The environmental conditions and test duration in rainfall simulators have been major constraints to find reliable differences in preharvest sprouting (PHS) among wheat cultivars. This study aimed to elucidate the temperature conditions and degree-days (DD) that enable higher discrimination of genotypes in a PHS test. Thirteen genotypes with different degrees of PHS (BR 18, BRS 220, CD 104, CD 105, CD 108, CD 114, CD 116, Frontana, IPR 085, IPR 128, IPR 136, OR1 and Safira) were evaluated in a rainfall simulator, during four years, conducting two trials per year. The tests were carried on 20 spikes per cultivar, kept in a vertical position on Styrofoam plates, spaced 10 cm between rows and 5 cm within the row. The air temperature data were recorded on a thermograph and the DD were calculated from the mean daily air temperature assuming a base temperature of 4 °C. The Falling Number (FN) parameter and germination percentage (GP) data were averaged for each test. The temperatures (minimum, mean and maximum) and the DD were regressed and correlated with FN and GP. Any increase in the minimum and mean air temperature and accumulated DD decreased FN values and increased GP. Higher genotypic discrimination was achieved at an average air temperature of 21.5 °C and 35 DD. These values can be used as reference to set simulated rain testing condition for screening genotype for PHS based on FN or pericarp rupture of grains.

Applying stochastic frontier Cobb–Douglas production function, the study assessed the efficiency of sweet potato (Ipomoea batatas) producers in the Southern region of Ethiopia. The study revealed the existence of fairly large technical inefficiency in sweet potato production. The technical efficiency ranged from 12.6 to 93.7%, with more than half of the producers above the mean efficiency level (66.1%). This suggests that there is room for output gains through technical efficiency improvement. If the average producers in the study region are to achieve the technical efficiency level of the most efficient producer in the sample (93.7%), they can realize nearly 30% output gains. The analysis of allocative efficiency also revealed that sweet potato producers were producing sweet potato with sub-optimal utilization of production inputs, suggesting that potential for output gains remains to be exploited through reconfiguration of the existing resource use. They can make more value out of their sweet potato production by reconfiguring their current utilization of production inputs in favour of more land and manure but less seed rate. Furthermore, age and education are important determinants of the efficiency of sweet potato production. In view of these findings, it is advisable to put in place appropriate extension intervention programmes that enable sweet potato producers to exploit the potential gains in sweet potato output through technical and allocative efficiency improvement.

Biochar application appears to be a promising method to improve soil physicochemical and biological properties by increasing soil carbon. Along with the influence of hardwood biochar on wheat growth, yield and soil quality for a period of two years, this study also evaluates the major soil parameters to be taken as minimum data set while assessing the impact of hardwood biochar in an acidic sandy loam soil. Five fertilizer treatments combining inorganic fertilizers and biochar were applied: unfertilized control (T1); 100% NPK (T2); 5 Mg ha−1 biochar (T3); 100% NPK + 5 Mg ha−1 biochar (T4); and 50% N + 100% PK + 5 Mg ha−1 biochar (T5). Biochar application (T3 vs. T1; T4 and T5 vs. T2) significantly increased leaf chlorophyll content, net photosynthesis rate, leaf N concentration and above and below-ground biomass, with improved wheat yield and grain quality (total grain protein and carbohydrate). Soil pH, water-holding capacity, available nutrients (N, P and K), organic carbon and its fractions also enhanced in biochar applied plots with reduced bulk density. Increased activities of soil enzymes urease, phosphatase, dehydrogenase, fluorescein di-acetate and arylsulphatase were recorded in biochar treatment along with significant increase in N recovery index (22%) and agronomic efficiency (40%). Multivariate analysis identified activity of phosphatase, pH and humic acid to fulvic acid ratio as the indicators to explain the total variance from biochar addition in acidic sandy loam soil under wheat cultivation. Soil quality index showed a significant improvement when biochar was added with reduced N doses (T5). This study confirms the efficacy of biochar as a soil conditioner when applied with reduced N fertilizer and would be a sustainable option to improve wheat production and soil quality in acidic sandy loam soils of northeast India.

To explore effective ways to decrease soil CO2 emission and increase winter wheat grain yield in the North China Plain, a field experiment was conducted using two planting systems (wide-precision planting and conventional-cultivation planting) and two straw mulching rates (0 and 0.6 kg m−2) to study carbon emission, carbon cumulative emission flux, grain yield and yield carbon utilization efficiency. In the 2013–2014 and 2014–2015 winter wheat growing seasons, CO2 emission rate and cumulative CO2-C fluxes following straw mulching treatment were significantly lower than those following non-mulching treatments, whereas the yield carbon utilization efficiency was significant higher following straw mulching treatment. Straw mulching significantly reduced winter wheat grain yield, which was mainly due to the significant decrease in spike numbers and 1000-kernel weight. However, wide-precision planting system significantly increased winter wheat grain yields by increasing spike numbers under straw mulching conditions. Therefore, wide-precision planting system could compensate for the reduction in winter wheat grain yield under carbon sequestration conditions in the North China Plain.

Canopy normalized difference vegetation index (NDVI), soil plant analysis development (SPAD) reading and petiole sap NO3−‒N concentration are increasingly used as quick and non-destructive methods to monitor plant N nutrition and growth status and predict yield of crops. However, little information is available on the comparisons of these three methods in assessing N nutrition, growth and yield for cotton (Gossypium hirsutum L.). Four N rates (0, 34, 67 and 101 kg N ha−1) under two cover conditions [no cover crop and hairy vetch (Vicia villosa) crop] in a 33-year long-term field trial were used to evaluate how canopy NDVI, SPAD reading (related to chlorophyll content) and petiole sap NO3−‒N concentration (conventional method) are able to assess N nutrition and plant biomass and predict yield for cotton. Canopy NDVI and SPAD readings responded less sensitively to N rates than petiole sap NO3−‒N. The responses of NDVI and SPAD reading to N rates were generally reduced due to the winter cover crop with hairy vetch. Significant and positive correlations existed mostly among NDVI, SPAD reading, and petiole sap NO3−‒N concentration. Canopy NDVI during mid-bloom to late bloom and SPAD reading during early bloom to late bloom were effective alternative methods for assessing cotton N nutrition status. The SPAD reading at late bloom was an effective parameter to estimate cotton biomass. The NDVI at early square and SPAD reading during early square to mid-bloom were effective for cotton yield prediction.

Indigenous crops, such as jute mallow (Corchorus olitorius L.) have high potential for improving nutrient efficiency and income source diversification of farmers in sub-Saharan Africa. A better understanding of plant responses to nitrogen (N) is essential in shedding light on the trend towards increasing fertilizer applications for commercially grown jute mallow. The aim of this study was to determine the critical N dilution curve in order to assess the N nutrition index (NNI) in jute mallow in southern Benin. Above-ground dry matter (DM) and N concentration were determined weekly during the 2010 and 2011 growing seasons and six N treatments of 0, 30, 60, 120, 180 or 240 kg N ha−1 were tested under irrigated conditions. A critical N curve (Nc = 3.35 W−0.18), where W is the DM in Mg per ha, was plotted based on the N concentration in the whole plant. The critical N concentration (Nc) represents the minimal N concentration required to achieve maximum growth. According to significant differences in DM at each sampling date, data points were divided into two groups representing either N deficient or N excess conditions. All data points in the N deficient group were under the critical N curve and most data points in the N excess group were on or above the critical N curve, therefore confirming the validity of the critical N curve determined in southern Benin. The NNI calculated as the ratio between the measured N concentration and predicted Nc, ranged from 0.55 to 1.30. The equation for the critical N curve and NNI determined in this study for jute mallow could potentially be used as a parameter for N application under non-deficient water conditions in southern Benin.

Determination of canopy resistance (rc) is necessary for accurate estimating hourly latent heat flux (LET), using the Penman–Monteith (PM) model for tea crop. In this study, a non-linear relationship between rc and climatic resistance (r*) was obtained for tea plants based on micro-meteorological data and LET from the end of 2014 to the beginning of 2016 in southern China. The proposed rc model was integrated to the PM method and compared with measured LET using a Bowen ratio energy balance method. The root mean square error (RMSE) and the index of agreement (d) were calculated for assessing the accuracy of the proposed rc model. RMSE and d values for rc and LET were 167.4 s m−1 and 29.7 W m−2 and 0.93 and 0.99, respectively. As compared to data from a single season, the rc sub-model based on data from different seasons was more reliable for estimating LET of tea field when integrated to the PM model.

Deficiencies of micro (Zn, B) and secondary (S) nutrients are well-documented in soil as well as in cereal crops, leading to decreased crop yields and low nutritional quality of food. We evaluated the effects of coated urea on maize yield, N and Zn uptake, and input cost relationships. Field experiments were conducted on maize to test boron-coated (BCU), sulphur-coated (SCU) and zinc-coated urea (ZnCU) during 2013 and 2014. On the basis of 2 years’ average data, the highest grain yield was achieved with 0.5% BCU, 5% SCU and 2.5% ZnCU as zinc sulphate hepta hydrate. These treatments increased yields by 5.4, 12.8 and 9.9% over prilled urea (PU), respectively. Application of 0.5% BCU (supplying 1.4 kg B ha−1), 5% SCU (supplying 14.1 kg S ha−1) and 2.5% ZnCU (supplying 7.05 kg Zn ha−1) registered the highest N concentrations and uptake in grain and stover. Total N uptake (grain + stover) was increased by 7.6, 16.7 and 17.1% with BCU, SCU and ZnCU treatments over PU. As compared to PU, Zn concentration in maize grain was significantly higher and total Zn uptake (grain + stover) increased by 32.4% with 2.5% ZnCU. Coated urea materials also enhanced the partial factor productivity (PFPN), agronomic efficiency (AEN), recovery efficiency (REN) and harvest index (HIN) over those of PU. From the economic viewpoint this study suggests that coating of urea with 0.3% boron, 5% sulphur or 2% zinc gives maximum net returns and benefit-cost ratio. Our data indicate that coating of B, Zn and S onto urea increases maize yield, profitability and nitrogen use efficiency in the western Indo-Gangetic plains of India.

Genotype by environment (G x E) interactions for grain yield were investigated in 13 perennial rice (Oryza sativa L./Oryza longistaminata) derivatives over three sites and 2 years in Lao PDR. Genotype accounted for 29.0% of the total sum of squares, with environment and the G x E interaction responsible for 60.2 and 10.8%, respectively. Cluster analysis identified three environment and six genotype groups, which accounted for 49.7, 98.0 and 42.8% of the E, G and G x E sums of squares, respectively. Principal component axes 1, 2 and 3 accounted for 54.0, 30.6 and 11.7% of the G x E sum of squares, respectively, with PCA1 indicating yield potential, PCA2 timing of cessation of rainfall in the 2011 wet season, and PCA3 environmental stresses affecting regrowth in the 2012 wet season. Genotype groups differed in adaptation to these contrasting conditions. G6 (Line 213, 240 and RD23) was widely adapted to all environments, with G5 (Line 248) being especially adapted to the 2012 environments. G3 and G4 were neutral, though G3 (Line 53) showed some preference for the Na Pok environments. G1 and G2 were poorly adapted everywhere, with the tall and late G1 (Line 11) being especially poor at Na Pok 2011 in a dry finish. While yields were lower in 2012, all derivatives survived the dry season with access to life-saving irrigation. This is promising, as the annual rice RD23 was unable to ratoon under these conditions, and had to be re-sown. Importantly, Line 213, 240 and 248 yielded comparably to RD23 from regrowth in 2012. Development of perennial rice should target rainfed and especially upland environments.

This study was aimed at comparing in-field parameters and remote sensing NDVI (normalized difference vegetation index) by both satellite (SAT) and unmanned aerial vehicle (UAV) for the assessment of early nitrogen (N) status and prediction of yield in winter wheat (Triticum aestivum L.). Six increasing N rates, i.e., 0, 40, 80, 120, 160, 200 kg N ha−1 were applied, half at tillering and half at shooting. Thus, when the crop N status was monitored between the two N applications, consecutive N treatments differentiated from each other by just 20 kg N ha−1. The following in-field and remote sensed parameters were compared as indicators of crop vegetative and N status: plant N% (w:w) concentration; crop N uptake (Nupt); ratio between transmitted and incident photosynthetically active radiation (PARt/PARi); leaf SPAD values, an indirect index for chlorophyll content; SAT and UAV derived NDVI. As reliable indicators of wheat N availability, in-field parameters were ranked as follows: PARt/PARi ≅ Nupt > SPAD ≅ N%. The PARt/PARi, Nupt and SPAD resulted quite strongly correlated to each other. At all crop stages, the NDVI was strongly correlated with PARt/PARi and Nupt. It is of relevance that NDVI correlated quite strongly to in-field parameters and grain yield at shooting, i.e., before the second N application, when the N rate can still be adjusted. The SAT and UAV NDVIs were strongly correlated to each other, which means they can be used alternatively depending on the context.

Reducing the emissions of greenhouse gases (GHG) from paddy fields is crucial both for the sustainability of rice production and mitigation of global climatic warming. The effects of applying industrial and agricultural wastes as fertilizer on the reduction of GHG emissions in cropland areas, however, remain poorly known. We studied the effects of the application of 8 Mg ha−1 of diverse wastes on GHG emission and rice yield in a subtropical paddy in southeastern China. Plots fertilized with steel slag, biochar, shell slag, gypsum slag and silicate and calcium fertilizer had lower total global-warming potentials (GWP, including CO2, CH4 and N2O emissions) per unit area than control plots without waste application despite non-significant differences among these treatments. Structural equation models showed that the effects of these fertilization treatments on gas emissions were partially due to their effects on soil variables, such as soil water content or soil salinity. Steel slag, biochar and shell slag increased rice yield by 7.1%, 15.5% and 6.5%, respectively. The biochar amendment had a 40% lower GWP by Mg−1 yield production, relative to the control. These results thus encourage further studies of the suitability of the use waste materials as fertilizers in other different types of paddy field as a way to mitigate GHG emissions and increase crop yield.