Effect of phosphorus nutrition on growth of potato genotypes with contrasting phosphorus effeciency

Potato (Solanum tuberosum L.) has high phosphorus requirement for optimum growth and yield. Thus, under P deficiency, growth and yield are considerably reduced. An experiment was conducted in a controlled growth chamber on the effect of P supply on morphological and physiological plant parameters of three potato genotypeshaving contrasting P efficiency. The genotypes were CGN 17903, CIP 384321.3 and CGN 18233. They were grown under two P levels [100 mg P kg-1 soil (low P) and 700 mg P kg-1 of soil (high P)]. Treatments were arranged in a completely randomised block designs with six replications. Low P supply reduced shoot dry matter yield, relative growth rate, leaf number, whole plant relative leaf expansion rate, total leaf area per plant, plant height and net assimilation rate of P-inefficient genotype, more than that of the P-efficient genotypes. However,low P supply did not affect net photosynthetic rate per unit leaf area, leaf dark respiration rate, chlorophyll fluorescence rate and electron transport rate of both P-efficient and inefficient genotypes. P-efficient genotype CGN 17903 allocated more dry matter yield to the leaf which might have enabled higher light harvesting, hence contributing to high biomass accumulation of this genotype

Emergence of the subtropical sea urchin Centrostephanus rodgersii as a threat to kelp forest ecosystems in northern New Zealand

Marine protected areas have long been proposed as a key tool to restore lost food web interactions and increase the resilience of ecosystems to climate change impacts. However, a changing climate can result in the arrival of new species or differentially affect native species, which can alter ecosystem dynamics and make it difficult to predict how ecosystems will respond to protection. The long-spined sea urchin Centrostephanus rodgersii is a well-known range extender with large impacts on kelp forest ecosystems, yet its response to warming and long-term marine protection has not been examined within its native range. We examine long-term trends in C. rodgersii and the endemic sea urchin Evechinus chloroticus following no-take protection within the Poor Knights Islands Marine Reserve, in northeastern Aotearoa New Zealand, from 1999-2022, and compare with population trends at an unprotected island group. Within the marine reserve, E. chloroticus decreased in density, became more cryptic, and urchin barrens associated with this species largely disappeared, whereas in fished areas, populations and extent of barrens remained stable. This differing response between the reserve and fished location is consistent with a top-down effect and greater abundance of predatory fish in the reserve. In contrast, the subtropical sea urchin C. rodgersii increased in abundance by 9.3 times in the Poor Knights Island Marine Reserve and 4.3 times at the fished location, with areas of urchin barrens associated with this species developing at both locations. This increase coincides with substantial warming over the monitoring period (0.25°C decade-1) and low numbers of key predators (rock lobster) at both reserve and fished locations. This highlights the emerging threat of C. rodgersii to rocky reefs in the region and how marine protection alone may not increase resilience to this threat. This suggests multifaceted management approaches are needed to mitigate the impacts of emerging pest species and increase the resilience of temperate reef ecosystems in a warming climate

Science-based decision support for formulating crop fertilizer recommendations in sub-Saharan Africa

Open Access Article; Published online: 31 Jan 2020In sub-Saharan Africa, there is considerable spatial and temporal variability in relations between nutrient application and crop yield, due to varying inherent soil nutrients supply, soil moisture, crop management and germplasm. This variability affects fertilizer use efficiency and crop productivity. Therefore, development of decision systems that support formulation and delivery of site-specific fertilizer recommendations is important for increased crop yield and environmental protection. Nutrient Expert (NE) is a computer-based decision support system, which enables extension advisers to generate field- or area-specific fertilizer recommendations based on yield response to fertilizer and nutrient use efficiency. We calibrated NE for major maize agroecological zones in Nigeria, Ethiopia and Tanzania, with data generated from 735 on-farm nutrient omission trials conducted between 2015 and 2017. Between 2016 and 2018, 368 NE performance trials were conducted across the three countries in which recommendations generated with NE were evaluated relative to soil-test based recommendations, the current blanket fertilizer recommendations and a control with no fertilizer applied. Although maize yield response to fertilizer differed with geographic location; on average, maize yield response to nitrogen (N), phosphorus (P) and potassium (K) were respectively 2.4, 1.6 and 0.2 t ha−1 in Nigeria, 2.3, 0.9 and 0.2 t ha−1 in Ethiopia, and 1.5, 0.8 and 0.2 t ha−1 in Tanzania. Secondary and micronutrients increased maize yield only in specific areas in each country. Agronomic use efficiencies of N were 18, 22 and 13 kg grain kg−1 N, on average, in Nigeria, Ethiopia and Tanzania, respectively. In Nigeria, NE recommended lower amounts of P by 9 and 11 kg ha−1 and K by 24 and 38 kg ha−1 than soil-test based and regional fertilizer recommendations, respectively. Yet maize yield (4 t ha−1) was similar among the three methods. Agronomic use efficiencies of P and K (300 and 250 kg kg−1, respectively) were higher with NE than with the blanket recommendation (150 and 70 kg kg−1). In Ethiopia, NE and soil-test based respectively recommended lower amounts of P by 8 and 19 kg ha−1 than the blanket recommendations, but maize yield (6 t ha−1) was similar among the three methods. Overall, fertilizer recommendations generated with NE maintained high maize yield, but at a lower fertilizer input cost than conventional methods. NE was effective as a simple and cost-effective decision support tool for fine-tuning fertilizer recommendations to farm-specific conditions and offers an alternative to soil testing, which is hardly available to most smallholder farmers

Assessment of rainwater management practices and land use land cover changes in the Meja watershed of Ethiopia

Poor rainwater management (RWM) practices and resultant problems of land degradation and low water productivity are severe problems in the rural highlands of Ethiopia. The current study was undertaken at Meja watershed, which is located in the Jeldu district of Oromia region. The study investigated rainwater management practices and associated socio-economic and biophysical conditions in the watershed. The existing RWM interventions, their extent and the nature of changes in land use and land cover (LULC) conditions were mapped and evaluated. Results indicated that over the two decades between 1990 and 2010 there was an increase in the extent of cultivated land and large expansion in eucalyptus plantation at the expense of natural forest and grazing lands. Results indicate that, with few exceptions of RWM interventions practised, there were mainly poor and inefficient rainwater management practices. The overall effect leads to inadequacy of water for household consumption, livestock and for intensifying agricultural production via small scale irrigation systems. Deforestation and poor resource management resulted in soil degradation, reduction of hydrological regimes and water productivities in the watershed

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Not AvailableA field experiment was conducted during the summer season of 2000-2001 at the Vegetable Research Farm of Indian Agricultural Research Institute (I.A.R.I.), New Delhi (India) to test the efficacy of three Azotobacter strains as a potential supplement to nitrogenous fertilizer in improving growth and yield of onion cv. Pusa Madhvi. The treatments consisted of factorial combination of four levels of nitrogen (0, 25, 50 and 75 kg N ha -1 ) and three Azotobacter strains (CBD-15, AS-4 and M-4) with two uninoculated controls one with full dose of N (100 kg ha -1 ) and the other without NPK. Application of 75 kg N ha -1 along with inoculation of CBD-15 was found to have significantly increased most of the growth and yield parameters, soil available nitrogen, and nitrogen content in the bulb followed by M-4 inoculation as compared to application of full dose of nitrogen without the inoculation. Days to bulb initiation were significantly reduced due to inoculation with CBD-15 or M-4 along with 50 kg N ha -1 whereas days to bulb maturity were significantly reduced due to inoculation with any of the strains along with the same N rate (50 kg ha -1 ) as compared to application of full dose of nitrogen without the inoculation. The finding demonstrated a saving of 50 kg N ha -1 without significantly affecting yield and an average increase of 13.5% marketable yield due to Azotobacter inoculation in the presence of 75 kg N ha -1 .Not Availabl

PPMaP: Reproducible and Extensible Open-Source Software for Plant Phenological Phase Duration Prediction and Mapping in Sub-Saharan Africa

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software runs on the ‘Windows’ platform and supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest in sub-Saharan Africa. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework was implemented in R, providing a flexible and easy-to-use GUI interface. Since this allows for appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.publishedVersio

PPMaP: Reproducible and Extensible Open-Source Software for Plant Phenological Phase Duration Prediction and Mapping in Sub-Saharan Africa

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software runs on the ‘Windows’ platform and supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest in sub-Saharan Africa. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework was implemented in R, providing a flexible and easy-to-use GUI interface. Since this allows for appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety