Agricultural Production Strategies Research Articles

The combination of Neosartorya (Aspergillus) fischeri antifungal proteins with rationally designed \u03b3-core peptide derivatives is effective for plant and crop protection

Plant pathogenic fungi are responsible for enormous crop losses worldwide. Overcoming this problem is challenging as these fungi can be highly resistant to approved chemical fungicides. There is thus a need to develop and introduce fundamentally new plant and crop protection strategies for sustainable agricultural production. Highly stable extracellular antifungal proteins (AFPs) and their rationally designed peptide derivatives (PDs) constitute feasible options to meet this challenge. In the present study, their potential for topical application to protect plants and crops as combinatorial biofungicides is supported by the investigation of two Neosartorya (Aspergillus) fischeri AFPs (NFAP and NFAP2) and their γ-core PDs. Previously, the biofungicidal potential of NFAP, its rationally designed γ-core PD (γNFAP-opt), and NFAP2 was reported. Susceptibility tests in the present study extended the in vitro antifungal spectrum of NFAP2 and its γ-core PD (γNFAP2-opt) to Botrytis, Cladosporium, and Fusarium spp. Besides, in vitro additive or indifferent interactions, and synergism were observed when NFAP or NFAP2 was applied in combination with γNFAP-opt. Except for γNFAP2-opt, the investigated proteins and peptides did not show any toxicity to tomato plant leaves. The application of NFAP in combination with γNFAP-opt effectively inhibited conidial germination, biofilm formation, and hyphal extension of the necrotrophic mold Botrytis cinerea on tomato plant leaves. However, the same combination only partially impeded the B. cinerea-mediated decay of tomato fruits, but mitigated the symptoms. Our results highlight the feasibility of using the combination of AFP and PD as biofungicide for the fungal infection control in plants and crops.

A perspective for advancing climate prediction services in Brazil

AbstractThe Climate Science for Service Partnership Brazil (CSSP‐Brazil) project provides Brazil and UK partners the opportunity to address important challenges faced by the climate modeling community, including the need to develop subseasonal and seasonal prediction and climate projection services. This paper provides an overview of the climate modeling and prediction research conducted through CSSP‐Brazil within the context of a framework to advance climate prediction services in Brazil that includes a research‐to‐services (R2S) and a services‐to‐research (S2R) feedback pathway. The paper also highlights plans to advance scientific understanding and capability to produce beneficial climate knowledge and new products to improve climate prediction services to support decisions in various industries in Brazil. Policy‐relevant outcomes from climate modeling and prediction exercises illustrated in this paper include supporting stakeholders with climate information provided from weeks to months ahead for (a) improving water management strategies for human consumption, navigation, and agricultural and electricity production; (b) defining crop variety and calendars for food production; and (c) diversifying energy production with alternatives to hydropower.

Evaluating environmental and economic trade-offs in cattle feed strategies using multiobjective optimization

CONTEXTReducing livestock greenhouse gas (GHG) emissions is now central to sustainable agricultural production strategies. Feedlot systems are a significant part of the production process in many countries, and associated feeding plans can influence product emission intensity significantly. Feed formulation can be used to target several objectives including animal productive performance, direct emissions from enteric fermentation and manure decomposition, and pre-farm gate emissions associated with the feed life cycles. OBJECTIVETo explore the environmental and economic trade-offs in feed formulation for beef cattle using multiobjective optimization. METHODSWe develop a multiobjective model to derive the efficient frontier between profit maximization and environmental impact minimization in diet formulation for beef cattle in a typical French feedlot system. The nonlinear profit function includes animal performance, animal selling price, and feeding costs. The environmental impact accounts for the feed ingredient life cycles (non-renewable energy consumption, phosphorus demand, soil acidification, soil eutrophication, climate change potential, and land requirement), and for methane and nitrous oxide emissions from enteric fermentation and manure decomposition. The model is solved using a combination of optimization methods and for two scenarios with different weights representing the environmental impacts: a low carbon scenario (minimizing only CO2eq emissions), and a balanced impacts scenario (minimizing the sum of impacts with an arbitrary choice of weights derived from the literature). RESULTS AND CONCLUSIONSWe show that optimal cost-effective mitigation arises from a combined strategy, concurrently: increasing animal performance by 20% and reducing daily emissions from the feed life cycle by 50% and from enteric fermentation and manure decomposition emissions by 43%. With this strategy, both scenarios present similar maximum GHG reduction in the feedlot phase – around 42% compared to the maximum-profit solution. The similar behaviour of both scenarios shows that environmental impact transference only occurs in more extreme solutions. Finally, about 50% of the total potential reduction can be achieved at a cost of 22 € / kg CO2eq / kg CWE. SIGNIFICANCEResults suggest that significant GHG emissions reduction can be obtained solely from manipulating animal diets. Achieving these reductions cost-effectively derives from a combination of well-known strategies rather than focusing on any one individually.

Development of an Integrated Model to Assess the Impact of Agricultural Practices and Land Use on Agricultural Production in Morocco under Climate Stress over the Next Twenty Years

Climate change is one of the major risks facing developing countries in Africa for which agriculture is a predominant part in the economy. Alterations in rainfall patterns and increasing temperatures projected by the Intergovernmental Panel on Climate Change (IPCC) could lead to a decline in agricultural production in many areas requiring significant changes in agricultural practices and land distribution. The study provided estimates of the economic impacts of climate change, compared these with historical impacts of drought spells, and estimated the extent to which the current Moroccan agricultural development and investment strategy, the Plan Maroc Vert, helps in agricultural adaptation to climate change and uncertainty. The aim of this study was to quantify the effects of climate change on the overall economy by using an integrated framework incorporating a computable general equilibrium model. A concomitant factor to climate change will be the increase in population and its distribution and level of consumption, which will also influence agricultural production strategies, the conversion of agricultural land, the type of irrigation, and technological development. We demonstrated how changes in cereal production and area, affluence, and climate (rainfall and temperature) can be acquired for 12 regions of Morocco and used to develop and validate an earth system model in relation to the environment and socio-economic level, which projects their impact on current and potential land use over the next 20 years. We used different mathematical equations based on cereal area and production, population, consumption (kg/person), and change in climate (temperature and rainfall) in bour and irrigated areas for the growing season of 2014 in 12 regions to project agricultural land use over the next 20 years. Therefore, several possible scenarios were investigated to explore how variations in climate change, socio-economic level, and technological development will affect the future of agricultural land use over the next 20 years, which in turn could have important implications for human well-being. Among the 12 Moroccan regions, only 4 had a surplus of cereal production compared to their local consumption. The increase in population will generate a cereal deficit in 2024 and 2034, thus lowering the average annual quantity available per capita of cereals from 204.75 to 160.61 kg/p in 2014 and 2034, respectively. Therefore, it is necessary to reduce the amount of cereals per person by 5 kg/p and 25 kg/p so that the 2014 production could satisfy the population projected in 2024 and 2034. We found that cereal production will decrease with increasing temperature and decreasing precipitation according to the simulated scenarios, which might not satisfy the growing population in 2024 and 2034. This study provides a practical tool that can be used to provide policy makers with advice on food security assurance policy based on our current knowledge of the impending onset of climate change, including socio-economic statistics and the agricultural constraints of cereals in the 12 regions of Morocco.

Simulating the Capacity of Rainfed Food Crop Species to Meet Social Demands in Sudanian Savanna Agro-Ecologies

West African land use systems have been experiencing one of the fastest transformations in the world over recent decades. The Sudanian savanna is an interesting example, as it hosts the cultivation of some crops typical of the Guinean savanna as well as some of the Sahel. Therefore, this region is likely to experience further changes in its crop portfolio over the next decades due to crop migration processes responding to environmental change. Simulation approaches can guide the development of agricultural production strategies that contribute to sustainably optimize both food and fuel production. This study used crop models already available in the APSIM platform to simulate plant production and the soil water and nutrient cycles of plots cultivated with groundnut, millet, sorghum, maize, and rice on three (two upland and one lowland) soil fertility classes and subjected to five levels of management (conventional tillage without residue incorporated to the soil and nor fertilizer application; conventional tillage without residue incorporated to the soil and 5 kg N ha−1; conventional tillage with residue incorporated to the soil 20 kg N ha−1, and no-till herbicide treated with 50 and 100 kg N ha−1). Simulation outputs were contrasted against data reported in the literature and converted into nutritional, fuel and feed yields based on the qualities and uses of their different plant comparments. Groundnut yields outperformed all of the cereals across most growing conditions, nutritional and feed indicators. Maize and rice provided the highest caloric yields, with the least fertile growing conditions. Sorghum provided average to high caloric and iron yields across all of the treatments. Millet provided the highest iron yields and high fuel yields across most treatments. Some simulated treatments could not be compared against literature review data because of their absence in actual cropping systems and the lack of experimental data. Plant production was simulated with higher accuracy than the other components of the simulation. In particular, there is a need to better parameterize and validate the rice, groundnut and millet models under Sudanian savanna conditions in order to perform more accurate comparative assessments among species.

Solar Photovoltaic Architecture and Agronomic Management in Agrivoltaic System: A Review

Agrivoltaic systems (AVS) offer a symbiotic strategy for co-location sustainable renewable energy and agricultural production. This is particularly important in densely populated developing and developed countries, where renewable energy development is becoming more important; however, profitable farmland must be preserved. As emphasized in the Food-Energy-Water (FEW) nexus, AVS advancements should not only focus on energy management, but also agronomic management (crop and water management). Thus, we critically review the important factors that influence the decision of energy management (solar PV architecture) and agronomic management in AV systems. The outcomes show that solar PV architecture and agronomic management advancements are reliant on (1) solar radiation qualities in term of light intensity and photosynthetically activate radiation (PAR), (2) AVS categories such as energy-centric, agricultural-centric, and agricultural-energy-centric, and (3) shareholder perspective (especially farmers). Next, several adjustments for crop selection and management are needed due to light limitation, microclimate condition beneath the solar structure, and solar structure constraints. More importantly, a systematic irrigation system is required to prevent damage to the solar panel structure. To summarize, AVS advancements should be carefully planned to ensure the goals of reducing reliance on non-renewable sources, mitigating global warming effects, and meeting the FEW initiatives.

Does it matter who gives information? The impact of information sources on farmers’ pesticide use in China

The timely delivery of scientific information regarding pesticide use to farmers is essential to address negative externalities. Farmers have four information sources regarding pesticide use in China: public agricultural extension agents (PAEAs), pesticide sellers, peer farmers, and farmers’ own experience. A better understanding of which information source is the most effective in reducing pesticide use would be a principal step toward designing policy strategies for sustainable agricultural production. In this study, we examine the relative effectiveness of each information source on farmers’ pesticide use, based on nationally representative data from 603 rice farmers in seven major rice-producing provinces in China. We adopt a multinomial endogenous switching regression model to correct for selection bias due to observed and unobserved factors. Results show that compared with farmers’ own experience, PAEAs significantly increase farmers’ pesticide expenditure by 8.7 %, while pesticide sellers and peer farmers significantly decrease farmers’ pesticide expenditure by 18.5 % and 10.1 % respectively, with the largest reduction coming from pesticide sellers. Discouraging PAEAs’ commercial activities, working with pesticide sellers, and using peer farmers as social multipliers to disseminate knowledge may be effective ways to develop education programs that aim to reduce pesticide use.

Bacillus strains immobilized in alginate macrobeads enhance drought stress adaptation of Guinea grass

Drought stress reduces crop growth and yield. This study aimed to formulate alginate macrobeads inoculants using strains Bacillus sp. XT13 and XT14, and evaluate their effect on the stress response of guinea grass under drought. First, we produced two prototypes per bacterial strain based on the alginate-bacterial broth ratio and selected one for each strain based on the release kinetics and the biodegradability of the formulates in soil. Then, we evaluated their effect on some biochemical, morphological, and nutritional responses of Guinea grass under drought in greenhouse conditions. The results showed a biodegradability increase and a slow-release rate for the prototypes 70:30 XT13 and 80:20 XT14. The greenhouse experiments showed that inoculation of both Bacillus sp. strains improved plant growth significantly under drought. Furthermore, the co-inoculation of the alginate macrobeads of both strains showed a greater effect on the grass response than that observed with individual inoculations (p < 0.05). When compared with the drought control treatment, the co-inoculation increased plant total dry biomass production by 94.4% and nutritional quality parameters such as crude protein content (260%) and digestibility (10.73%). Co-inoculation also showed a significant effect (p < 0.05) in the plant's antioxidant response, as the ascorbate peroxidase activity decreased 5.46%. In contrast, proline accumulation increased in plants inoculated with the alginate macrobeads of XT13, XT14 and XT13 + XT14 by 3.1-fold, 3.3-fold and 2.3, respectively. Overall, our results suggest that formulation of macrobeads with these bacteria can modulate plants response to drought and have the potential to be a climate change adaptation strategy for agricultural production.

Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (Tmin and Tmax) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p &lt; 0.1). There was an increasing trend in Tmax at Kara, Mango and Niamtougou, unlike Dapaong where Tmax revealed a significant decreasing trend (p &lt; 0.01). Similarly, there was an increasing trend in Tmin at Kara, Mango and Dapaong, unlike Niamtougou where Tmin showed a non-significant decreasing trend (p &gt; 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). Tmax increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, Tmin increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

Impacts of COVID-19 on agriculture and food systems in Pacific Island countries (PICs): Evidence from communities in Fiji and Solomon Islands

CONTEXTCOVID-19 mitigation measures including border lockdowns, social distancing, de-urbanization and restricted movements have been enforced to reduce the risks of COVID-19 arriving and spreading across PICs. To reduce the negative impacts of COVID-19 mitigation measures, governments have put in place a number of interventions to sustain food and income security. Both mitigation measures and interventions have had a number of impacts on agricultural production, food systems and dietary diversity at the national and household levels. OBJECTIVEOur paper conducted an exploratory analysis of immediate impacts of both COVID-19 mitigation measures and interventions on households and communities in PICs. Our aim is to better understand the implications of COVID-19 for PICs and identify knowledge gaps requiring further research and policy attention. METHODSTo understand the impacts of COVID-19 mitigation measures and interventions on food systems and diets in PICs, 13 communities were studied in Fiji and Solomon Islands in July-August 2020. In these communities, 46 focus group discussions were carried out and 425 households were interviewed. Insights were also derived from a series of online discussion sessions with local experts of Pacific Island food and agricultural systems in August and September 2020. To complement these discussions, an online search was conducted for available literature. RESULTS AND CONCLUSIONSIdentified impacts include: 1) Reduced agricultural production, food availability and incomes due to a decline in local markets and loss of access to international markets; 2) Increased social conflict such as land disputes, theft of high-value crops and livestock, and environmental degradation resulting from urban-rural migration; 3) Reduced availability of seedlings, planting materials, equipment and labour in urban areas; 4) Reinvigoration of traditional food systems and local food production; and 5) Re-emergence of cultural safety networks and values, such as barter systems. Households in rural and urban communities appear to have responded positively to COVID-19 by increasing food production from home gardens, particularly root crops, vegetables and fruits. However, the limited diversity of agricultural production and decreased household incomes are reducing the already low dietary diversity score that existed pre-COVID-19 for households. SIGNIFICANCEThese findings have a number of implications for future policy and practice. Future interventions would benefit from being more inclusive of diverse partners, focusing on strengthening cultural and communal values, and taking a systemic and long-term perspective. COVID-19 has provided an opportunity to strengthen traditional food systems and re-evaluate, re-imagine and re-localize agricultural production strategies and approaches in PICs.

The variability of natural and climatic conditions in investment projects in the field of nature management

The article focuses on the actual scientific and practical problem of accounting for the influence of meteorological and climatic factors in the technical and economic calculations in the field of environmental management. It has been proven that the introduction of scientifically sound and effective methods of using meteorological and cli-matic information in economic calculations significantly reduces the loss caused by weather conditions and improves the implementation of an optimal strategy for agricultural production on reclaimed lands. Such calculations are based on economic and statistical modelling of different variants that accounting for standard hy-drometeorological information in the implementation of design, management and economic decisions. This increases the validity and reliability of calculations, as well as their compliance with the actual operating conditions of environmental and economic facilities. Consequently, this attracts increased interest of both public and private investors. Not only under such conditions is a sustainable development of environmental management sectors possible but also the adaptation to global climate change and additional benefits from the efficient economic activity in the new environmen-tal conditions.

Origins of Farmers’ Adoption of Multiple Climate-Smart Agriculture Management Practices in the Vietnamese Mekong Delta

Farmers’ adoption of multiple climate-smart agricultural practices may guarantee food security and economic and social efficiency considering the adverse effects of climate change. This study investigates the adoption of climate-smart agricultural technologies among farmers in the Mekong Delta, Vietnam. The analysis used a primary data sample of 350 rice farmers and a multinomial logit model. The findings indicate that the most critical determinants of climate-smart agricultural technology adoption among farmers include perceived impact of climate change, farmer’s education level, farm size, access to credit, social capital, access to extension, secured farmland tenure, and constraint to market. The results demonstrate the need for policymaking designed to improve the probability of households applying climate-smart agricultural technology as the most crucial step in successfully implementing adaptive agricultural production strategies to climate change.

A new strategy using nanoscale zero-valent iron to simultaneously promote remediation and safe crop production in contaminated soil.

Novel versatile nanomaterials may facilitate strategies for simultaneous soil remediation and agricultural production, but a thorough and mechanistic assessment of efficacy and safety is needed. We have established a new soil remediation strategy using nanoscale zero-valent iron (nZVI) coupled with safe rice production in paddy soil contaminated with pentachlorophenol (PCP). In comparison with rice cultivation in contaminated soil with 100 mg PCP per kg soil but without nZVI, the addition of 100 mg nZVI per kg soil increased grain yield by 47.1-55.0%, decreased grain PCP content by 83.6-86.2% and increased the soil PCP removal rate from 49.9 to 83.9-89.0%. The specific role of nZVI-derived root iron plaque formation in the safe production of rice has been elucidated, and the synergistic effect of nZVI treatment and rice cultivation identified in the nZVI-facilitated rhizosphere microbial degradation of PCP. This work opens a new strategy for the application of nanomaterials in soil remediation that could simultaneously enable safe crop production in contaminated lands.

Assessment of rice yield gap under a changing climate in India

Abstract Climate change evokes future food security concerns and needs for sustainable intensification of agriculture. The explicit knowledge about crop yield gap at country level may help in identifying management strategies for sustainable agricultural production to meet future food demand. In this study, we assessed the rice yield gap under projected climate change scenario in India at 0.25° × 0.25° spatial resolution by using the Decision Support System for Agrotechnology Transfer (DSSAT) model. The simulated spatial yield results show that mean actual yield under rainfed conditions (Ya) will reduce from 2.13 t/ha in historical period 1981–2005 to 1.67 t/ha during the 2030s (2016–2040) and 2040s (2026–2050), respectively, under the RCP 8.5 scenario. On the other hand, mean rainfed yield gap shows no change (≈1.49 t/ha) in the future. Temporal analysis of yield indicates that Ya is expected to decrease in the considerably large portion of the study area (30–60%) under expected future climate conditions. As a result, yield gap is expected to either stagnate or increase in 50.6 and 48.7% of the study area during the two future periods, respectively. The research outcome indicates the need for identifying plausible best management strategies to reduce the yield gap under expected future climate conditions for sustainable rice production in India.

Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (Tmin and Tmax) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p &lt; 0.1). There was an increasing trend in Tmax at Kara, Mango and Niamtougou, unlike Dapaong where Tmax revealed a significant decreasing trend (p &lt; 0.01). Similarly, there was an increasing trend in Tmin at Kara, Mango and Dapaong, unlike Niamtougou where Tmin showed a non-significant decreasing trend (p &gt; 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). Tmax increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, Tmin increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

Agricultural production strategies: world experience

Agricultural production strategies: world experience

Adaptive farm management in the context of the expansion of industrial tree plantations in northern Argentina

Landscape reconversion by plantation-oriented forestry is associated with transformations in regional economic systems. Under such change, rural communities develop different environmental and economic management strategies. Due to forest plantation growth since the 1970's in Misiones, Argentina, different areas of production can be identified according to the intensity of the forestry management model carried out. Each area defines a forestry productive landscape in which local rural populations are immersed. In this study, we describe and analyse the agricultural production strategies of Colonos (settlers) according to the size of industrial tree plantations. We offer insights into the construction of an adaptive, agrobiodiverse strategy in the context of the dominant forestry industry. Considering historical processes and current land use, we expected to find less diversity and overall development of the family productive system among rural families living in more homogenized, plantation-dominated landscapes. Qualitative and quantitative data was gathered to assess the agricultural richness and producers´ related production management. Departing from the idea that the homogenization of the landscape diminishes the diversification of the family productive system, we found that families have been able to shape the components of their subsistence in complex environments. In other words, in the face of change and instability, Colono farmers were able to reconfigure and incorporate diverse agricultural strategies. Also, they engage in biologically diverse farming systems and provide ecological heterogeneity to a regional landscape deeply transformed by tree plantations.

Saberes locales sobre tecnologías y estrategias de producción agropecuaria para la resiliencia climática

The research was carried out in the 2017-2018 agricultural cycle, in four characteristic communities of the Municipality of Toledo of the Oruro department of the Plurinational State of Bolivia. The objective was to identify local knowledge about agricultural production technologies and strategies that can generate sustainability in agricultural production systems to strengthen the resilience of Climate Change. The approach used was logical cultural historical research, participatory revalu-ative research. According to the results, it was possible to identify 10 agricultural production technologies used with the highest frequency, of which are used by the producers with the highest incidence (100%) is the wijina (conical deposit dug in the ground to accumulate rainwater), followed by because it has a preference for 79.3% of producers, the kurmi khotas (traps to harvest rainwater) that only 16.6% of producers use. From these technologies grouped into 4 CC-resistant agricul-tural production strategies, it is evident that the Rainwater management plan and the management and management of native pastures and forage species introduced by those that the producer approves in their production systems.

Evaluation of water demand and supply under varying meteorological conditions in Eastern India and mitigation strategies for sustainable agricultural production

Spatio-temporal variability of water demand and supplies under different meteorological conditions and their linkage with dynamic groundwater (annually utilizable groundwater) reserve was investigated in a Canal Command (area irrigated by a canal system) of Eastern India. Annual irrigation water supply from surface water sources (i.e., canal, river lift and tanks) and groundwater sources (i.e., shallow and deep tubewells) was estimated for different meteorological conditions. Annual water demands as crop irrigation requirements (CIRs) for the prevailing cropping patterns in the study area were also assessed under different meteorological conditions using crop evapotranspiration and effective rainfall data. Thereafter, the estimated irrigation water supply and irrigation water demand were subjected to spatio-temporal and statistical analyses. The mean annual CIR in the study area was estimated at 7002 ± 852 MCM during 2004–2013 period. Boro paddy was found to be the most water-consuming crop, accounting for about 50% of the total crop water requirements. The mean annual dynamic groundwater reserve (DGWR) in the study area was estimated to be 5169 ± 782 MCM. Considering DGWR as an additional source of irrigation water, 28, 25 and 35 blocks were characterized as ‘water surplus’ during ‘normal,’ ‘dry’ and ‘wet’ years, respectively. Also, DGWR substantially reduced demand–supply gaps in the remaining blocks. The surplus water available in the blocks due to DGWR availability could be used to mitigate water-deficit condition in neighboring blocks. Thus, this study suggests cost-effective alternatives for the efficient management of available water resources and identifies management strategies for sustainable agricultural production under diverse climatic conditions.

Machine learning to predict biomass sorghum yields under future climate scenarios

AbstractCrop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near‐term and long‐term pathways for scaling up bio‐based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. We used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. © 2020 Society of Chemical Industry and John Wiley &amp; Sons, Ltd