soil fertility
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Geoderma ◽  
2022 ◽  
Vol 409 ◽  
pp. 115597
Sasirin Srisomkiew ◽  
Masayuki Kawahigashi ◽  
Pitayakon Limtong ◽  
Owat Yuttum

2022 ◽  
Vol 210 ◽  
pp. 105910
Sonia Boudjabi ◽  
Haroun Chenchouni

2022 ◽  
Vol 216 ◽  
pp. 105250
Tiago R. Tavares ◽  
Abdul M. Mouazen ◽  
Lidiane C. Nunes ◽  
Felipe R. dos Santos ◽  
Fábio L. Melquiades ◽  

Revista CERES ◽  
2022 ◽  
Vol 69 (1) ◽  
pp. 102-112
Erivelton Gonçalves da Cunha ◽  
Rebyson Bissaco Guidinelle ◽  
Otacilio José Passos Rangel ◽  
Renato Ribeiro Passos

Hamza Abubakar ◽  
Abdullahi Muhammad ◽  
Smaiala Bello

The Boolean Satisfiability Problem (BSAT) is one of the most important decision problems in mathematical logic and computational sciences for determining whether or not a solution to a Boolean formula.. Hopfield neural network (HNN) is one of the major type artificial neural network (NN) popularly known for it used in solving various optimization and decision problems based on its energy minimization machinism. The existing models that incorporate standalone network projected non-versatile framework as fundamental Hopfield type of neural network (HNN) employs random search in its training stages and sometimes get trapped at local optimal solution. In this study, Ants Colony Optimzation Algorithm (ACO) as a novel variant of probabilistic metaheuristic algorithm (MA) inspired by the behavior of real Ants, has been incorporated in the training phase of Hopfield types of the neural network (HNN) to accelerate the training process for Random Boolean kSatisfiability reverse analysis (RANkSATRA) based for logic mining. The proposed hybrid model has been evaluated according to robustness and accuracy of the induced logic obtained based on the agricultural soil fertility data set (ASFDS). Based on the experimental simulation results, it reveals that the ACO can effectively work with the Hopfield type of neural network (HNN) for Random 3 Satisfiability Reverse Analysis with 87.5 % classification accuracy

2022 ◽  
Vol 14 (2) ◽  
pp. 9
Daniel M. Kalala ◽  
Victor Shitumbanuma ◽  
Benson H. Chishala ◽  
Alice M. Mweetwa ◽  
Andreas Fliessbach

For studying the effect of soil fertility management practices on N mineralization, urease activity and maize yield, replicated field trials were established in 2015 at Misamfu and Msekera agricultural research stations (ARS) representing two geo-climatic regions of Zambia. The soil at Msekera ARS is a sandy clay loam (SCL) from a Paleustult, while that at Misamfu is a loamy sand (LS) from a Kandiustult. The field trials had three categories of treatments namely legumes, traditional and conventional. The legumes group consisted of researcher-recommended legume-cereal intercrop systems of maize with Cajanus cajan, Crotalaria juncea and Tephrosia vogelii in combination with compound D (10% N, 20% P2O5, 10% K2O) and urea (46% N) at the recommended rate (200 kg ha-1) and half of the recommended rate (100 kg ha-1). Composted cattle manure and Fundikila, a special plant biomass management technique, were the inputs under the traditional category. The conventional category consisted of a treatment to which only chemical fertilizer was applied. Urease activity was determined in surface soil samples (0-20 cm) collected from the field trials after 3 years. For N mineralization, a laboratory incubation study was conducted over 13 weeks. For the laboratory incubation, an additional treatment to which no input was applied was included as control. Application of organic inputs significantly increased the potentially mineralizable N (No) by 127% to 256% on the LS and by 51% to 131% on the SCL in comparison to the control. Similarly, the cumulative N mineralized (Ncum) was twice or thrice higher where organic inputs had been applied in comparison to the control. The No followed the order traditional > legumes > conventional > control, while the mineralization rate constant (k) followed the order legumes > conventional > traditional > control on both soils. The rate of N mineralization was significantly higher on the LS than the SCL. Higher rates of chemical fertilizer resulted in high Ncum and higher maize yield. Maize yield was significantly and positively correlated to Ncum, but inversely correlated to the amount of applied N that was mineralized (%Nmin). Urease activity was stimulated by application of organic inputs and suppressed by higher rates of chemical fertilizers. The type of organic inputs; the rate of chemical fertilizers; and soil texture are factors influencing N mineralization and maize yield. Urease activity was largely influenced by the rate of chemical fertilizer, but not the type of organic inputs or soil texture.

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