Selection Of Crop Varieties Research Articles

Screening of New Dendrobium officinale Strains Adapted to Karst Forest Environmental Stress Based on Electrophysiological Detection Method

At present, the main methods of breeding Dendrobium officinale (D. officinale) include introduction and domestication, selective breeding, hybrid breeding, and mutation breeding. In the process, traditional methods of field investigation of agronomic traits are often used to select resistant varieties. Although these breeding methods are effective, they have a certain degree of subjectivity and empiricism, and the breeding cycle is long. Electrophysiological instruments were used in this experiment to test the material transport and metabolic capacity of D. officinale in a karst forest epiphytic environment and to quickly evaluate the suitability of different strains of D. officinale in a drought environment. These instruments detected the data on electrophysiological information of leaves of different strains of D. officinale under long-term drought conditions, providing immediate access to the inherent electrophysiological information of the leaves of these strains. Based on the electrophysiological parameters of D. officinale leaves as defined by the inherent electrophysiological information of plants, the water metabolism, nutrient transport, and metabolic capacity in different leaves were evaluated. The key electrophysiological indexes were verified by combining the results of chlorophyll fluorescence and chlorophyll content. The results indicate the following: (1) Parameters defined based on electrophysiological information effectively characterized the differences in intracellular water utilization, the nutrient transport status, and the metabolic capacity of different D. officinale strains. (2) The intrinsic physiological resistance, intrinsic physiological reactance, active nutrient transport capacity, and passive nutrient transport capacity were closely related to the growth status and chlorophyll function of D. officinale leaves. These electrophysiological parameters could serve as critical indicators for evaluating the drought resistance of D. officinale. (3) Under severe drought stress, strain LH1 exhibited less leaf damage, adequate water/nutrient supply, vigorous life activities, and excellent drought resistance. We found that strain LH1 demonstrates better adaptation to the arid environment of karst forest lands. The electrophysiological detection method employed in this study offers a new technique for screening wild-cultivated D. officinale resistance strains. The results indicate that the real-time online leaf electrophysiological information measured by the method in this study can characterize the energy and material metabolism of crops, greatly improving the efficiency of crop-variety selection and reducing costs. These conclusions can be used to obtain real-time information on the transmission of water and nutrients within plant cells and can provide theoretical support for studying the adaptation mechanisms of crops to adverse environments.

Coastal Acid-Sulfate Soils of Kalimantan, Indonesia, for Food Security: Characteristics, Management, and Future Directions

Coastal acid-sulfate soils are crucial for producing crops and thus, for food security. However, over time, these soil resources experience degradation, leading to higher agro-input, lower yields, and environmental hazards that finally threaten food security. The optimal use of this fragile resource is only attained by implementing vigorous integrated water–soil–crop management technologies amid the climate change impact. This study aimed to review the distribution, properties, use, and management of acid-sulfate soils in Kalimantan, Indonesia. Acid-sulfate soils cover about 3.5 Mha of the coastal area in Kalimantan and have high acidity, high-risk iron and aluminum toxicity, and low fertility, requiring precise water management, amelioration and fertilizer application, crop variety selection, and rice cultivation technologies. Lime, biochar, organic fertilizer, compost, ash, and fly ash are ameliorants that raise pH, reduce iron and aluminum toxicity, and improve crop yield. Rice cultivation has developed from traditional to modern but needs re-designing to fit local conditions. Depending on the soil nutrient status, rice cultivation requires 80–200 kg ha−1 of urea, 50–150 kg ha−1 of SP36, 50–150 kg ha−1 of KCl, and 125–400 kg ha−1 of NPK compound fertilizer, but is affected by CH4 and CO2 emissions. Good water management impacts the effective implementation of amelioration and fertilizer application technologies. The remaining challenges and future directions for water management, amelioration, fertilizer application, crop varieties, cultivation techniques, land use optimization, climate change adaptation and mitigation, technology adoption and implementation, and resource conservation are outlined. Acid-sulfate soils remain a resource capital that supports food security regionally and nationally in Indonesia.

Comparing dry farming of tomatoes across varieties and soil management history

Farmers faced with increasingly limited access to freshwater for irrigation are utilizing dry farming techniques to produce fruit, vegetable, and grain crops. Defined as crop production during a dry season using little or no irrigation, dry farming relies on water stored in the soil and requires specialized soil management, healthy soil biology, and careful selection of crop varieties. We investigated these three factors in a dry-farmed tomato (Solanum lycopersicum) field trial with three indeterminate varieties (Early Girl, Momotaro, and Zapotec) and two determinate genotypes (76R and rmc), the latter serving as a model system for studying the role of arbuscular mycorrhizal (AM) fungi. While five prior years of contrasting surface tillage practices changed soil properties, they did not affect marketable tomato yields or quality, nor affect plant physiology, including plant water use efficiency [intrinsic (WUEi) and long-term (δ13C)], gas exchange, stem water potential (Ψstem), and leaf relative water content (RWC). Early Girl produced a greater number of fruits and fewer non-marketable fruits than Momotaro and Zapotec. Although AM fungi root colonization was very low for both wildtype mycorrhizal genotype 76R and its reduced mycorrhizal mutant rmc, it differed significantly depending on genotype and tillage treatment. 76R produced slightly greater marketable fruit, but physiological responses did not differ significantly between genotypes. This study does not provide field-based evidence that soil chemical and biological changes resulting from no-till influence dry-farmed tomato productivity, while genotype had a clear impact on tomato yield and quality. Field-scale tillage experiments may better capture soil physical changes that affect water availability, especially at depth, and should be examined.

YouTube as a Source of Information for Agribusiness: Audience Perspective and Content Video Analysis

Agribusiness forms the cornerstone of many economies worldwide. Access to agribusiness information is crucial, as it is a valuable resource, catering to a diverse audience, including farmers and the general public. YouTube is a prominent online platform extensively used by people to seek information about agribusiness. The videos and content uploaded on YouTube offer an in-depth comprehension and provide diverse perspectives from various angles on the discussed topics. In agriculture, visual content plays a pivotal role in elucidating intricate concepts such as farming techniques, pest and disease management, crop variety selection, and the latest advancements in agricultural technology. This research endeavors to assess the utility of YouTube as a source of information and scrutinize the content of YouTube videos in the context of agribusiness information. The results of this data analysis reveal that most viewers accessing agribusiness-related content on YouTube are notably influenced by cognitive effects. Furthermore, the study identifies affective effects, personal integration effects, and encouragement as additional factors that impact the audience's inclination to view videos about agribusiness on YouTube. The findings from this analysis underscore the significance of factors such as the number of likes, dislikes, views, reliability assessment, video quality, and completeness evaluation in establishing a substantial correlation with audience preferences and behaviors.

Estimation of grain filling rate of winter wheat using leaf chlorophyll and LAI extracted from UAV images

The grain filling rate (GFR) plays a pivotal role in assessing winter wheat grain development and guiding crop variety selection and cultivation strategies. Presently, GFR monitoring primarily relies on destructive sampling methods, which are impractical for swift assessments in extensive agricultural fields. Our study introduces a novel approach for estimating winter wheat grain filling rate (GFR) using leaf chlorophyll content (LCC) and Leaf Area Index (LAI) extracted from UAV imagery. Initially, we established a quantitative relationship between GFR and LAI as well as LCC in winter wheat. Subsequently, UAV multispectral imagery was employed to track the time-series dynamics of LAI and LCC during the grain-filling stage. Ultimately, we constructed an estimation model for winter wheat GFR and achieved plot-scale GFR mapping through UAV-based imaging technology. To identify sensitive vegetation index combinations for LAI and chlorophyll content (SPAD), we employed adaptive re-weighted sampling and continuous projection algorithms, respectively. Following this, we employed partial least squares and random forest algorithms to develop LAI and SPAD estimation models, which were then compared to full-band regression. Finally, GFR estimation was based on the conversion models of LAI and SPAD to GFR. Our findings revealed that, despite variations in water supply, there were no significant differences in GFR trends among the irrigated treatments. However, in the nitrogenous fertilizer application treatments, GFR initially declined with increased nitrogenous fertilizer supply, reaching its peak between 21 and 25 days post-flowering, during which period the differences in GFR among the various nitrogenous fertilizer application treatments were not significant. As the reproductive period advanced, higher nitrogenous fertilizer treatments maintained a higher GFR for a more extended period and experienced a slower decline compared to the lower nitrogenous fertilizer treatments. LAI validation yielded an R2 of 0.84, a root mean square error (RMSE) of 0.39, and a normalized root mean square error (NRMSE) of 10.9%. SPAD validation resulted in R2, RMSE, and NRMSE values of 0.79%, 1.30%, and 12.5%, respectively. The GFR estimation achieved an R2 of 0.77, an RMSE of 0.32 mg/d, and an NRMSE of 11.3%. Mapping the GFR distribution in the field, coupled with water and fertilizer management, supports UAVs in monitoring crop growth and refining field-level water and fertilizer decisions.

Selection of crop varieties and yield prediction based on phenotype applying deep learning

<div align="center"><span lang="EN-US">In India, agriculture plays an important role in the nation’s gross domestic product (GDP) and is also a part of civilization. Countries’ economies are also influenced by the amount of crop production. All business trading involves farming as a major factor. In order to increase crop production, different technological advancements are developed to acquire the information required for crop production. The proposed work is mainly focused on suitable crop selection across districts in Tamil Nadu, considering phenotype factors such as soil type, climatic factors, cropping season, and crop region. The key objective is to predict the suitable crop for the farmers based on their locations, soil types, and environmental factors. This results in less financial loss and a shorter crop production timeframe. Combined feature selection (CFS)-based machine regression helps increase crop production rates. A brief comparative analysis was also made between various machine learning (ML) regression algorithms, which majorly contributed to the process of crop selection considering phenotype factors. Stacked long short-term memory (LSTM) classifiers outperformed other decision tree (DT), k-nearest neighbor (KNN), and logistic regression (LR) with a prediction accuracy of 93% with the lowest classification accuracy metrics. The proposed method can help us select the perfect crop for maximum yield.</span></div>

Empowering Women in Agriculture: Exploring Their Role and Decision Making Impact – A Study in Manipur, India

Background: Manipur, a North-Eastern State of India where about 49.81 per cent of total population is women [1] and they contribute about 51.46 per cent of total working force. The state, which is relatively backward in agricultural development paradigm, has a glorious past regarding women’s ‘movement’ for the state’s cause. Now, it is to be understood properly their role and participation in farm economy for revamping the agrarian situation in the state by exploring the farm women’s role.
 Methods: The study was conducted by collecting both secondary as well as primary information from sample respondents equally distributed over two valley districts (namely, Thoubal and Imphal East) of Manipur. In all the phases of selection (of sub-division, block, village etc.) the method of probability proportional sampling was employed. Standard econometric methods and statistical packages were applied to elucidate the core objective(s) of the study.
 Results: The status of participation of farm women in decision making process has been judged with the help of Participatory Index (P.I) and Decision Making Index (DMI). Farm women, in general, participates prominently in socio-cultural matters (DMI = 0.86-0.93) and miscellaneous matters (DMI = 0.83-0.96), moderately in family’s financial/economic matters (DMI = 0.62-0.89) but rather poorly (DMI = 0.43-0.56) in farming matters. More specifically, they are relatively less consulted or are given less importance on matters like consultation with officials (private or government), purchase of household furniture, purchase of improved implements/machineries, selection of crop variety, input management in crop cultivation etc.

Assessing Soil Organic Carbon Pool for Potential Climate-Change Mitigation in Agricultural Soils—A Case Study Fayoum Depression, Egypt

It is essential to assess the soil organic carbon pool (SOCP) in dry environments to apply appropriate management techniques that address sustainable development. A significant opportunity for sustaining agricultural output and reducing climate change is the storage of soil organic carbon in agricultural soil. The goal of this study was to measure the spatial variability of SOCP content, and determine the effects of soil texture, changes in land use, and land cover on SOCP in surface soil samples. The study additionally investigated the relationships between SOCP and other characteristics, including the normalized vegetation index (NDVI) and land surface temperature (LST), as well as the effects of increasing soil organic carbon on the amount of greenhouse gases. To accomplish this goal, 45 soil surface samples were collected to a depth of 30 cm at the Fayoum depression in Egypt, and analyzed. The soil samples were representative of various soil textures and land uses. The average SOCP concentration in cultivated regions is 32.1 and in bare soils it is 6.5 Mg ha−1, with areas of 157,112.94 and 16,073.27 ha, respectively. According to variances in soil textures, sandy soils have the lowest SOCP (1.8 Mg ha−1) and clay loam soils have the highest concentrations (49 Mg ha−1). Additionally, fruit-growing regions have the greatest SOCP values and may therefore be better suited for carbon sequestration. The overall average SOCP showed 32.12 Mg C ha−1 for cultivated areas. A rise in arable land was accompanied by a 112,870.09 Mg C rise in SOCP. With an increase in soil organic carbon, stored carbon dioxide emissions (greenhouse gases) would be reduced by 414,233.24 Mg CO2. We should consider improving fertilization, irrigation methods, the use of the multiple cropping index, decreasing desertion rates, appropriate crop rotation, and crop variety selection. The research highlights the significance of expanding cultivated areas towards sustainable carbon sequestration and the climate-change-mitigation potential.

Impact of rainfall onset date on crops yield in Ghana

Rainfall onset date (ROD) influences farmer planting decisions, yet there is a dearth of information on the extent to which ROD influences crop yield. This study assesses the effect of ROD on the yield of four crops (Maize, millet, rice, and sorghum) in Ghana. It uses crop yields from the Ministry of Food and Agriculture (MoFA) and the Food and Agriculture Organization (FAO), and employs the Decision Support System for Agro-technology Transfer (DSSAT) crop model to simulate maize yields from 1985 to 2004. The crop model simulations were forced with weather data from the gridded Global Meteorological Forcing Dataset (GMFD). The relationship between crop yields and RODs from three datasets (observed, satellite, and GMFD) are studied. The results of the study show a good correlation between MoFA and FAO crop yield data (with correlation coefficient (r) of 0.97, 0.92, 0.77, and 0.99 for maize, millet, rice, and sorghum, respectively). RODs from satellite observation feature a high correlation with RODs from station observation (r = 0.72), but RODs from GMFD feature weak correlations (r < 0.3) with both observation datasets. The study finds a negative correlation between observed RODs and crop yields (i.e. an early onset corresponds to high yields) but a positive correlation between GMFD RODs and crop yields (i.e. an early onset correspondence to low yields). The DSSAT model reproduces the observed yield pattern, but with substantial biases. The findings of this study can be used to advise small-holder farmers on planting dates and crop variety selection.

Assessment of Available Water and Crop Water Requirements of Major Crops in Nagarjuna Sagar Right Canal Command Area, Andhra Pradesh, India

The mean water releases at head section of 11 years of Nagarjuna Sagar Jawahar right main Canal, Andhra Pradesh, India is found to be 128.13 TMC (3,627.71 MCM). The mean surface water availability was estimated as 2,229 MCM. For the efficient utilization of groundwater, the quality plays a major role in terms of selection of crop variety for sustainable agriculture. The ground water quantity of the command area available was estimated 1385 MCM and the mean annual conjunctive use of command area was 3,614 MCM (128 TMC).
 The crop water requirement for paddy, cotton, chilies, millet and pulses were estimated in the command area by using CROPWAT model. The crop water requirement for paddy in NSRC command area of Guntur district for black soils was 848.2 mm. The irrigation water requirement was 638.9 mm and for red soils, crop water requirement for paddy and irrigation water requirements were 848.2 mm and 624.5 mm respectively. Similarly, computed for all the crops and overall crop water demand for both (Guntur and Prakasam) districts of NSRC command area for different soils and different crops per annum was 4,456 MCM without considering cattle and domestic water use. Based on the research, it was concluded that the available water is not sufficient and it is suggested to choose alternative crops for bringing entire area into cultivation.

Modelling spatial and temporal correlation in multi-assessment perennial crop variety selection trials using a multivariate autoregressive model

Context Perennial crop variety selection trials are often conducted over several seasons or years. These field trials often exhibit spatial correlation between plots. When data from multiple assessment times are analysed, it is necessary to account for both spatial and temporal correlation. A current approach is to use linear mixed models with separable spatial and temporal residual covariance structures. A limitation of these separable models is that they assume the same spatial correlation structure for each assessment time, which may not hold in practice. Aims This study aims to provide more flexible methods for modelling the spatio-temporal correlation in multi-assessment perennial crop data, allowing for differing spatial parameters for each time, together with modelling genetic effects over time. Methods The paper investigates the suitability of two-directional invariant multivariate autoregressive (2DIMVAR1) models for analysis of multi-assessment perennial crop data. The analysis method is applied to persistence data from a pasture breeding trial. Key results The multivariate autoregressive spatio-temporal residual models are a significant improvement on separable residual models under different genetic models. The paper demonstrates how to fit the models in practice using the software ASReml-R. Conclusions A flexible modelling approach for multi-assessment perennial crop data is presented, allowing differing spatial correlation parameters for each time. The models allow investigation into genotype × time interactions, while optimally accounting for spatial and temporal correlation. Implications The models provide improvements on current approaches and hence will result in more accurate genetic predictions in multi-assessment perennial crop variety selection trials.

Phyto-Friendly Soil Bacteria and Fungi Provide Beneficial Outcomes in the Host Plant by Differently Modulating Its Responses through (In)Direct Mechanisms.

Sustainable agricultural systems based on the application of phyto-friendly bacteria and fungi are increasingly needed to preserve soil fertility and microbial biodiversity, as well as to reduce the use of chemical fertilizers and pesticides. Although there is considerable attention on the potential applications of microbial consortia as biofertilizers and biocontrol agents for crop management, knowledge on the molecular responses modulated in host plants because of these beneficial associations is still incomplete. This review provides an up-to-date overview of the different mechanisms of action triggered by plant-growth-promoting microorganisms (PGPMs) to promote host-plant growth and improve its defense system. In addition, we combined available gene-expression profiling data from tomato roots sampled in the early stages of interaction with Pseudomonas or Trichoderma strains to develop an integrated model that describes the common processes activated by both PGPMs and highlights the host’s different responses to the two microorganisms. All the information gathered will help define new strategies for the selection of crop varieties with a better ability to benefit from the elicitation of microbial inoculants.

Preliminary Study on Existing Scenario of Selected Soil Properties in Cheddikulum Grama Niladhari Division Vavuniya District, Sri Lanka

The productivity of the soil has changed into the worst condition knowingly or unknowingly by anthropogenic activities as well as natural phenomena. The study was conducted to quantify selected soil properties in Cheddikulum Grama Niladhari division, Vavuniya District and find reclaim the problem soil and make suggestions to cultivate the crop variety suitable for the existing soil properties since this area is a recently rehabilitated area. Fifty composite samples were selected for the research using the stratified random sampling method. Stratification was based on the type of land cover, and following land cover patterns were identified agriculture land patches, forest patches, and grassland patches. Soils were collected from top to 30 cm depth (root zone) using a core sampler, and subsamples were collected to obtain composite samples. Soil samples were analyzed for pH, EC, organic matter content, total nitrogen, exchangeable potassium, and available phosphorous. 14.8% of agricultural land area was acidic soil and 4.7% alkaline soil. 15.3% of agricultural land area was identified as saline soil. 67.11% of agricultural lands contain more phosphorous concentration than the optimum range. 4.7% of agricultural lands contain higher potassium concentrations than the optimum range. 94% of forest lands and 100% of grasslands contains phosphorous concentration higher than the optimum range. But forest lands showed a lower level of potassium concentration. 23.6% of grasslands contain higher potassium than the optimum level. Organic matter ranged between 0.01% to 5.43% in agricultural lands where 82% of total nitrogen concentrations were the optimum level. Agriculture practices lead to change in the soil; hence identified soil problems should be reclaimed in order to maintain the fertility of the soil for sustainable production. Proper management of soil can be a better solution for supporting the successful agricultural activity of the community in the future and socio-economic development of this region and need to be adhering to crop variety selection and soil reclamation practices.
 Keywords: Productivity, Soil problems, Soil reclamation

Effect of fertility levels on sesame (Sesamum indicum) varieties under agri-horti system

The move towards higher production of quality crops with alternative land use systems i.e. agri-horticulture system in combination with adequate supply of nitrogen, phosphorus, potassium and sulphur and improved varietal selection can solve the problem of lower productivity. Consequently, the present study illustrated that selection of crop varieties according to land use system with balanced nutrients supply can optimize the crop production in sustainable manner. The study showed that the performance of crop with different varietal selection was influenced by the different levels of nutrients supply. The growth and yield parameters were significantly affected with the application of 60, 30, 30, 30 kg of N, P2O5, K2O and S/ha and produced significantly higher seed yield (675 kg/ha) as compared to 40, 20, 20, 20 kg of N, P2O5, K2O and S/ ha and 20, 10, 10, 10 kg of N, P2O5, K2O, and S/ha among various fertility levels.

Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model

In this study, we evaluated the suitability of semi-arid region of Central Morocco for wheat production using Agricultural Production Systems sIMulator (APSIM) considering weather, soil properties and crop management production factors. Model calibration was carried out using data collected from field trials. A quantitative statistics, i.e., root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and index of agreement (d) were used in model performance evaluation. Furthermore, series of simulations were performed to simulate the future scenarios of wheat productivity based on climate projection; the optimum sowing date under water deficit condition and selection of appropriate wheat varieties. The study showed that the performance of the model was fairly accurate as judged by having RMSE = 0.13, NSE = 0.95, and d = 0.98. The realization of future climate data projection and their integration into the APSIM model allowed us to obtain future scenarios of wheat yield that vary between 0 and 2.33 t/ha throughout the study period. The simulated result confirmed that the yield obtained from plots seeded between 25 October and 25 November was higher than that of sown until 05 January. From the several varieties tested, Hartog, Sunstate, Wollaroi, Batten and Sapphire were yielded comparatively higher than the locale variety Marzak. In conclusion, APSIM-Wheat model could be used as a promising tool to identify the best management practices such as determining the sowing date and selection of crop variety based on the length of the crop cycle for adapting and mitigating climate change.

Adaptation Strategies in Response to the Effect of Climate Change on Tomato Production

Climate change is one of the largest challenge of this century. Globally, climate change causes drops in yield for their most valuable crops, particularly in developing countries. Afghanistan is one of the world's most vulnerable countries to the negative consequences of climate change. Tomato cultivation is a means of livelihood for most farmers in Afghanistan. The aim of this study was to assess the adaptation strategies on tomato production in response to the impact of climate change in Ghazni province. The study findings indicate a rise in both maximum and minimum temperatures, combined with a decline in annual precipitation over the ten years (2008-2017) period in an unreliable seasonal distribution. The study found that the occurrence of pests and diseases had a substantial impact on tomato production due to climate change. Present study highlights the role of climate variables in the production of tomatoes (temperature and precipitation) while controlling other confounding factors. Selection of crop variety according to climate change and planting time are the two adaptation methods to cope up with the drastic change in the climate to retain the productivity to some extent.

Evaluation of Phenolic Root Exudates as Stimulants of Saptrophic Fungi in the Rhizosphere.

The rhizosphere microbial community of crop plants in intensively managed arable soils is strongly dominated by bacteria, especially in the initial stages of plant development. In order to establish more diverse and balanced rhizosphere microbiomes, as seen for wild plants, crop variety selection could be based on their ability to promote growth of saprotrophic fungi in the rhizosphere. We hypothesized that this can be achieved by increasing the exudation of phenolic acids, as generally higher fungal abundance is observed in environments with phenolic-rich inputs, such as exudates of older plants and litter leachates. To test this, a rhizosphere simulation microcosm was designed to establish gradual diffusion of root exudate metabolites from sterile sand into arable soil. With this system, we tested the fungus-stimulating effect of eight phenolic acids alone or in combination with primary root metabolites. Ergosterol-based fungal biomass measurements revealed that most phenolic acids did not increase fungal abundance in the arable soil layer. These results were supported by comparison of fungal biomass in the rhizosphere of wild type Arabidopsis thaliana plants and mutants with altered phenolic acid metabolism. Salicylic acid was the only phenolic acid that stimulated a higher fungal biomass in the arable soil layer of microcosms, but only when combined with a background of primary root metabolites. However, such effect on rhizosphere fungi was not confirmed for a salicylic acid-impaired A. thaliana mutant. For three phenolic acid treatments (chlorogenic acid, salicylic acid, vanillic acid) fungal and bacterial community compositions were analyzed using amplicon sequencing. Despite having little effect on fungal biomass, phenolic acids combined with primary metabolites promoted a higher relative abundance of soil-borne fungi with the ability to invade plant roots (Fusarium, Trichoderma and Fusicolla spp.) in the simulated rhizosphere. Bacterial community composition was also affected by these phenolic acids. Although this study indicates that phenolic acids do not increase fungal biomass in the rhizosphere, we highlight a potential role of phenolic acids as attractants for root-colonizing fungi.

Opportunities and barriers for using climate information for building resilient agricultural systems in Sudan savannah agro-ecological zone of north-eastern Ghana

Empirical evidence on the opportunities and barriers to the uptake of climate services by smallholder farmers for resilient agricultural systems in sub-Saharan Africa is limited. This paper addresses this important gap by evaluating the opportunities and barriers to the uptake of climate information (from short-term weather forecasts, through seasonal forecasts to longer-term climate change information on decadal timescales) by smallholder farmers in the Sudan savannah agro-ecological zone of Ghana. The paper answers the following research questions: i) what kinds of weather and climate information are available and accessible to smallholder farmers for agricultural management decision-making? ii) what opportunities exist for using climate information in agricultural systems in the Sudan savannah agro-ecological zone? iii) what are the key barriers to the uptake of climate information by smallholder farmers in the Sudan savannah agro-ecological zones of Ghana? The study used participatory approaches including household surveys with 555 farmers, 3 stakeholder workshops, 15 key informant interviews and 12 focus group discussions across 6 communities in the Sudan savannah agro-ecological zone. Findings show that more than a third of the study respondents (40%; n = 555) were not receiving climate information. Out of the 60% receiving climate information, the majority (91%; n = 335) indicated receiving information on rainfall with fewer respondents 21% and 26% receiving information on temperature and windstorms, respectively. Radio was the key medium for receiving weather and climate information. Both female and male smallholder farmers were using climate information to make critical farming decisions including time of land preparations (79%), crop variety selection (50%), changing cropping patterns (36%), planting time adjustments (31%), harvesting time (21%) and disease/pest management (10%). Increasing uptake of weather and climate information is confronted with multiple barriers including inadequate information on seasonal forecast for long-term planning, low accessibility of climate information, high levels of illiteracy, difficulties in understanding technical language used in communicating climate information and misalignment between the climate information provided and what smallholder farmers need. Climate information should be linked directly to agricultural impacts and management decision-making to ensure it is both available to, and usable by smallholder farmers.

English

Crop canopy architecture is known to affect weed performance. Field experiments were conducted to examine the effect of altered crop canopy architecture and light interception on growth and development of wild proso millet and giant foxtail, two problematic weed species. Crop canopy architecture was manipulated by planting two sweet corn varieties contrasting in canopy architecture (Bonus-has a dense leaf canopy and Sprint-has an open leaf canopy) at two row spacings (51-cm and 76-cm rows). Results showed that sweet corn variety, rather than row spacing, altered crop canopy architecture, which in turn altered photosynthetically active radiation (PAR) and red:far-red light ratio (R:FR) received by both weeds. The competitive Bonus canopy had a higher (P<0.05) PAR and R:FR than Sprint at anthesis and harvest. Bonus also more effectively suppressed weed growth and development than Sprint, and weeds growing on Bonus plots had reduced tiller numbers, reduced biomass, lower population densities, and reduced seed production (P<0.05). These responses were attributed to the Bonus canopy having a higher canopy area index, which intercepted more light resulting in lower PAR and R:FR received by both weeds. This study suggests that crop variety selection is an important consideration for weed suppression in row-cropping systems. Key words: Crop canopy architecture, light interception, photosynthetically active radiation, red:far-red ratio, row spacing, sweet corn, wild proso millet, giant foxtail.

Comparison of physiological effects of osmotic stress on two wheat genotypes

Revealing stress tolerance mechanisms in plants would contribute to the selection of crop varieties with a higher capacity for surviving in unfavourable environments. In this regard, it is essential to identify possible physiological features that might be beneficial for increasing plant resistance to stress. Two contrasting common wheat (Triticum aestivum L.) cultivars with different drought tolerance were subjected to 48 h treatment with 20% polyethylene glycol 8000, which provoked an extra degree of osmotic and oxidative stress as well as distinct physiological responses. Better water retention capacity in leaves and lesser extent of membrane injury found in cultivar ‘Guinness’ compared to cultivar ‘Niki’ correlated with increased osmotic adjustment by accumulating higher amounts of proline and higher antioxidant scavenging capacity in the former. Compared to soluble sugars and total free amino acids, proline contributed to a greater extent to preserving leaf water. It was speculated that such a combination of features would set a genotypic advantage for this cultivar, which could also determine better performance under drought conditions in the field.