SummaryResponse of wheat to fertilizer-P on soils low and medium in available P increased with increasing doses up to 26 kg P/ha; responses were proportionately greater on medium-P soils. Application of 39 kg P/ha increased the response slightly on low-P but decreased it drastically on medium-P soils. The relatively small response on low-P soils may be due to fixation of fertilizer-P. The results indicate that the maximum response to fertilizer-P may be obtained only when P fixing capacity of the soil is satisfied so that sufficient P for the crop remains in the soil solution. The results of this investigation suggest that fertilizer should be applied on the basis of soil test data of individual fields instead of following regional recommendations.

Objective: Characterise the diagnostic and prognostic value of muscle MRI patterns as biomarkers in a genetically heterogeneous nemaline myopathy (NM) patient cohort. Methods: Modified Mercuri scoring of lower limb MRI in genetically characterised NM patients referred to the highly specialised service for congenital myopathies at Great Ormond Street Hospital. Findings were compared to clinical data and MRI patterns derived from collated published data. Results: Twenty-seven patients with MRI were identified (8 NEB-NM, 13 ACTA1-NM, 6 TPM3-NM). NEB-NM demonstrated sparing of the thigh. ACTA1-NM demonstrated diffuse thigh involvement, notable in the vasti, sartorius and biceps-femoris, with relative adductor and gracilis sparing. TPM3-NM demonstrated diffuse thigh involvement notable in biceps-femoris and adductor magnus with relative rectus femoris, adductor longus and gracilis sparing. In the lower leg, the soleus and tibialis anterior are notably involved in all three genotypes. NEB-NM and ACTA1-NM demonstrated relative gastrocnemii and tibialis posterior sparing, while TPM3-NM showed significantly more tibialis posterior involvement (P =< 0.05). Comparison of involvement patterns with literature datasets highlighted preferential adductor and gracilis sparing in our ACTA1-NM cohort, consistent tibialis posterior involvement in our TPM3-NM cohort and a distinct MRI pattern from those derived from other NM genotypes and congenital myopathies. Greater tibialis anterior involvement correlated with foot drop (P = 0.02). Greater tibialis anterior and extensor hallucis longus involvement correlated with worse mobility (P =< 0.04). Interpretation: This is the widest NM MRI data set described to date; we describe distinct muscle involvement patterns for NEB-NM, ACTA1-NM and TPM3-NM which may have utility as diagnostic and prognostic biomarkers and aid in genetic variant interpretation.

In this paper, we study the phenomenological consequences of two-zero textures of inverse neutrino mass matrix(M −1 ν ). In M l and MD diagonal basis, zero(s) in heavy right-handed neutrino mass matrix correspond to zero(s) in inverse neutrino mass matrix(M −1 ν ). There are fifteen possibilities to have two-zero textures of M −1 ν . In order to study complete phenomenology of the model, we confront these textures with the latest neutrino data including large mixing angle(LMA) and dark -large mixing angle(DLMA) degenerate solutions, later of which originates if neutrinos exhibit non-standard interactions with matter. Out of fifteen possibilities only seven(B2, B4, C1, C3, D1, D2, E1) are found to be in consonance with LMA and/or DLMA solutions. In general, we find that the textures for which (M −1 ν )11 = 0 are disallowed. The textures B2, B4, C1, C3 and D2 textures are found to be allowed under both LMA and DLMA descriptions. Also, these textures are necessarily CP violating. However, the textures which are not consistent with DLMA paradigm, for example D1 and E1, allow both CP conserving and violating solutions. The generic feature of the class of model discussed in the present work is the existence of neutrino mass hierarchy degeneracy in a particular texture.For example, if a texture is allowed by LMA solution with "X" neutrino mass hierarchy then, if DLMA is allowed, it is allowed with the same hierarchy "X". Interestingly, amongst all the seven texture, textures with (M −1 ν )23 = 0 are found to be either disallowed or are consistent with LMA(D1 and E1) description only. We have, also, obtained the implication of the model for 0νββ decay amplitude |Mee|. Except for textures D1 and E1, the predicted 3σ lower bound on |Mee| is O(10 −2 ) which is within the sensitivity reach of 0νββ decay experiments like SuperNEMO, KamLAND-Zen, NEXT, and nEXO. For example, the non-observation of 0νββ decay down to these high sensitivities will refute all the textures except D1 and E1. Furthermore, we have proposed a flavor model, based on discrete non-Abelian flavor group A4, wherein such textures of M −1 ν can be realized within Type-I seesaw setting.

The present investigation was carried out to fit Autoregressive Moving Average (ARIMA) models to arrive at a methodology that can precisely explain the fluctuations of area, production and productivity for wheat crop data in Gujarat state after checking the stationary condition. The data from year 1960−61 to 2012−13 were used for model fitting and forecasting five years ahead from the year 2012−13. The ARIMA models with different p, d and q were judged on the basis of auto correlation function (ACF) and partial auto correlation function (PACF) at various lags. Among different fitted ARIMA models, the final models were selected on the basis of significant autoregressive and moving average term, Akaike's Information Criterion (AIC), Schwartz-Bayesian Criterion (SBC), test of normality (Shapiro-Wilk test) and randomness of residual's (Run test) distribution. Among the ARIMA models, ARIMA (0, 1, 1) family model was found suitable to forecast the pattern of wheat area and production and ARIMA (1, 1, 0) was found suitable for forecasting of wheat productivity trend of Gujarat State. Forecasted values showed an increasing pattern in area, production and productivity of wheat in Gujarat State and predicted values for area, production and productivity of wheat in the year 2017−18 are 12989.2 hundred ha, 40296.9 thousand t and 3148.42 kg ha -1 respectively.