The farmers of hilly areas face severe fodder shortage in winter when they have only dry stalks of summer cereals. The study aimed to evaluate the adaptability of winter forage cereals (barley, oats, rye and triticale) and to quantify the suitable dose of nitrogen (0, 75,150 and 225 kg ha-1) for the assessment of bio-metric and qualitative characteristics of winter forage cereals (WFCs) at booting stage (BS) and milking dough stage (MDS) grown under temperate conditions of Rainfed Rawalakot, Kashmir, Pakistan. A two year (2017 and 2018) field trial was executed at research farm of the University of Poonch Rawalakot (latitude 33.51°N, longitude 73.45°E). Harvested forage then preserved as silage by adding Folic acid and Molasses as additives. The relationship among yield attributes with green fodder and dry matter yield was also determined through correlation analysis. Rye crop in conjunction with 225 kg ha-1 nitrogen out yielded more number of plants m-2, number of tillers m-2, plant height which led to the highest green fodder (55413 and 43542 kg ha-1) and dry matter yield (188471 and 12440 kg ha-1) during consecutive years (2017 and 2018). Whereas, oats cultivar performed better for fresh weight per plant, dry weight per plant and leaf area per plant. Qualitatively, preserved silage was assessed through crude protein (%) and crude fibre (%) contents. More crude protein contents were recorded for triticale crop at N3 level of N with use of molasses during both the years at both forage cutting stages (booting and milking dough). More crude fibre was noted in barley crop during both the years at control level of nitrogen fertilization on both booting and milking dough stage. The correlation analysis revealed direct interrelationship among yield attributes and fodder yield of winter forage cereals and thus indicating the need to supply nitrogen @ 225 kg ha-1 for improving biometric characteristics of WFCs.

In ensuring a cleaner and sustainable agricultural production which increases efficiency in the allocation of resources at the same time decreasing waste, this paper forecast yield and area share of maize in Zambia using the Error Correction Model. The aim is to offer an empirical approach in forecasting yield and planted area of maize which is prominent in conserving land use, energy, water, human capital and eminent resources in agricultural production. Zambia is a middle-income emerging country located in the Southern Sub-Sahara of Africa. The study focuses on maize, which is the staple food crop and hence a widely grown crop among farmers in the country. We use time series data for maize yield and area share in Zambia collected from FAO statistics. After all the tests, our results indicate that the area share and maize yield has no unit root and is stationary after first differencing, integrated in the first order I(1). Additionally, a unit increase of the area share of maize has 2% decrease of maize yield in the next season owed to excess stock, and price variability. We estimate the area share of maize to have an average growth of 764828 hectors while maize yield is estimated to have an average growth of 16597 hg/ha. Our findings also attest that to drive green and sustainable agricultural growth in Zambia, there is need to mitigate soil, water and air pollution emanating from the mining quarries and manufacturing industries, precisely for farmer situated near mining zones. This requires amendment of land allocation and dumping policies in farming ecological zones. As the current policies tend to be inefficient in ensuring green growth among farmers and the country as a whole. Thus, there is need to embrace new farming technologies from land preparations to efficient but cheaper crop storage facilities. There is also need to embolden the use of unexplored organic farming systems using compost which is safe, and substitute for chemical fertilizer in order to ensure high yield while conserving ecological zones in Zambia.

This critical review evaluates the challenges of agriculture sector faces by evaluating agriculture sector related to the government food security policies. During the 2019 period, agriculture sector only grew by 3.08% compared to the previous year, and became the second contributor to the GDP after industrial sector, due to growth in food crop production by -4.81%. Although the agricultural sector dominates employment and has the potential to reduce unemployment, it has not been supported by adequate human resources and even tends to degeneration because income is the lowest compared to other sectors. Another serious problem is that every year there is reducing between 150,000 to 200,000 hectares of land due to the change of function because of infrastructure development.\nAs an agrarian country, the welfare of farmers in Indonesia has also not changed much from year to year. Farmers Exchange Rate (NTP) in 2019 was 104.46, only an increase of 1.25% from the previous year. The low wage of farm laborers, limited land owned, and the selling price of agricultural products does not benefit to the farmers, making indicators of the farmer’s welfare is still low. With this phenomenon, Indonesia really needs to reform its governance in the agricultural sector, and restore the role of BULOG. Strengthening the role and function of Bulog will be able to maintain food price stability and motivate farmers\' interest to continue planting rice and various other food commodities

There is a need to sustainably manage the available water (Capsicum annuum). Therefore, a field experiment was carried out to investigate the agronomic response of pepper to aquaculture water. Dry season experiment was carried out using a Randomized Complete Block Design (RCBD) Experimental design. The treatments include; 50% Potential Evapotranspiration (PET) with fish pond water (T1), 100% PET with fish pond water (T2), and 100% PET with borehole water- control (ground water), (T0) and were replicated three times. Soil physico-chemical properties, soil water content, Pepper Agronomic parameters (growth and yield) were also determined. Results showed that the water quality of aquaculture water and ground water used for irrigating pepper was within the permissible limits when compared to standard. Also, Aquaculture water improves the soil physico-chemical and soil water content, which consequently led to improved growth and yield of pepper. The average plant height values were 59.00 cm, 37.50 cm, and 45.00 cm in treatments T2, T1 and T0, while girth diameter obtained in treatments T2, T1 and T0 were 11.45 mm, 10.49 mm and 9.06 mm, respectively. Similarly, the highest number of leaves, biomass and sweet pepper yield, root weight and Leave area index (LAI) were recorded in treatment, T2. Statistical analysis showed that agronomic parameters were significantly different (p<0.05) in all the treatments. The result provides useful information about the use of aquaculture water in improving the soil physico-chemical, growth and yield of pepper. This showed that in arears where water is limiting, aquaculture water could be used.

Wetlands are indispensable ecosystems and play a crucial role in the stability of their periphery ecosystems. However, wetlands need to be managed sustainably to ensure that not only the present but also the future benefits continue to accrue. As a result, this study proposes and validates a participatory pattern of sustainability management of wetlands. The sample of the study was 251 experts in the field, recruited to answer a questionnaire related to participatory management and the related factors. Data analysis in this study was performed through structural equation modeling using LISREL software. The results showed that economic, environmental, and socio-cultural mechanisms have significant and positive effects on participatory management of wetlands. Moreover, beneficiaries related factors such as consultation, motivation, relationships, and rights have significant and positive effects on the social, environmental, and economic mechanisms and consequently on participatory management of the wetlands under study.

Fluoride contamination has now become an emerging concern in agroecosystems. A diagnostic survey was conducted across the fluoride (F-) contaminated wetlands of Kuttanad, India with an aim to examine the influence of edaphic factors on F- concentration in soils. The (Inceptisols) predominantly sandy had a substantial percentage of clay and the soil characteristics such as bulk density (BD), moisture, temperature, pH, electrical conductivity (EC), cation exchange capacity (CEC) and organic carbon (OC) varied with soils. Similarly, the soil nutrients (NPK) and the oxides of Fe and Al as well as total sesquioxide differed with soils. Principal component analysis (PCA) revealed two distinct factors. PC1 accounted for 52.3% and second component PC2 for 12% of the variation in the profiles. Out of soil samples, 53% had a similar distribution of soil characteristics and F- concentration and are grouped together in PC1 while, the remaining 47% of the samples had a similar distribution of characteristics and are grouped together in PC2. Among the soil characteristics examined, silt content, pH, EC, CEC, OC, N and P had a significant (P<0.001) positive association along PC1 indicating that these factors are contributing to the augmentation of F- concentration in the wetlands of Kuttanad.

Leukaemia is a malignant disease characterized by the uncontrolled accumulation of abnormal white blood cells. Leukaemia is a fatal cancer. All blood cells arise in the bone marrow, which occupies the central cavity of the bone, via hematopoiesis. Acute leukaemia causes the fast deterioration of the patient, whereas chronic leukaemia is characterized by slow progression and maybe lymphocytic or myelogenous. A comparative analysis of different machine learning algorithms can be done to obtain the algorithm which can give the highest accuracy for a dataset which henceforth will help to detect if a patient is suffering from acute leukaemia or chronic leukaemia. In this paper, a thorough review done on algorithms implemented such as k-Means, Naive Bayes, SVM, logistic regression and XG-Boost.

Kefir is produced by the microbial activity of ketofil granules which are relatively stable and specific balance between lactic acid bacteria and yeast. Here, we determined the relationship between kefir flavor and microbial structure during 0-120 hours fermentation by 16S rDNA sequencing. Firstly, the content of flavor substances at different fermentation time was determined by GC-MS. It was found that 72 h was the best fermentation time. Secondly, among the operational taxa (OTUS) obtained by 16S rDNA sequencing, the number of OTUs at 72h is the largest. In addition, we found that Lactobacillus, Streptococcus and Bacillus were the dominant bacteria in the fermentation process. Streptococcus was the main strain in the early stage of fermentation, and Lactobacillus was the main strain in the late stage of fermentation. In addition, these changes in microbial community structure are associated with changes in flavor substance levels. Diversity analysis showed that the microbial structure of fermentation system was the most complex at 72h. Our results illustrate the dynamic changes of microorganisms in kefir fermentation and the potential relationship between kefir fermentation and flavor substances. The results showed that probiotics were the main microorganisms in kefir system after a certain fermentation time. These results can be used to optimize the fermentation process, flavor and health-related characteristics of these foods and other fermented foods.

To detect RAPD-DNA markers for four Nigella sativa cultivars treated with different doses of gamma radiations, we used seven RAPD primers. Three doses; 0 Gy (as control treatment), 20 Gy and 40 Gy were used. Each genotype revealed different responses on the molecular level to gamma irradiation. The total number of polymorphic fragments (PF) and total specific markers (TSM) ranged from 11 fragments as least value for Elmenia cultivar to 37 fragments as highest value for Turkey1 cultivar. All the total specific markers (TSM) were positive (appeared bands) and negative (disappeared bands) markers in all cultivars with most of the seven arbitrary primers used.

Meat is one of the main components of a balanced human diet; however, some studies have linked meat consumption to an increased risk of cardiovascular diseases because of its fatty acid (FA) composition. The aim of this study was to evaluate the effect of a panel of single-nucleotide polymorphisms (SNPs) on the FA composition of Mexican beef meat. One hundred six Longissimus muscle samples were collected and genotyped according to a literature-based SNP panel. Seven SNPs showed effects on FA concentration and composition. Novel associations were found for markers located at the Myocyte enhancer factor 2C (MEF2C), Hepatocyte Nuclear Factor 4 Alpha (HNF4A) and Solute Carrier Family 2 Member 4 (SLC2A4) genes. The marker ss38329156 located at MEF2C was associated with significant reductions in the concentrations of four saturated fatty acids (C14:0, C15:0, C16:0 and C17:0), while the ss61961144 marker located at HNF4A had significant effects in terms of increasing two monounsaturated fatty acids (MUFAs) (C16:1 and C18:ln9c). While these significant associations need to be validated further, these markers are potential tools for breeding strategies to control the FA composition of meat and improve the nutritional quality of beef.