Simulating Regional Cassava Yield Gap in Nigeria

Cassava production is essential for food security in Sub-Saharan Africa and serves as a major calorie- intake source in Nigeria. Here we use a crop model, LINTUL5, embedded into a modeling framework SIMPLACE to estimate potential cassava yield gaps (Yg) in 30 states of Nigeria. Our study of climate parameter influence on the variability of current and potential yields and Yg shows that cumulative radiation and precipitation were the most significant factors associated with cassava yield variability (p = 0.01). The cumulative Yg mean was estimated as 18202 kg∙ha-1, with a maximum of 31207 kg ha-1 in Kano state. Across the states, nutrient limitation accounts for 55.3% of the total cassava yield gap, while the remaining 44.7% is attributed to water limitation. The highest untapped water-limited yields were estimated in States, such as Bauchi, Gombe, and Sokoto, characterized by the short rainy season. Conclusively, the current cassava yield levels can be increased by a factor of five through soil fertility enhancement and with irrigation, particularly in semi-arid regions.

Cascading Models of CNN and GRU with Autoencoder Loss for Precipitation Forecast in Thailand

It is a crucial task to accurately forecast precipitation, especially rainfall in Thailand, since it relates to flood prevention and agricultural planning. In our prior work, we have presented a model based on deep learning approach; however, its performance is still limited due to two main issues. First, there is an imbalance issue, where most rainfall is zero or no rain because Thailand has short rainy season. Second, predicted rainfall is still underestimated since moderate and heavy rainfall cases barely occurs. In this paper, we propose an enhanced deep learning model to forecast rainfall in Thailand. Our model is a cascading of CNN and GRU along with exogenous variables, i.e., temperature, pressure, and humidity. There are two stages in our model. First, CNN is specialized for classifying rain and non-rain events. In this stage, an imbalanced issue is alleviated by applying “focal loss”. Second, GRU is responsible for forecasting rainfall. Its predicted range is lifted using “autoencoder loss”. The experiment was conducted on hourly rainfall dataset between 2012 and 2018 obtained from a public government sector in Thailand. The results show that our enhanced model outperforms ARIMA and CNN-GRU in terms on RMSE of most regions in Thailand.

Analysing The Feature of Meteorological Drought in North East Ethiopia: The Case of Meket and Wadla Districts in North Wello Zone, Amhara Region

The study was undertaken to investigate the magnitude, frequency and trends of drought incidence in North Wello Zone, northeast Ethiopia using monthly rainfall record for the period 1987 to 2017 of Meket and Wadla station. Standard precipitation index and Mann–Kendal test were used to analyse drought event and trends of drought occurrences, respectively. Drought Index Calculator used to analyse standard precipitation index. The coefficient variation of the study area for Meket was (21.2%), while for Wadla it was (53%) which showed high inter-annual variability. It was established that both studied stations experienced drought episodes in 1987, 1988, 1991, 1992, 1994, 1998, 1999, 2001, 2006, 2014 and 2015, drought years in the history of Ethiopia. The year 2006 was the most severe and distinct-wide extreme drought episode in both studied stations which standard precipitation index values -2.14 at Wadla and -2.01 at Meket station. The frequency of drought number of years which experienced negative standardize precipitation index values in the total time series of 30 years observed for all time scale at both station is 50 percent and above. The drought magnitude of different time scale varied from slight to extreme severe in the studied stations. The Mann–Kendal trend test shows except two-month timescale at Wadla station, all timescales were not statistically significant (P<0.05). Generally increasing tendencies of drought were observed during main rainy season and decreasing tendencies of drought during short rainy season and annual scale observed in the study area.

Epidemiological and Clinical Profile of Patients in the Medical Emergency Department at Amissa Bongo Regional Hospital in Franceville (ABRH), Gabon; Retrospective Cross-sectional Study

Objective: To evaluate the different non-surgical predominant pathologies in the emergency department of the Amissa Bongo regional hospital in Franceville, Haut-Ogooué. Materials and Methods: Using consultation registers and some medical records, we retrospectively studied the epidemiological and clinical profile of patients who consulted for a medical and non-surgical or gynaeco-obstetrical emergency, from 1 January 2018 to 31 December 2018. Results: During this period, 19597 patients consulted for a medical emergency at the Amissa Bongo regional hospital in Franceville in Haut-Ogooué (Gabon). This high score indicated that the majority of patients came from the different districts of the commune of Franceville and other departments of the province. Three periods of high attendance were distinguished: the long dry season (37.3%), the short rainy season (28.4%) and the long rainy season (24%), compared to the short dry season (10.3%). Infectious diseases were recurrent with 63.16%, and with 67% of cases, malaria (severe and simple) was more frequent. Non-infectious emergencies were also noted, such as diseases of the respiratory system (1791 cases = 24.81%), diseases of the digestive system (1028 cases = 14.24%), skin diseases (809 cases = 24.81%), cardiovascular diseases (800 cases = 11.21%), blood diseases (686 cases = 9. 5%), diseases of the urogenital system (588 cases = 8.14%), diseases of the locomotor system (510 cases = 7.06%), ENT diseases (451 cases = 6.24%), diseases of the glands and metabolism (296 cases = 4.10%), diseases of the nervous system and the senses (260 cases = 3.60%) Conclusion: Compared to non-infectious diseases, infectious and parasitic diseases are recurrent at CHRAB. They therefore require special attention from the health authorities of this hospital, and even of Gabon.

The 2019–2020 Rise in Lake Victoria Monitored from Space: Exploiting the State-of-the-Art GRACE-FO and the Newly Released ERA-5 Reanalysis Products

During the period 2019–2020, Lake Victoria water levels rose at an alarming rate that has caused various problems in the region. The influence of this phenomena on surface and subsurface water resources has not yet been investigated, largely due to lack of enough in situ measurements compounded by the spatial coverage of the lake’s basin, incomplete/inconsistent hydrometeorological data, and unavailable governmental data. Within the framework of joint data assimilation into a land surface model from multi-mission satellite remote sensing, this study employs the state-of-art Gravity Recovery and Climate Experiment follow-on (GRACE-FO) time-variable terrestrial water storage (TWS), newly released ERA-5 reanalysis, and satellite radar altimetry products to understand the cause of the rise of Lake Victoria on the one hand, and the associated impacts of the rise on the total water storage compartments (surface and groundwater) triggered by the extreme climatic event on the other hand. In addition, the study investigates the impacts of large-scale ocean–atmosphere indices on the water storage changes. The results indicate a considerable increase in water storage over the past two years, with multiple subsequent positive trends mainly induced by the Indian Ocean Dipole (IOD). Significant storage increase is also quantified in various water components such as surface water and water discharge, where the results show the lake’s water level rose by ∼1.4 m, leading to approximately 1750 gigatonne volume increase. Multiple positive trends are observed in the past two years in the lake’s water storage increase with two major events in April–May 2019 and December 2019–January 2020, with the rainfall occurring during the short rainy season of September to November (SON) having had a dominant effect on the lake’s rise.

Effect of Planting Density and K2O:N Ratio on the Yield, External Quality, and Traders' Perceived Shelf Life of Pineapple Fruits in Benin

Quality, shelf life, and yield of a pineapple fruit are the important attributes for the producers and customers in the pineapple value chain of Benin, whereas poor quality, short shelf life, and low yield are the main constraints. We quantified the effects of planting density and K2O:N fertilizer ratio on the pineapple yield, external quality, and perceived shelf life in four on-farm experiments with cv. Sugarloaf in Benin; two experiments were installed in the long rainy season and two in the short rainy season. A split-plot design was used with the planting density as the main factor at three levels: 54,000, 66,600, and 74,000 plants.ha−1. The K2O:N ratio was a subfactor with three levels: K2O:N = 0.35 (farmers' practice), K2O:N = 1, and K2O:N = 2. The results showed that both factors had no effect on the crop development variables (such as the number of functional leaves and D-leaf length) at the moment of flowering induction. The planting density had no effect on the total weight per fruit, infructescence weight, total fruit length, infructescence length, crown length, or the fruit shelf life as perceived by traders. The yield increased from 54.9–69.1 up to 90.1 t.ha−1 with an increase in the planting density. The yield increase was not at the expense of the fruit weight. Increased K2O:N ratio led to a higher fruit weight whereas the fruit length was not affected. The shelf life of fruits produced at a K2O:N ratio of 1 and as perceived by traders was 6 days longer than that of fruits produced at a ratio of 0.35 (farmers' practice). Based on these results, we suggest the fresh pineapple farmers in Benin to use a combination of 66,600 plants.ha−1 with a K-fertilization scheme based on a K2O:N ratio of 1 to meet the expectation of both producers and customers in terms of fruit yield and fruit quality.

Assessment of Sediment and Nutrient Losses from Forest, Pasture, Tea and Cropped Farms along the Nyondo River Basin

The widespread poor agricultural practices and ancient technologies continuously aggravate erosion of sediments and soil nutrients from delicate terrains at the major catchments of water shades. The ongoing study is assessing soil and nutrient losses in the four major land use covers (forest, pasture, tea and maize farms) in the upper catchment of Nyondo River Basin. The study sites in the upper catchment of Nyondo River Basin are densely populated and receive bimodal rains that support agriculture which is the main economic activity supporting livelihoods of the communities in the region. The experiment is laid in a randomized complete block design (RCBD) with each of the land use covers replicated 3 times with erosion traps mounted on 150 m2 plots. First data set was collected during the short rainy season of 2019 and long rainy season of 2020, with subsequent data collection continuing up to the short rainy season of 2021. Preliminary results showed that soil and nutrients were significantly lost in maize fields (p=0.05), forest cover was the least vulnerable while pasture cover had the highest surface runoff. Nutrient concentrations in the eroded sediments (p=0.05) were significantly higher than those that remained in maize plot while forest and tea fields registered comparable effectiveness in reducing both soil and nutrient losses, seasons notwithstanding. Pasture and maize fields had the highest water loss due to low infiltration rate and were also vulnerable to sediment and nutrients loss through surface runoff. The information will be used to inform and advise stake holders on land use policies geared towards attainment of sustainable agriculture and water quality in Nyondo and areas with similar landscapes and agricultural practices. Keywords: Erosion; Sediment; Nutrients; Land use

Effect of Plant Population on Yield of Selected Maize (Zea mays L.) Varieties in Mwea and Bura in Kenya

The objective of the study was to determine the effect of plant population on the growth and yield of maize. The study was conducted during the short rainy season of December 2018 and April 2019 in Mwea, Kirinyaga County and Bura, Tana River County, in Kenya. An experiment was set in a split-split plot design with three replications. Five selected maize (Zea mays) varieties commonly grown in these areas namely: Pioneer, DH04, Sungura, SC Duma and DH02 were grown under three plant population densities namely: 53,333, 66,666 and 88,888 plants ha-1 under irrigated conditions. Cob length, ear height, plant height, above ground biomass and grain yield data was collected. Plant population had significant effects on the grain yield and yield components of the selected maize varieties. The plant population of 53,333 plants ha-1 gave significantly higher above ground biomass in Mwea than population of 88,888 plants ha-1, though not significantly different from population of 66,666 plants ha-1. In Bura, the plant population of 88,888 plants ha-1 gave significantly higher above ground biomass than that of 66,666 and 53,333 plants ha-1 respectively. An increase in plant population reduced the grain yield of the selected maize varieties but increased the above ground biomass of the varieties.

Combining SIF, reflectance, and leaf scale measuremnts to assess the effcets of interannual changes in winter rainfall on tree physiology during the following summer drought period in a dry Mediterranean pine forest

&lt;p&gt;Dry Mediterranean forests are characterized by a short rainy season followed by a long dry period with high temperatures and radiation levels. These ecosystem are also exposed to large interannual variations in precipitation. Taking advantage of contrasting rainfall years, we investigated the opportunistic nature of pine trees in this region.&amp;#160; In our study site (the Yatir forest) mean annual precipitation is 288 mm, but it was 220 and 420 mm in the hydrological years 2018/19 and 2019/20, respectively. We used fluorescence measurements at the leaf, tower, and satellite scales, together with reflectance indices and eddy covariance measurements to assess the physiological response in the dry stressful season in these contrasting years.&lt;/p&gt;&lt;p&gt;The results showed that following a low rainfall season, soil moisture contes (SWC) reaches the 16% threshold of no traspirable water in spring, followed by larg decrease in carbon uptake and quantum yield of photosynthesis and the activation of protection mechanisms, such as decrease in chlorophyll content, large NPQ, and drop in the chlorophyll to cartenoid ratio (CCI index, obtained from canopy reflectance). Following the high rainfall year, the active season is extended (as indicated also by the satellite data), but even after the SWC threshold is reached, and mid-day VPD reaches ~5 KPa), carbon uptake continues, the amount of energy allocated to photochemistry remains high (high Fv/Fm and Y(II) levels), without the onset of protective mechanisms: No decrease in leaf chlorophyll and in NPQ, or decrease in CCI. We hypothesize that the opportunistic response of the dry-land forest must rely on yet unidentified water storage outside the root zone (e.g. deep soil pockets within the bedrock, or within the plants), which allow the plant to maintain high, with the only apparent adjustment reflected in shift of activity to early morning hours, when VPD is still low but the PAR levels are sufficiently high.&lt;/p&gt;

Antifungal activity of some alternative control against mango anthracnose in Senegal

Mango production in the South of Senegal is exposed to intensive rainfall from late May to October, with high temperature and moisture levels. These conditions are conducive for the development of anthracnose caused by Colletotrichum gloeosporioides (sensu lato) and leading to an absolute necessity for adequate control measures for good quality mango production. Anthracnose disease causes both pre- and postharvest fruit spots and fruit rot as well as premature fruit drop. The purpose of this study was to test the efficacy of several fungicide alternatives (fertilizers and biological control agents) against mango anthracnose in Senegal comparatively to standard fungicides. Field trials were set up in contrasting climates conditions and involved three orchards in the Northern part of the country with a short rainy season and dry climate over 9 to 10 months a year and three other orchards in the Southern part of Senegal with in a humid tropic environment. No anthracnose was recorded in the orchards in northern Senegal. In the south, in contrast, the disease was actual. Among the treatments tested for the control of anthracnose, Sodium molybdate were found effective after fungicides (azoxystrobin and thiophanate methyl). All the alternative treatments to fungicides provided a statistically significant control to the disease as compared to the control