Agriculture

Since the era of the Green Revolution, Agricultural production worldwide experienced much efficiency with a remarkable aim to eradicate threats of food insecurity. This breakthrough was anchored on science and technology. Among the interventions this era saw to date were the use of fertilizers and pesticides in our day-to-day farming activity to boost yield and control pests/diseases. The study assessed farmers’ knowledge in the use of Agrochemicals given their environmental effects such as on water bodies, occupational hazard and safety, disposal, and storage regarding product use. Questionnaires were administered to farmers cultivating vegetables, food, and cash crops under Open-field and Greenhouse managements in respective Production Specification; Organic and Inorganic productions. The study revealed that 85% of respondents who cultivated cash crops such as Cocoa and Rubber heavily relied on the use of inorganic fertilizers and pesticides. 35.40%, 32.74%, and 19.47% of respondents disposed of Agrochemical containers using Pit burial, Burn/Incinerate, and Indiscriminate methods, respectively, while 12.39% used ecological (biodegradable) materials. 92.7% of the respondents had knowledge about perilous consequence and yet didn't garment recommended protective apparels during application. It was concluded and recommended that the necessity of Agrochemical for pest, disease and weed control were unavoidable in the smallholder farming business in Ghana, despite the gradual rise of inorganic fertilizer and Integrated Pest Management control products. However, needful actions such as Government policy on educational campaign/programs must be intensified. to help appropriately redress misapplications and chemical residue on fresh food produce.

The regular maintenance of the fields and harvesting of the pods had in itself made it possible to maintain a good sanitary state of the Congolese plantations. Black rot and mirid diseases were still under control at that time. The plantations managed by the planters under the supervision of the "CABEN" Company, Cacaoyère de Bengamisa, were well maintained and monitored. However, in recent years, farmers, especially those in the Bengamisa cocoa zone, have observed their production to be declining.In order to accurately determine the level of this disease in this zone, where abnormal production losses have been reported, observations were carried out in the cocoa farms at the Kisangani, Kapalata and Yangambi posts in the Banalia Territory in the Democratic Republic of Congo "DRC".Weekly passages during which pods affected by black rot and healthy pods were counted revealed very high and increasing levels of infection over two successive harvest seasons (2018 and 2019) (i.e. a growth rate of 17.5 in Kisangani, 14.08 in Kapalata and 9.25 in Yangambi). These rates are similar to those recorded in countries where Phytophtora megakarya, a species known for its aggressiveness, regularly occurs. This serious disease becomes more important in 2019, which evokes the evolution of the latter from year to year. However, it remains understood that the environmental conditions created by the demotivation of coffee and cocoa growers from 1980 onwards, combined with the lack of maintenance of orchards, would have favoured a rapid emergence of black rot. Lasiodiplodia theobromae is becoming a major constraint to cocoa production in DRC. This study is the first to report the effects of L. theobromae causing the decline of cocoa pods in DRC.

Incidence of guava orchards decline was surveyed in different localities of District Larkana. The samples were collected from trees showing clear disease attack. Pure culture was obtained by transferring single spore/ piece of mycelium to PDA plates. Identification was made by using microscopic characters and taxonomical keys. The fungal pathogens responsible for guava orchard decline were fusarium oxysporium f.sp. psidii. and Botryodiplodia theobromae.

Soil, plant and indicators are the main criteria to recognize the function of natural ecosystems and evaluate their potentials. Rangeland ecosystem contains various patches with different functions. The structural and functional characteristics of fertilized patches in Bozdaghy rangeland, in North-Khorasan Province was measured and analyzed in this study. A group of measurable and simple indices of landscape function analysis (LFA) methods were used to evaluate these characteristics. The data were measured from seven land unit which is developed from overlaying of geology map on the dem and slope map. In this research the length and width of ecological patches by the forms of Grass, forb, shrub and bare soil with litter measured. Also we measured 11 soil surface parameters on three, 50 meters transects in the seven mentioned regions. These 11 parameters are belonging to 3 major attributes of soil: Stability, infiltration and nutrients. Statistical analysis of data using the software landscape function analysis, carried. Using multivariate analysis of variance and Duncan's test, functional characteristics associated with each of the land units were studied. Stability, infiltration and nutrients indices of Shrub, forbs and Grass showed significant differences in seven land unit (p<0.05). shrub was most important ecological indicators of areas.

This paper examines agroforestry as a panacea to food insecurity in Nigeria. Agroforestry is defined as a combination of agriculture and forestry, resulting in better management of natural resources and sustainable use of land. It is the planting of trees among crops so as to help sustain environments and livelihoods. The practice of agroforestry is a dynamic, ecologically based, natural resources management system that, through the integration of trees on farms and in the agricultural landscape, diversifies and sustains production for increased social, economic and environmental benefits for land users at all levels. It has some characteristic features which could either be intentional or interactive. Intentional agroforestry is designing and managing combinations for a planned result. Intentional agroforestry can be intensive or integrated. In practice of intensive agroforestry, components are managed to maintain production and environmental benefits. Integrated agroforestry is a blend of agriculture, forestry and environmental science. Interactive agroforestry is designed to minimize negative and maximize positive interactions between trees, other crops, livestock and humans. The goal is to enhance the production of more than one component at a time while providing for environmental benefits. The paper discusses some characteristic features of agroforestry as either intentional or interactive. Silvopastoral, agrisilviculture and agrisilvopastoral are discussed as types of agroforestry systems while alley cropping, forest farming, riparian buffer strips and windbreaks or shelterbelts are described as the most common or popular agroforestry practices. Some limitations to agroforestry practices are also mentioned in the paper.

An innovative approach incorporated to predict large quantity of rose water extraction through distillation process in a solar still under the climatic conditions of Coimbatore, India (11?.00 N, 77 ? E). The rose water extraction to utilize the process is performed to increase the large yield rate by coupling the still with the concentrating assembly. The hourly rose essence yield from the still and efficiency are recorded. In normal evaporation process of the still requires more time to evaporate the content in the still which spends 1½ hour for evaporation. But in this type of still concentrator plays a major role for evaporating the content within a short duration of time. It requires only 10 minutes for evaporation. Thus this type of still is very much support to extract the rose essence without any loss of smell. The conventional solar still loses its smell even before the evaporation process.

Different concentrations of vermicompost such as 25% (25kg vc: 75 kg red soil), 50% (50kg vc:50 kg red soil), 75% (75kg vc:25 kg red soil), and 100% (100 kg vc) produced by earthworm, Eudrilus eugeniae, were added to red soil in polythene bags. Maize plants (Zea mays L.) were grown on vermicompost-enriched soil for 90 days. The plants were harvested at the end of 90 days and the kernels were collected. In the present investigation the number of kernels was counted; the length, breadth, and circumference of kernels were measured; the weight of kernel and total weight of all kernels were calculated. The maximum kernel number of 598.55/corn and the highest length of 1.71cm/kernel were noticed in the plants cultivated on 75% vermicompost concentration whereas the maximum kernel breadth of 1.40cm/kernel, circumference of 3.07cm/kernel, weight of 0.41 gm/kernel and total weight of all kernels (232.43gm/corn) were noticed in the plants grown on 50% vermicompost concentration. At the same time minimum kernel number of 69.42/corn, low kernel length of 0.80cm/kernel, breadth of 0.60cm/kernel, circumference of 2.02cm/kernel, weight of 0.08gm/kernel and total weight of all kernels (5.55gm/corn) were found in the control plants. The present investigation clearly revealed that the addition of vermicompost to soil greatly enhanced the kernel yield in maize.

In India maize ranks fifth position in area and fourth in production among the major cereals grown. Being a C4 plant and having very high yield potential, it is called queen of cereals. One of the main deterrents to high grain yield in maize is its susceptibility to several diseases. Of 112 diseases of maize reported so far from different parts of the globe, 65 are known to occur in India. Banded leaf and Sheath blight (BLSB) is one of them caused by most widespread, destructive and versatile pathogen Rhizoctonia solani f. sp Sasakii (teleomorph: Corticium sasakii, syn Thanatephorus cucumeris) which claims significant yield loss (Saxena, 2002). It was first reported by Bertus (1927) in Sri Lanka under the name Sclerotial disease. The epidemics of this disease were first reported in the warm and humid foot hills of Himachal Pradesh by Thakur et al. (1995). Singh and Sharma (1976) recorded a loss in grain yield in the range of 11 to 40 per cent due to this disease while Lal et al. (1985) reported a reduction to the extent of 97.4 per cent in severe condition. A range of 25 to 30°C (Ahuja and Payak, 1981) coupled with an average relative humidity of 90-100% (Ahuja and Payak, 1981) is most suitable for development of this disease. These conditions prevail in the plains of N.E. region of India during the months of July-August, a time when the crop is in vulnerable growth stage. In India the disease was first recorded in the Tarai (foot hill plain areas) region of Uttar Pradesh (Payak and Renfro, 1966). Maize plant is affected by as many as 61 diseases, out of which 16 have been identified a major ones which occur both in tropical and temperate regions of India (Sharma and Payak, 1986). Among these, banded leaf and sheath blight (BLSB) incited by Rhizoctonia solani is gaining economic importance. Grain yield loss, depending on severity varies between 11 to 40 per cent (Singh and Sharma, 1976). Now banded leaf and sheath blight is considered as one of the major diseases of Maize (Payak and Sharma, 1985).

Any experiment should be compatible with scientific approaches such as statistical reliability, rationality, internal and external validity, generalizability, and other specific criteria related to the subject, at the laboratory level or field level. Hence, planning a design to accomplish those approaches is critical, and selecting an appropriate model accordingly to acquire basic principles of design would make the experiment more precise. Straightforward designs of CRD, RCBD, and LSD, and complicated designs of IBD, Factorial experiments, Split-plot designs, and Lattice designs are discussed here. Consequently, the researcher can decide the appropriate experimental design.

Climate change and climate variability and financial institutions’ unwillingness to give loans have resulted in many farmers losing confidence in dry land agriculture. Traditional crop insurance methods have also presented challenges due to the risk related to adverse selection and moral hazard resulting in high transaction costs for individual assessment. This study focused on developing a weather index based insurance model that uses artificial neural networks to estimate potential evapotranspiration (ETO) and consequently yield reduction due to moisture stress. Weather data from 2012 to 2015 for Kutsaga area in Harare was used for the study. Seasonal weather data were used as input data to the first model to predict the ETo. The output ETO and effective rainfall data together with the crop factor (Kc), yield reduction factor (Ky), root zone depth (RzD) and root zone moisture (RzM)were used as input data for the second network to compute % yield reduction. Data for maize for the 2012-13 growing season was used for training the network and validating the estimated ETO and % yield reduction. The estimated ETO compared very well with the calculated values with R2 values of above 0.84. The estimated yield reduction % indicated even high accuracies with R2 values of above 0.91. The 2014-2015 growing season resulted in crop loss due to mid-season dry spells and the model predicted a 100% crop loss which means the farmer had to be compensated for the value equivalent to cost of inputs. The model has got potential to be used by insurance companies using weather based data and, with mobile banking transaction costs can be reduced.Climate change and climate variability and financial institutions’ unwillingness to give loans have resulted in many farmers losing confidence in dry land agriculture. Traditional crop insurance methods have also presented challenges due to the risk related to adverse selection and moral hazard resulting in high transaction costs for individual assessment. This study focused on developing a weather index based insurance model that uses artificial neural networks to estimate potential evapotranspiration (ETO) and consequently yield reduction due to moisture stress. Weather data from 2012 to 2015 for Kutsaga area in Harare was used for the study. Seasonal weather data were used as input data to the first model to predict the ETo. The output ETO and effective rainfall data together with the crop factor (Kc), yield reduction factor (Ky), root zone depth (RzD) and root zone moisture (RzM)were used as input data for the second network to compute % yield reduction. Data for maize for the 2012-13 growing season was used for training the network and validating the estimated ETO and % yield reduction. The estimated ETO compared very well with the calculated values with R2 values of above 0.84. The estimated yield reduction % indicated even high accuracies with R2 values of above 0.91. The 2014-2015 growing season resulted in crop loss due to mid-season dry spells and the model predicted a 100% crop loss which means the farmer had to be compensated for the value equivalent to cost of inputs. The model has got potential to be used by insurance companies using weather based data and, with mobile banking transaction costs can be reduced.