and it is leading the developing nations to place agriculture in the ongoing negotiations. The National Mission on Sustainable Agriculture, as part of National Action Plan on Climate Change for more than a decade now, has focused to make Indian agriculture sustainable, considering likely risks arising from climate variability. The Indian Council of Agricultural Research and International Agricultural Research Centres of the CGIAR system (a France-headquartered public agricultural innovation network), including International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), have developed climate smart agricultural technologies and approaches to assist the agricultural sector to be less vulnerable to the adverse impacts of climate change