Future Food Demand Research Articles

Strip cropping increases yield and revenue: multi-year analysis of an organic system in the Netherlands

Intercropping is proposed as a promising strategy to meet future food demand while reducing agriculture’s environmental impact by re-diversifying agricultural fields. Strip cropping, a form of intercropping, has a potential to simultaneously deliver multiple ecosystem services including productivity, while facilitating management as strip width can be adjusted to the working width of available machines. While the yield performance of strip cropping systems is influenced by the interaction between neighboring crops, to date, empirical studies on the performance of various crop combinations in strip cropping systems are limited. Here we used three-year data (2020–2022) from a 64-ha organic strip cropping system in the Netherlands to (1) evaluate the effects of crop neighbors and strip cropping on yield and (2) explore if optimizing the allocation of crop neighbors in alternative strip cropping configurations can improve yield and revenue performances. We analyzed the edge effect and strip cropping effect on yield of six crops grown in strips, each neighboring a total of five crops. The yield data was then used to evaluate the performance of the current and alternative strip configurations in terms of LER and relative revenue. Results showed that except for the positive effect observed on potato when neighboring celeriac or broccoli, edge effects lacked statistical significance. Strip cropping effect varied per crop: positive for faba bean and parsnip, neutral for celeriac and potato, and negative for oat and onion. Analysis across crops showed an overall significant positive strip cropping effect on yield. These findings highlighted the value of analysis at the cropping system level in developing designs aimed at unlocking the potential of strip cropping. The positive but variable strip cropping effects observed in the current experimental design and the two alternative configurations suggests prioritizing an overall increased crop diversity over optimizing their spatial arrangement. While we demonstrated increased productivity with strip cropping, further research is needed to expand the database on optimal crop combinations, extending the evaluation beyond yield and revenue performances to facilitate broader adoption of strip cropping in the Netherlands and Western Europe.

Plant Factory Speed Breeding Significantly Shortens Rice Generation Time and Enhances Metabolic Diversity

Rice (Oryza sativa L.) plays a pivotal role in global food security, yet its breeding is constrained by its long generation time and seasonality. To enhance rice breeding efficiency and meet future food demands, we have developed a vertical hydroponic breeding system integrated with light-emitting diodes (LEDs) lighting in a closed plant factory (PF), which significantly accelerates rice growth and generation advancement. The results show that indica rice can be harvested as early as after 63 days of cultivation, a 50% reduction compared with field cultivation, enabling the annual harvesting of 5–6 generations within the PF. A hyperspectral imaging system (HSI) and attenuated total reflectance infrared (ATR-IR) spectroscopy were further employed to characterize the chemical composition of the PF- and field-cultivated rice. Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) revealed that, compared with the field-cultivated rice, the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites, such as isovitexin, succinic acid, and methylillicinone F. Overall, this study reveals the unique metabolic profile of PF-cultivated rice and highlights the potential of PFs to accelerate the breeding of crops such as rice, offering an innovative agricultural strategy to support food security in the face of global population growth and climate change.

Smart City Aquaculture: AI-Driven Fry Sorting and Identification Model

The development of smart agriculture has become a critical issue for the future of smart cities, with large-scale management of aquaculture posing numerous challenges. Particularly in the fish farming industry, producing single-sex fingerlings (especially male fingerlings) is crucial for enhancing rearing efficiency and could even provide key support in addressing future global food demands. However, traditional methods of manually selecting the gender of broodfish rely heavily on experienced technicians, are labor-intensive and time-consuming, and present significant bottlenecks in improving production efficiency, thus limiting the capacity and sustainable development potential of fish farms. In response to this situation, this study has developed an intelligent identification system based on the You Only Look Once (YOLO) artificial intelligence (AI) model, specifically designed for analyzing secondary sexual characteristics and gender screening in farmed fish. Through this system, farmers can quickly photograph the fish’s cloaca using a mobile phone, and AI technology is then used to perform real-time gender identification. The study involved two phases of training with different sample sets: in the first phase, the AI model was trained on a single batch of images with varying parameter conditions. In the second phase, additional sample data were introduced to improve generalization. The results of the study show that the system achieved an identification accuracy of over 95% even in complex farming environments, significantly reducing the labor costs and physical strain associated with traditional screening operations and greatly improving the production efficiency of breeding facilities. This research not only has the potential to overcome existing technological bottlenecks but also may become an essential tool for smart aquaculture. As the system continues to be refined, it is expected to be applicable across the entire life cycle management of fish, including gender screening during the growth phase, thereby enabling a more efficient production and management model. This not only provides an opportunity for technological upgrades in the aquaculture industry but also promotes the sustainable development of aquaculture. The smart aquaculture solution proposed in this study demonstrates the immense potential of applying AI technology to the aquaculture industry and offers strong support for global food security and the construction of smart cities.

Development and application of a nutritional quality model for life cycle assessment of protein-rich foods

Alternative protein sources (APSs) have emerged as a potentially healthy and, presumably, environmentally sustainable solution for meeting future food demand. Here we develop a new complex nutrient profile model to assess the nutritional quality of protein-rich foods, which, concurrently, allows to evaluate their environmental implications efficiently through the application of life cycle assessment (LCA). The development of the index was guided by the identification of priority nutrients in APSs and main deficiencies of similar models, which gave rise to the ‘quality Nutrient Rich Food 1.10.2’ (qNRF1.10.2). This model is the first nutrient profile system that combines various essential nutrients and a protein quality scoring system, namely Digestible Indispensable Amino Acid Score (DIAAS). From a nutritional perspective, its accuracy was proven and its application identified animal products as the most nutritionally complete food group, surpassing plant-based alternatives. However, when using the index as functional unit in LCA of protein-rich foods, we discovered that seeds, nuts, and mixtures of vegetable foods reported the lowest environmental impacts as a function of their nutrient density. Some exceptions were found for algae or insects, which performed worse than animal-derived foods in terms of resources consumption, or for cereals, which shown an important water deprivation potential. These results suggest that we should find a trade-off between the production of emerging and conventional foodstuffs, and that main environmental issues of each region should condition the location of production systems.

Revolutionizing Rice: The Synthesis of Nature's Evolution and Biotechnology in C4 Rice

Agriculture plays a fundamental role in meeting the essential needs of humanity, yet numerous factors continuously influence agricultural production and productivity. Over time, evolving agricultural practices have significantly increased yields of staple food crops, thereby enhancing global food security. However, as the world's population continues to grow, there is a pressing need to further augment crop yields. Historically, increases in yield were achieved by expanding cultivated land, but rapid industrialization and urbanization have diminished available agricultural land and depleted natural resources essential for farming. In response to these challenges, enhancing crop photosynthetic efficiency has emerged as a pivotal strategy. Photosynthesis, the process by which plants convert sunlight into energy, has been optimized in various crops through evolutionary and biotechnological approaches. One such innovation is the adaptation of the C4 photosynthetic pathway into C3 rice, a staple food for billions worldwide. The C4 pathway, found in several efficient crops like maize and sugarcane, enhances carbon dioxide uptake and reduces photorespiration, leading to improved water and nitrogen use efficiency. This review explores the integration of nature’s evolutionary principles with cutting-edge biotechnological advancements in the development of C4 rice. By introducing the C4 pathway into rice—a traditionally C3 plant—scientists aim to dramatically increase its productivity and resilience to environmental stressors. This transformative approach not only holds promise for meeting future food demands sustainably but also addresses the challenges posed by climate change and resource scarcity. Moreover, the review examines the scientific basis, technological innovations, and potential agricultural implications of implementing C4 rice. It highlights the collaborative efforts of researchers, agronomists, and biotechnologists worldwide in reimagining rice cultivation to secure global food supplies while minimizing environmental impact. Ultimately, the integration of C4 photosynthesis into rice represents a significant step forward in agricultural innovation, poised to redefine food production capabilities and enhance global food security in the face of escalating population growth and environmental change.

Sustainable future food demand: Integrating social, health, and environmental considerations in forecasting

Predicting future food demand and understanding its environmental and dietary ramifications are vital for ensuring food system sustainability in an equitable manner. Existing forecasting methods often overlook societal diversity and do not connect projected food demand with its socio-environmental implications. This paper introduces a framework for forecasting a nation's future food demand with considerations for socio-demographics and dietary preferences, along with potential dietary and environmental implications. Israeli household expenditure surveys spanning two decades (1997–2017) representing over 120,000 households were used to explore a series of potential food purchase scenarios for the period up to 2030 and the nutritional and environmental footprints of subgroups. These subgroups included small and large families, young couples, the elderly, and wealthy adult households. Three dietary scenarios based on expected socio-demographic changes were then examined: “Environmental,” “Healthy,” and “Mediterranean” scenarios. All examined scenarios predicted a surge in food demand by 18 to 22 % for the period of 2018–2030. The “business-as-usual” (BAU) scenario emphasizes the expected rise in the consumption of meat, oil products, and food outside the home, leading to a 20 % rise in greenhouse gas emissions. In comparison, in the case of the Healthy scenario, emissions are expected to rise by 22 %, and according to the Environmental scenario by only 10 %. Significant differences were also discovered across various social groups in regard to the analyzed dietary and environmental indicators. Although the study focuses on Israel, the proposed framework's universality makes it adaptable to any country. This could empower policymakers and stakeholders to craft food security informed decisions and targeted interventions that address the needs of diverse social groups while considering socio-environmental implications both presently and in the future.

The Long-Term Agroecosystem Research cropland common experiment at Northern Plains.

Cropland agriculture in the northern Great Plains is challenged by variable weather, agricultural intensification, and competing use for energy development. Innovative cropland practices that address these challenges are needed to ensure regional agriculture can sustainably meet future food, fuel, and fiber demand. In response to this need, the Northern Plains Long-Term Agroecosystem Research Network site established a cropland experiment in 2019 that contrasts prevailing and alternative practices at plot and field scales over a proposed 30-year time frame. The experimental site is located on the Area IV Soil Conservation Districts Cooperative Research Farm near Mandan, ND. Cropping practices for the first 6 years of the experiment were developed with input from stakeholders and include a 3-year crop rotation of spring wheat (Triticum aestivum L.), corn (Zea mays L.), and soybean (Glycine max L.) with cover crops (alternative practice) and without (prevailing practice). The prevailing practice also involves the removal of crop residue, while a second alternative practice of perennial forages is included in the plot-scale experiment. Biophysical measurements are made at both spatial scales at frequencies aligned with approved methods for each agronomic and environmental metric. Findings from the first 6 years of the experiment will help identify tradeoffs associated with cover crop use and residue removal in dryland cropping systems. In the future, the experiment will adopt a knowledge co-production approach whereby researchers and stakeholders will work collaboratively to identify problems, implement research, and interpret results.

A comprehensive analysis of food insecurity in the drought-prone rural areas of Tigray.

The number of globally food-insecure people is increasing since 2017. Sub-Saharan Africa has the highest proportion of severely food-insecure people in the world. Tigray region of Ethiopia is one of the food-insecure regions, which, over the past many decades has been affected by recurrent food insecurities. In the drought-prone rural areas of Tigray, many people are living under the condition of chronic hunger. Proper food security studies are vital for proper intervention mechanisms. Yet, previous food security studies have rarely addressed the four pillars of food security: availability, access, utilization, and stability. In this study, all components are duly considered to assess the food insecurity status in the drought-prone rural areas of Tigray, Ethiopia. Of the 34 rural districts in Tigray, 363 households from three drought-prone rural districts were studied. Household Food Insecurity Access Scale and Food Insecurity Experience Scale were adapted to measure the food availability, access to food, and stability components of food security; and, Household Dietary Diversity Score (HDDS), Food Consumption Score (FCS), mid-upper arm circumference, and Bitot's spot were used to analyze the food utilization aspect. Findings show that 68% of the studied community frequently ate less food than they felt they needed and 82.1% of the households have experienced hunger because of lack of food. The study rural districts were unconnected to road networks; hence, 87.9% of the elderly and 20.4% of the women and girls had no access to food markets. Regarding the food utilization, 81.5% of the studied households had poor FCS; and the average HDDS and FCS for the study areas were 2.47 and 18.9, respectively. The prevalence of Global acute malnutrition, severe acute malnutrition (SAM), and moderate acute malnutrition (MAM) for 6-59months of age children in the study areas were 50.3, 4.2, and 46.1%, respectively. More notably, the prevalence of SAM for children from the food-insecure households was 21.2%. The prevalence of MAM for pregnant and lactating women (PLW) in the study areas was 59.5. Further, the prevalence of Bitot's spot among 6-59months of age children was 1.9%. On the other hand, all the rural households had anxiety about their future food demands. The rural households living in the studied areas were critically food-insecure. All the measurements implied that the food insecurity situation in the study areas was unacceptably worrisome and life-threatening. This calls for an instant action to avert the occurrence of famine and starvation in the drought-prone rural areas of Tigray region. Thus, interventions should primarily target the vulnerable rural people and need to be planned based on attaining food availability first rather than concurrently addressing all components of food security. Further, due emphasis should be given to diversifying livelihood strategies of the vulnerable villagers.

Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply–demand gap?

With rising demand for food and the threats posed by climate change, The Gambia faces significant challenges in ensuring sufficient and nutritious food for its population. To address these challenges, there is a need to increase domestic food production while limiting deforestation and land degradation. In this study, we modified the FABLE Calculator, a food and land-use system model, to focus on The Gambia to simulate scenarios for future food demand and increasing domestic food production. We considered the impacts of climate change on crops, the adoption of climate change adaptation techniques, as well as the potential of enhanced fertiliser use and irrigation to boost crop productivity, and assessed whether these measures would be sufficient to meet the projected increase in food demand. Our results indicate that domestic food production on existing cropland will not be sufficient to meet national food demand by 2050, leading to a significant supply–demand gap. However, investments in fertiliser availability and the development of sustainable irrigation infrastructure, coupled with climate change adaptation strategies like the adoption of climate-resilient crop varieties and optimised planting dates, could halve this gap. Addressing the remaining gap will require additional strategies, such as increasing imports, expanding cropland, or prioritising the production of domestic food crops over export crops. Given the critical role imports play in The Gambia’s food supply, it is essential to ensure a robust flow of food imports by diversifying partners and addressing regional trade barriers. Our study highlights the urgent need for sustained investment and policy support to enhance domestic food production and food imports to secure sufficient and healthy food supplies amidst growing demand and climate change challenges.

Microplastics in seafood: Consumer preferences and valuation for mitigation technologies

Microplastics, an emerging pollutant, have garnered widespread attention due to potential repercussions on human health and the environment. Given the critical role of seafood in food security, growing concerns about microplastics might be detrimental to meeting future global food demand. This study employed a discrete choice experiment to investigate Chilean consumers’ preferences for technology aimed at mitigating microplastic levels in mussels. Using a between-subjects design with information treatments, we examined the impact of informing consumers about potential human health and environmental effects linked to microplastics pollution on their valuation for the technology. We found that the information treatments increased consumers’ willingness to pay for mussels. Specifically, consumers were willing to pay a premium of around US$ 4 for 250 g of mussel meat with a 90 % depuration efficiency certification. The provision of health impact information increased the price premium by 56 %, while the provision of environmental information increased it by 21 %. Furthermore, combined health and environmental information significantly increased the probability of non-purchasing behavior by 22.8 % and the risk perception of microplastics for human health by 5.8 %. These results emphasized the critical role of information in shaping consumer preferences and provided evidence for validating investment in research and development related to microplastic pollution mitigation measures.

Molecular profiling of rice (Oryza sativa L.) genotypes using trait-based SNP markers linked to yield under drought condition

Drought is one of the major abiotic stress factors affecting the growth and production of rice globally and it can cause an estimated yield loss up to 90% in rice. With the increasing population around the globe, a comprehensive approach for mitigating drought stress should be taken to develop drought-tolerant rice varieties to meet future food demands. One hundred and eighty-two rice genotypes were evaluated for six critical gene/QTLs associated with drought tolerance using SNP marker data. The results revealed that 172 genotypes carry at least one gene/QTL for drought tolerance. The six gene/QTLs, namely, DTY1.1, qDTY2.2, qDTY3.1, qDTY3.2, qDTY4.1 and qDTY12.1were found in 103, 26, 90, 25, 27 and 45 genotypes corresponding to 57, 49, 14, 14, 15 and 25% of the total screened genotypes, respectively. Remarkably, five genotypes (RL-32, RL-105, RL-110, RL-142 and RL-158) possessed a unique combination three major genes/QTLs and three genotypes (RL-21, RL-41 and RL-188) possessed a unique combination four major gene/QTLs for drought tolerance. Furthermore, both cluster and populationn structure analyses revealedd the distribution of the genotypes into two major clusters. The genotypes carrying valuable gene/QTLs either in single or combination, hold immense potential for deployment in drought tolerance rice breeding programs.

Harnessing the potential of mutation breeding, CRISPR genome editing, and beyond for sustainable agriculture.

By 2050, the global population is projected to exceed 9.5 billion, posing a formidable challenge to ensure food security worldwide. To address this pressing issue, mutation breeding in horticultural crops, utilizing physical or chemical methods, has emerged as a promising biotechnological strategy. However, the efficacy of these mutagens can be influenced by various factors, including biological and environmental variables, as well as targeted plant materials. This review highlights the global challenges related to food security and explores the potential of mutation breeding as an indispensable biotechnological tool in overcoming food insecurity. This review also covers the emergence of CRISPR-Cas9, a breakthrough technology offering precise genome editing for the development of high-yield, stress-tolerant crops. Together, mutation breeding and CRISPR can potentially address future food demands. This review focuses into these biotechnological advancements, emphasizing their combined potential to fortify global food security in the face of a booming population.

Long-term croplands water productivity in response to management and climate in the Western US Corn Belt

Global population growth and water scarcity are raising concerns about agricultural systems' ability to meet future food, fuel, feed, and fiber demands. Water productivity (WP), the ratio of crop production to water use, is crucial for assessing agricultural resilience and sustainability. Yet, research on WP often lacks long-term observational data to understand the impact of management and climate variability. Long-term monitoring of crop yield and water use, using Eddy Covariance technique, allows for accurate assessment of crop performance and their response to climate change in major cropping systems. In this study, we used data collected over a 20-year period (2001–2020) to investigate the interannual variability in yield (Y), crop evapotranspiration (ET), and water productivity (WP, ratio of Y and ET), and their response to management and climate in three major cropping systems located in Eastern Nebraska: irrigated continuous maize, irrigated maize-soybean rotation, and rainfed maize-soybean rotation. Our results showed significant differences (p <0.05) in WP between irrigated and rainfed sites, mainly attributed to variations in Y rather than ET, while there was no significant effect of crop rotation on measured responses. WP was 18.4% higher in irrigated maize in rotation relative to the rainfed site. Water input (mm, sum of precipitation and irrigation) was the main management factor in rainfed maize WP (R=0.67, p = 0.05) and Y (R=0.79, p <0.05). Vapor pressure deficit was negatively correlated with Y in rainfed maize (R=−0.72, p <0.05) and therefore was considered a determinant in WP (R=−0.7, p <0.05). For soybean, soil water content had the highest correlations with Y and WP (irrigated: R=−0.77; rainfed: R=0.49, only significant in irrigated sites). These findings can aid in formulating strategies to enhance water productivity and resilience in the US Corn Belt.

Assessing consumer rationality during a pandemic: Panic buying behaviours and its association with online social media discourse

As an unprecedented, shared global experience in crisis, the Covid-19 pandemic witnessed unusual behaviours amongst populations. Large-scale panic buying was observed in numerous countries. Such behaviours can be detrimental to the population's wellbeing and societal functioning. As global pandemics are a relatively rare phenomenon in history, research examining panic buying behaviours during pandemics and actual panic buying behaviours has been scarce. Within the context of the Covid-19 pandemic, the prevalence of social media has made it possible to monitor panic buying discourse real-time. The present research aims to study the relationship between online public discourse and its relationship with abnormal surges in buying behaviours. We first examined Singapore residents' supermarket purchase patterns based on daily supermarket sales data during Covid-19 and investigated its relationship with parallel social media information on the internet. Analysis involving these two large-scale social media and supermarket datasets revealed distinct purchasing patterns for various types of products such as staple food items and home electronic products. While significant positive correlation was found between purchasing patterns of staple and long-lasting canned foods and online discourse, this was absent for items such as home appliances and entertainment products. The findings point to the potential role of social media data in predicting future abnormal food demand episodes, with implications on food security and crisis management.

AICropCAM: Deploying classification, segmentation, detection, and counting deep-learning models for crop monitoring on the edge

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing the full utilization of imaging sensors. This paper reported AICropCAM, a field-deployable imaging framework that integrated edge image processing, Internet of Things (IoT), and LoRaWAN for low-power, long-range communication. The core component of AICropCAM is a stack of four Deep Convolutional Neural Networks (DCNN) models running sequentially: CropClassiNet for crop type classification, CanopySegNet for canopy cover quantification, PlantCountNet for plant and weed counting, and InsectNet for insect identification. These DCNN models were trained and tested with >43,000 field crop images collected offline. AICropCAM was embodied on a distributed wireless sensor network with its sensor node consisting of an RGB camera for image acquisition, a Raspberry Pi 4B single-board computer for edge image processing, and an Arduino MKR1310 for LoRa communication and power management. Our testing showed that the time to run the DCNN models ranged from 0.20 s for InsectNet to 20.20 s for CanopySegNet, and power consumption ranged from 3.68 W for InsectNet to 5.83 W for CanopySegNet. The classification model CropClassiNet reported 94.5 % accuracy, and the segmentation model CanopySegNet reported 92.83 % accuracy. The two object detection models PlantCountNet and InsectNet reported mean average precision of 0.69 and 0.02 for the test images. Predictions from the DCNN models were transmitted to the ThingSpeak IoT platform for visualization and analytics. We concluded that AICropCAM successfully implemented image processing on the edge, drastically reduced the amount of data being transmitted, and could satisfy the real-time need for decision-making in PA. AICropCAM can be deployed on moving platforms such as center pivots or drones to increase its spatial coverage and resolution to support crop monitoring and field operations.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean.

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

Outside-in and bottom-up: Using sustainability transitions to understand the development phases of mainstreaming plant-based in the food sector in a meat and dairy focused economy

Humanity needs food system sustainability transitions to align future food demand with the planetary boundaries. This requires stakeholders and organisations to react to each other to change their position, strategies and practices. On the basis of niche-regime interactions in sustainability transitions, we explore the case of Denmark's plant-based food business sector development through 27 company case and expert interviews. We identify four development phases and a sequence in which the different environments of society, users, business, and policy contributed to the diffusion and mainstreaming of ‘plant-based’ in food. We find that the development is characterized by an outside-in and bottom-up direction, meaning that the original trigger came from the international level as well as the consumer demand. Businesses see their key internal success factors in the interplay of their organizational set-up, their product and technology, and their strategic choices. The plant-based market is characterized by changes in terms of increasing competition, a diversification of motives among the users, and marketing communication moving away from ‘vegan/vegetarian’ and towards appealing to the mainstream, flexitarian consumer. Results highlight the importance of change and collaboration among all environments, and the crucial role of the international level as a trigger for national developments.

A Study on Irrigation Water Productivity under Different Irrigation Environments of Tamil Nadu, India

The world is attempting to increase water efficiency in all activities, especially in irrigation, which consumes three-fourths of total available water. Concerning the near future food demand and sustainability issues, views are directed to reduce the usage of water or increase the efficiency of water use. India is a major contributor to the agricultural production and food supply to many countries. Irrigated agriculture is being followed by the many farmers in India which consumes huge amounts of water. Considering the monsoon failure and increased water demand, one must find solutions for retaining water in an available manner. The focus is on finding major water-consuming crops and irrigation methods under different irrigation environments of Tamil Nadu. Pudukottai, Salem and Erode are the districts of Tamil Nadu state selected as a study area. In each district, blocks, villages and respondents are selected through multi-stage random sampling. This study is entirely based on primary data which is collected using a well-structured interview schedule. The collected data is used to estimate the Physical Water Productivity (PWP) and Economic Water Productivity (EWP). The results show that PWP and EWP are variable across crops under different irrigation environments. In a tank environment, the alternate drying and wetting method of irrigation in paddy is effective and saves around 39 per cent of water compared to the conventional method by flooding. For Groundnut crops, drip irrigation is more effective than check basins which are better than the flood irrigation method. We can conclude that the farmers should follow water-saving irrigation methods/technologies and cultivate crops that show less demand for water during the season when the water is scarce and turn to cultivation of crops like sugarcane and banana in water surplus season.

Evolution of wheat architecture, physiology, and metabolism during domestication and further cultivation: Lessons for crop improvement

In recent decades, genetic advances in yield improvement in the major cereal crops, including wheat, has stagnated or proceeded at a slower rate than is required to meet future global food demand, particularly in the face of climate change. To reverse this situation, and in view of the future climate scenario, there is a need to increase the genetic diversity of wheat to increase its productivity, quality, stability, and adaptation to local agro-environments. The abundant genetic resources and literature are a basis for wheat improvement. However, many species, such as wild relatives, landraces, and old cultivars have not been studied beyond their agronomic characteristics, highlighting the lack of understanding of the physiological and metabolic processes (and their integration) associated with higher productivity and resilience in limiting environments. Retrospective studies using wheat ancestors and modern cultivars may identify novel traits that have not previously been considered, or have been underestimated, during domestication and breeding, but that may contribute to future food security. This review describes existing wheat genetic diversity and changes that occurred during domestication and breeding, and considers whether mining natural variation among wheat ancestors offers an opportunity to enhance wheat agronomic performance, spike architecture, canopy- and organ-level photosynthetic capacity, and responses to abiotic stress, as well as to develop new wheat hybrids.

Intercropping millet with low-density cowpea improves millet productivity for low and medium N input in semi-arid central Senegal

Cereal-legume intercropping has been traditionally practiced across West Africa by farmers and provides resilience of agriculture to climate variability. Intensification of these extensive intercropping systems in order to meet future food demand is critical. This study aims at evaluating the agronomic performance of the intensification of millet-cowpea intercropping with low cowpea density, and its variation with climate variability, using an on-station experiment in Bambey, Senegal. Two trials (irrigated vs rainfed) were set up to compare millet sole- and inter-cropping with a grain and a fodder variety of cowpea, in 2018 and 2019. Two levels of fertilization were tested: 0 kg(N) ha−1 and 69 kg(N) ha−1. The two cropping years were contrasting and water stress around flowering and/or during grain filling (indicated by the Fraction of Transpirable Soil Water) was higher in 2019 than in 2018 in the rainfed experiment. In both experiment and for all treatments, land equivalent ratio (LER) in the intercropping was 1.6 and 1.4 for grain and biomass respectively. Millet aboveground biomass was significantly higher in intercropping than in sole cropping in the irrigated experiment but not in the rainfed experiment. In the rainfed experiment, the interaction between cropping system and year was significant, so that millet aboveground biomass was greater in intercropping than in sole cropping in 2018 (year of lower water stress) but not in 2019 (year of higher water stress). The effect of fertilization on millet aboveground biomass did not significantly interact with cropping system (sole vs intercrop). For grain yield, fertilization interacted significantly with the cropping system in the irrigated trial: the benefits of intercropping on millet grain yield were greater with 69 kg(N) ha−1 than with 0 kg(N) ha−1. This significant interaction could not be observed in the rainfed trial, potentially due to water stress. These results show that the level of water stress (related here to the year and to the rainfed or irrigated experiment) and that of fertilization modulate the performance of millet-cowpea intercropping in the semi-arid context of Senegal. Overall, fertilization had a stronger effect on millet grain yield than intercropping. The two strategies (intercropping and mineral fertilization) can be complementary to achieve sustainable intensification of cropping system in semi-arid areas of West Africa.