Transcriptional Network Involved in Drought Response and Adaptation in Cereals

Drought is the major abiotic stress in many wheat environments, decreasing grain yields and farmer’s income. Finding ways to improve drought tolerance in wheat is therefore a global effort. Transcription factors (TFs) play important roles in drought tolerance by stimulating plant’s protective genome activities in response to heat and water limitation. TFs are specialized proteins which can bind to specific DNA elements in gene promoters and modulate gene expression in response to various external and internal stimuli. Thus TFs is a crucial part of plant signal transduction pathway mediated by signal receptors, phytohormones and other regulatory compounds. The activities of TFs are closely related to their structure, and their binding specificity is determined by the homo-/hetero-dimerization of TFs. The expression of downstream genes may produce a subset of TFs or regulate other functional proteins involved in physiological drought adaptation. Thus, the hierarchic regulations of TF activities, downstream gene expression and protein–protein interaction comprise a complex regulatory network, which participates in drought response and adaptation in cereal crops. Basic mechanisms of this regulatory network have been described, but more insight is needed to find new tools for enhancing cereals’ adaptation to drought stress

Nutrient Management for Higher Productivity of Swarna Sub1 Under Flash Floods Areas

Two field experiments were conducted at Regional Agricultural Research Station, Tarahara, Nepal during 2012 and 2013 to determine the effect of agronomic management on growth and yield of Swarna Sub1 under flash floods. The first experiment was laid out in a split plot design with three replications; and four different nutrient combinations at nursery as main plots and three age groups of rice seedlings as sub plots. The second experiment was laid out in a randomized complete block design and replicated thrice; with three post flood nutrient doses at six and 12 days after de-submergence (dad). The experiments were complete submerged at 10 days after transplanting for 12 days. The survival percentage, at 21 dad, was significantly higher in plots planted with 35 (90.25%) and 40 (91.58%) days-old seedlings compared to 30 days-old seedlings (81.75%). Plots with 35 days-old seedlings produced 5.15 t ha-1 with advantage of 18.83% over 30 days-old seedlings. Plots with 100-50-50 kg N-P2O5-K2O/ha at nursery recorded the highest grain filling of 79.41% and grain yield of 5.068 t/ha with more benefit. Post flood application of 20-20 N-K20kg/ha at 6 dad resulted in higher plant survival and taller plants, leading to significantly higher grain yield of 5.183 t/ha and straw yield of 5.315 t/ha. Hence, 35-40 days old seedlings raised with 100-50-50 kg N-P2O5-K2O /ha in nursery and the additional application of20-20 kg N-K2O /ha at 6 dad improved plant survival and enhanced yield of Swarna Sub1 under flash flood conditions. The practice has prospects of saving crop loss with getting rice yield above national average yield leading to enhanced food security in the flood prone areas of Nepal

Macronutrient application rescues performance of tolerant sorghum genotypes when infected by the parasitic plant striga

Background and Aims Infection by the hemi-parasitic plant Striga hermonthica causes severe host plant damage and seed production losses. Increased availability of essential plant nutrients reduces infection. Whether, how and to what extent it also reduces striga-induced host plant damage has not been well studied. Methods The effects of improved macro- and micronutrient supply on host plant performance under striga-free and infected conditions were investigated in glasshouse pot assays. One striga-sensitive and two striga-tolerant genotypes were compared. Plants growing in impoverished soils were supplied with (1) 25 % of optimal macro- and micronutrient quantities, (2) 25 % macro- and 100 % micronutrients, (3) 100 % macro- and 25 % micronutrients, or (4) 100 % macro- and micronutrients. Key Results Photosynthesis rates of striga-infected plants of the sensitive genotype increased with improved nutrition (from 12.2 to 22.1 μmol m−2 s−1) but remained below striga-free levels (34.9–38.8 μmol m−2 s−1). For the tolerant genotypes, increased macronutrient supply offset striga-induced photosynthesis losses. Striga-induced relative grain losses of 100 % for the sensitive genotype were reduced to 74 % by increased macronutrients. Grain losses of 80 % in the tolerant Ochuti genotype, incurred at low nutrient supply, were reduced to 5 % by improved nutrient supply. Conclusions Increasing macronutrient supply reduces the impact of striga on host plants but can only restore losses when applied to genotypes with a tolerant background

Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a review

Over the past two decades soil spectroscopy, particularly, in the infrared range, is becoming a powerful technique to simplify analysis relative to the traditional chemical methods. It is known as a rapid, cost-effective, quantitative and eco-friendly technique, which can provide hyperspectral data with narrow and numerous wavebands, both in the laboratory and in the field. In this context, the present article reviews the recent developments in mid and near infrared techniques coupled with chemometrics and machine learning tools in addition to the preprocessing transformations and variable selection strategies to diagnose soil physical and chemical properties. Both spectral techniques demonstrated a good ability to provide accurate predictions of specific properties. Moreover, the MIR spectroscopy outperformed NIR for the estimation of most indicators used for fertilizers recommendation. Herein, a detailed overview on the opportunities and challenges that soil spectroscopy offers as efficient diagnostic tool in soil science was provided

Optimizing setup of scan number in FTIR spectroscopy using the moment distance index and PLS regression: application to soil spectroscopy

Vibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results. This study aimed at optimizing one of the essential settings during the acquisition of FTIR spectra (viz. Scans number) using the standardized moment distance index (SMDI) as a metric that could trap the fine points of the curve and extract optimal spectral fingerprints of the sample. Furthermore, it can be used successfully to assess the spectra resemblance. The study revealed that beyond 50 scans the similarity of the acquisitions has been remarkably improved. Subsequently, the effect of the number of scans on the predictive ability of partial least squares regression models for the estimation of five selected soil properties (i.e., soil pH in water, soil organic carbon, total nitrogen, cation exchange capacity and Olsen phosphorus) was assessed, and the results showed a general tendency in improving the correlation coefficient (R2) as the number of scans increased from 10 to 80. In contrast, the cross-validation error RMSECV decreased with increasing scan number, reflecting an improvement of the predictive quality of the calibration models with an increasing number of scans

Combining host plant defence with targeted nutrition: key to durable control of hemiparasitic Striga in cereals in sub-Saharan Africa?

Host plant defence mechanisms (resistance and tolerance) and plant nutrition are two of the most widely proposed components for the control of hemiparasitic weeds of the genus Striga in tropical cereal production systems. Neither of the two components alone is effective enough to prevent parasitism and concomitant crop losses. This review explores the potential of improved plant nutrition, being the chemical constituent of soil fertility, to fortify the expression of plant inherent resistance and tolerance against Striga. Beyond reviewing advances in parasitic plant research, we assess relevant insights from phytopathology and plant physiology in the broader sense to identify opportunities and knowledge gaps and to develop the way forward regarding research and development of combining genetics and plant nutrition for the durable control of Striga

Effect of Abiotic Stresses on the Nondestructive Estimation of Rice Leaf Nitrogen Concentration

Decision support tools for non-destructive estimation of rice crop nitrogen (N) status (e.g., chlorophyll meter [SPAD] or leaf color chart [LCC]) are an established technology for improved N management in irrigated systems, but their value in rainfed environments with frequent abiotic stresses remains untested. Therefore, we studied the effect of drought, salinity, phosphorus (P) deficiency, and sulfur (S) deficiency on leaf N estimates derived from SPAD and LCC measurements in a greenhouse experiment. Linear relations between chlorophyll concentration and leaf N concentration based on dry weight (N dw ) between SPAD values adjusted for leaf thickness and N dw and between LCC scores adjusted for leaf thickness and N dw could be confirmed for all treatments and varieties used. Leaf spectral reflectance measurements did not show a stress-dependent change in the reflectance pattern, indicating that no specific element of the photosynthetic complex was affected by the stresses and at the stress level applied. We concluded that SPAD and LCC are potentially useful tools for improved N management in moderately unfavorable rice environments. However, calibration for the most common rice varieties in the target region is recommended to increase the precision of the leaf N estimates

The nitrogen economy of rice-livestock systems in Uruguay

Over many decades there has been a global trend away from mixed farming and integrated crop-livestock systems to more-intensive single commodity systems. This has distorted local and global nutrient balances, resulting in environmental pollution as well as soil nutrient depletion. Future food systems should include integrated crop-livestock systems with tight nutrient budgets. For nitrogen (N), detailed understanding of processes, fluxes – including of gaseous forms – and budgets at a component level is needed to design productive systems with high N use efficiency (NUE) across the full nutrient chain. In Uruguay, a unique rice-livestock system has been practiced for over 50 years, attaining a high production level for rice (mean grain yields > 8 Mg ha−1) and an average level for livestock (120 kg liveweight gain ha−1 y−1). The aim of this study was to quantify the components of the N balance and NUE of this system, so as to understand its long-term sustainability, and draw conclusions for other regions. Analysis of country-level statistics for each component over the last 16 years shows tight N balances of +3.49, +2.20 and +2.22 kg N ha−1 yr−1 for rice, livestock and the whole system, respectively. Based on average values of N retained in edible food products, NUE values were 65.7, 13.2 and 23.1% for rice, livestock and the whole system, respectively. While NUE of livestock was unchanged over the period, NUE of the rice component decreased due to increasing fertiliser use. Further gains in N efficiency are possible by better integrating the system components. Actions to increase system level NUE include raising pasture and livestock productivity and controlling the increasing use of N fertilisers in rice. Tightly integrated crop-livestock systems can play a significant role in re-shaping global agriculture towards meeting food security, environmental and socioeconomic sustainability targets

Agricultural decision-making under uncertainty: a loss function on the kriging variance from soil properties predicted by infrared and X-ray fluorescence spectroscopy

Abstract and Presentatio

Spectral soil analysis for fertilizer recommendations by coupling with QUEFTS for maize in East Africa: A sensitivity analysis

Laboratory analysis of soil properties is prohibitively expensive and difficult to scale across the soils in sub-Saharan Africa. This results in a lack of soil-specific fertilizer recommendations, where recommendation can only be provided at a regional scale. This study aims to assess the feasibility of using spectral soil analysis to provide soil-specific fertilizer recommendations. Using a range of spectrometers [NeoSpectra Saucer (NIR), FieldSpec 4 (vis-NIR) with contact probe or mug light interface, FTIR Bruker Tensor 27 (MIR)], 346 archived soil samples (0–20 cm) with known soil chemical properties collected from Ethiopia, Kenya and Tanzania were scanned. Partial least square regression (PLSR) was used to develop prediction models for selected soil properties including pH, soil organic carbon (SOC), total nitrogen, Olsen P, and exchangeable K. These predicted properties, and associated uncertainty, were used to derive fertilizer recommendations for maize using the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model parameters for sub-Saharan Africa. Most soil properties (pH, SOC, total nitrogen, and exchangeable K) were well predicted (Concordance Correlation Coefficient values between 0.88 and 0.96 and Ratio of Performance to Interquartile values between 1.4 and 5.9) by all the spectrometers but there were performance variations between soil properties and spectrometers. Use of the predicted soil data for the development of fertilizer recommendations gave promising results when compared to the recommendations obtained with the conventional soil analysis. For example, the least performing NeoSpectra Saucer over/under-estimated up to 8 and 24 kg ha-1N and P, respectively, though there was insignificant variation in estimation of P fertilizer among spectrometers. We conclude that spectral technology can be used to determine major soil properties with satisfactory precision, sufficient for specific fertilizer decision making in East Africa, possibly even with portable equipment in the field