International Journal of Plant Production
Volume:14 Issue: 4, Dec 2020

Pulses are smart crops both for humans and the cropping system as they provide protein, minerals, vitamins, and fiber for human diet and nitrogen to the soil and contribute to the maintenance of biodiversity. Pulses, also called grain legumes, contribute about 33% of the global dietary protein requirement of the human population. In Pakistan, the production of pulses is far less than the requirement and the balance is met through imports. The reasons for low production and yield of pulses, in Pakistan, include lack of innovative crop improvement programs and seed distribution system. Currently, about 80% of the pulses are cultivated from the farmers own saved seed. Other major factors responsible for low production and yield are abiotic (drought, heat, salinity) and biotic (weeds, diseases, and insect-pests) stresses, and factors related with soil (marginal lands, alkaline soils with low organic matter and erosion), climate change, lack of crop-specific farm machinery, post-harvest losses and marketing issues. This manuscript discusses the current status, constraints, and opportunities to improve the production of pulses to meet the national requirements. The major opportunities to improve the pulses production includes crop improvement (development of short duration, high yielding, disease resistant and climate resilient varieties), intercropping and growing of pulses as catch crop, adoption of conservation agriculture to conserve the resources, strengthening system of certified seed distribution, provision of crop-specific farm machinery, development and dissemination of site-specific production technologies and seed enhancements.

Promiscuous soybeans are grain legumes that nodulate with diverse strains of indigenous Bradyrhizobium and play a significant role in biological nitrogen fixation through symbiosis. However, experiments on the potential use of promiscuous soybean varieties have recorded very low nodulation and poor nitrogen fixation probably due to ineffective native Bradyrhizobium isolates. Experiments were designed to investigate symbiotic nitrogen fixation of two promiscuous soybean varieties (SB8 and SB126) with indigenous Bradyrhizobium isolates in contrasting agroclimatic zones through greenhouse and field experiments. Inoculation of soybeans in the greenhouse had a significant (p < 0.001) effect on shoot and nodule dry weight. The best performing indigenous isolates RI9 and RI4 from the greenhouse study outperformed the commercial inoculant (Biofix) in symbiotic effectiveness with 119.17%, 142.35% and 101.01%, respectively. Inoculation in the field experiments showed a significant (p < 0.0001) increase in shoot dry weight and grain yield of promiscuous soybean. Agroclimatic zones showed significant (p < 0.0001) variability in above ground biomass of soybean due to inoculation. Despite the apparent promiscuity of the soybean varieties used, the response in nodulation suggests the cultivars grown under contrasting agroclimatic zones have a preference to specific Bradyrhizobium isolates.

Maize can be sown in spring and fall seasons in Pakistan under maize–maize cropping system. Due to seasonal variability in meteorological parameters, optimization of planting time for maize hybrids is vital to harvest improved productivity in maize-maize system. This study was designed to explore the effect of diverse sowing dates on phenology, growing degree days (GDDs), photo-thermal-units (PTUs) and helio-thermal-units (HTUs), and its impact on radiation-use-efficiency (RUE) and grain yield (GY) in different maize hybrids under maize-maize cropping system. Two-year experiments were conducted to optimize planting dates for hybrids during 2016 and 2017. In spring, three hybrids were sown on Jan 15, Feb 5, Feb 25, Mar 15 and Apr 05. During fall, three hybrids were planted on Jun 15, Jul 05, Jul 25, Aug 15 and Sept 05. Results showed that spring early (Jan 15), while fall late (Jul 25) sowing took more days to complete 50% tasseling, silking and maturity. However, maize sown on Feb 05 and Jul 25 accumulated more GDDs to attain 50% tasseling, silking and maturity. Maize sown on Feb 05 and Jul 25 had more leaf area index (LAI), crop growth rate (CGR), RUE and GY, which was linked with higher accrual of GDDs, PTUs and HTUs. Likewise, hybrids P-33M15 and P-30R50, during spring and fall observed higher values of all above cited traits. Moreover, positive-correlation was witnessed among days taken to complete different phenophases, LAI, CGR and 1000-grain weight, total biomass, GY and RUE. However, higher GY and RUE was obtained in spring than fall. In conclusion, maize sown on Feb 05 and Jul 25 using hybrids P-33M15 and P-30R50, during spring and fall crops, respectively produced more GY and higher RUE due to more accumulation of GDDs, PTUs and HTUs. Thus the spring season seemed more productive than fall season under maize-maize cropping system.

The wheat production variability is not well-understood in hilly region, especially in loess-derived soils of Golestan province in Iran with a sub-humid climate. Topography can greatly influence the production of agricultural crops by affecting soil quality. A study area located in Golestan province was selected in order to assess the spatial variability of wheat production and to develop regression models between the crop, soil properties, and topography attributes. The samples of wheat and soil were randomly taken from 100 points at different hillslope positions (i.e., shoulder, back-, foot-, and toe-slope). The soil physicochemical analysis and the measurement of wheat yield components were conducted. The digital elevation model (DEM; 10 m resolution) was used, and the topographic attributes (i.e., elevation, slope, wetness index, stream power index, curvature, erosivity factor, and watershed specific area) were calculated. The results showed that the greatest total yield and the highest grain yield were estimated to be 14.53 and 4.41 ton ha−1, respectively, in areas with a slope of less than 10%, which were significantly higher than those in the steep areas (slope classes of 10–30% and > 30%). The highest and the lowest total yields, with average values of 15.82 and 5.68 ton ha−1, were observed in the toeslope and shoulder slope positions, respectively. The greatest grain yields were obtained from the foot- and toeslope positions with the average values of 4.61 and 4.66 ton ha−1, respectively. The topographic curvature and wetness index had a significant correlation with the yield of wheat. According to the regression equations, topographic indexes can well justify the spatial variability of wheat yield, indicating the importance of these factors by influencing the distribution of moisture during the process of wheat production in the study region. The enhancements of wheat yield components in the lower slope positions could be attributed to an increase in soil depth and plant available water as well as to the accumulation of further soil organic matter and nutrient elements, including nitrogen and potassium, in such positions as a result of soil redistribution. Moreover, the results illustrated that by using easy accessable, cheap, and none destructive data (DEM derivatives and soil properties); it is possible to predict the production yield of wheat with a reliable estimation. We concluded that for better farming management and productivity in hilly regions, topographic attributes should be considered for plantation. Therefore, this study introduces the most suitable slope positions and topographic attributes for crop production with the least soil degradation. Shoulder and backslope positions are the most unsuitable slopes possibly better for orchards while toeslopes and footslopes could be used for intensive crop production.

The availability of water and nitrogen (N) to maize during its flowering stage affects the growth of individual kernels. The present study reports the variability of maize kernel dry weight under different levels of water and N applications. Two consecutive-year experiments were conducted during 2009 and during 2010 to study the interaction between three irrigation regimes and five N application rates on weekly maize kernel growth. Logistic and regression equations were fitted to kernel moisture content and kernel dry weight as a function of thermal time (TT) during critical crop stages. Kernel moisture content and growth rate increased non-linearly from 1 week after silking to physiological maturity. By applying logistic function we were able to improve simulation of kernel moisture content and daily increases in kernel dry weight. The logistic curve showed kernel moisture contents linearly correlated with kernel dry weight. Similarly, regression analyses of kernel dry weight showed a significant positive correlation with kernel moisture content for the 2009 (R2 = 0.86 NRMSE = 23%) and 2010 growing seasons (R2 = 0.92; NRMSE = 19%). Therefore, the logistics curves derived from the observed data may be helpful for predicting daily kernel growth for the semi-arid conditions. The results showed that the optimal N rate for maximum kernel dry weight was 250 kg ha−1 under 525 mm delta of water application ha−1. This rate might be considered in formulating good agricultural practices for optimum maize kernel growth in the semi-arid regions. Thus, our results contribute to better understanding of best management practices of N fertilizer and irrigation water for optimum maize productivity under semiarid region.

Water scarcity is the major limiting factor to crop production in arid and semi-arid regions. Better understanding the response of crops to the time and intensity of water stress at different growth stages is helpful to optimize irrigation scheduling under water limited conditions. A 4-year (2013–2016) field experiment was conducted at Yangling on the Loess Plateau, to quantify the effects of timing and intensity of water stress on yield, actual evapotranspiration (ETa) and water use efficiency (WUE) of summer maize, and to identify the most sensitive stage of maize to water stress. Two deficit irrigation levels, i.e. 70 mm and 110 mm, were considered. For each irrigation level, irrigation was applied for any three of four key growth stages of maize: seedling (D1), jointing (D2), tasseling (D3) and grain filling (D4). The results showed that: (1) water stress at vegetative growth stages had higher yield response factors than that at reproductive growth stages, indicating the former tended to have greater effects on maize yield; (2) although maize yield increased linearly with ETa, the variations of yield and WUE with changed ETa were not synchronous. Low-level irrigation should be applied in the regions with severe water shortage to obtain the maximum WUE, while in regions with more water a crop can be irrigated based on sufficient irrigation scheduling; (3) the contour map of Yield-ETa-WUE indicated a greater effect of yield on WUE than that of ETa on WUE. When irrigation water is limited, high WUE can be achieved if it is applied at vegetative growth stages, while high yield can be achieved if more available water is applied at tasseling stage. Therefore, in order to develop a sustainable irrigation scheduling on the Loess Plateau, water availability and agriculture production goals (high WUE or high yield) should be taken into account together.

Crop production depends on the interaction of climatic factors and agricultural management, such as nitrogen (N) fertilizer input in agricultural ecosystems. Understanding crop yield responses to climatic factors and N fertilizer supply can help select appropriate cultivars and develop appropriate measures to achieve the high and stable crop yield. In this study, a long-term N fertilizer experiment was conducted consisting of two crops (winter wheat and summer maize) from 1992 to 2014, to investigate the crop yield response to climatic factors and N treatments in Hotan, Xinjiang Uygur autonomous region. A long-term N supplied and without N supplied treatments significantly affect the soil properties and crop yields. It was found that low N stress significantly reduced the grain yield ranged from 33.1 to 76.4% and 26.8 to 69.3% for winter wheat and summer maize respectively. The grain N concentration was significantly reduced with the increase in N stress. There was positive correlation between crop yield and accumulated temperature (R2 = 0.58, P < 0.001) under high N conditions, and negative correlation (R2 = 0.50, P < 0.001) under low N conditions. Our result shows that the accumulated temperature is gradually increasing from 4051 to 5218 °C year−1 in the past 23 years (1992–2014) in Xinjiang Uygur autonomous region. Under sufficient N supplied conditions, the increase of accumulated temperature positively promote crop yields. However, under N deficient conditions, increasing accumulated temperature will further exacerbate the N stress effect and reduce crop yields. Hence, we recommended sufficient N fertilizer input in Hotan, Xinjiang region, which can maintain higher crop yield.

Climate models indicate that increasing atmospheric concentrations of greenhouse gases (GHG), mainly CO2, will alter climate by increasing temperatures and changing rainfall patterns. Considering that potato crop stands out as the most important non-grain crop in the world, it is imperative to understand how climate change will impact this crop and how it will affect global food security. In this sense, crop simulation models are useful tools to estimate crop growth, development and yield in response to climatic conditions, soils, genotype and crop management. Among the several potato crop simulation models, DSSAT-SUBSTOR-Potato is the main one and widely used around the world. The aim of this study was to validate this model for Brazilian conditions and used it to simulate the impacts of projected climate change on potato crop in the main Brazilian producing regions, for different growing seasons, considering an ensemble of different general circulation models, projected for 2040–2069 and 2070–2099 periods, under two GHG Representative Concentration Pathways (RCP4.5 and RCP8.5). The results showed that Brazil will have warmer climate with wetter conditions in the south and less rainfall in the north, which will impact potato crop in different ways, depending on the producing region and growing season. In Southern Brazil, future climate will benefit potato yield, mainly during the 3rd growing season. On the other hand, locations with warmer and drier climates will have lower potato yields in relation to the present, mostly during the 1st growing season, when extremely high temperatures and water deficit will limit plants’ growth. These impacts will be less expressive in the most optimist scenario (RCP4.5), while more intense yield losses are expected under the RCP8.5 in the end of the century.

Sugar beet is an important economic crop in Northwest China. In this area, efficient use of nitrogen (N) fertilizer has become crucial due to decreased profits associated with both under- and oversupply relative to sugar beet requirements. Thus, fast and non-destruction diagnostic tools for estimating plant N status have an important role in reducing N inputs while maintaining sugar beet yield and qualify. The objective of our study was to quantify leaf color characterization of sugar beet with an inexpensive scanner and establish the relationship with yield, leaf nitrogen content (LNC), plant total nitrogen content (PTNC), chlorophyll content (CC), soil nitrate nitrogen content (SNNC) and soil plant analysis development (SPAD) readings in sugar beet. In 2017 and 2018, field experiments were conducted with five N treatments ranging from 0 to 180 kg N ha−1. The main results showed the following: The SPAD readings (SPR) and CC exhibited a significant or highly significant correlation (maximum = 0.70, P < 0.01), both of which reflected well the N nutrient status of the entire plant. Furtherly, a detailed association analysis revealed that there was a close relationship (maximum = − 0.63, P < 0.01) of LNC, SPR, PTNC, CC and yield with leaf color parameter Red/Blue (R/B), which was recommended as leaf color parameters for N diagnosis in sugar beet. In addition, based on the distribution of R/B value under different N rate, the yield was low with greater R/B value than 1.36 indicating an insufficient N supply, and with the R/B value was lower than 1.36, the theoretical yield reached its peak indicating an adequate supply of N fertilizer. To summarize, compared to the complicated and expensive of hyperspectral and other remote sensing technologies, scanned leaf image (SLI) processing technique was a simple, inexpensive and reliable method of determining sugar beet N status that has potential as a diagnostic tool for determining crop N requirement.

Soil information is a vital input for crop models applications in various large area studies including climate change impact and food security. One of the global soil databases that provide full information for crop models is HC27 of IFPRI. The quality of the database has not been assessed for crop modeling so far. A tested crop simulation model (SSM-iCrop2) was used for this purpose that needs soil water related properties (i.e., depth, albedo, curve number for runoff, drainage coefficient, and soil water limits at saturation, drained upper limit and lower limit) for the simulation of crop properties. Actual data of two soil profiles from three different climate zones (locations) were used as model inputs to simulate potential yield, evapotranspiration (under rainfed conditions) or net irrigation water requirement (under irrigated conditions) of some important plant species (alfalfa, sugar beet, sugar cane, wheat, olive, soybean, apricot and chickpea) under rainfed and irrigated conditions of Iran. Results showed that the application of HC27 soil information in the SSM-iCrop2 model resulted in model output that was not different from the model output with actual soil information with respect to mean, variance, and distribution. No statistically significant difference was found in the simulation of various combinations of soil profiles-plant species-locations. It was concluded that HC27 information can be used in simulation studies with SSM-iCrop2 or other similar simple models for the simulation of potential yield, net irrigation water, or evapotranspiration that are commonly required for food security and climate change studies.

Cropland forms the material basis for human survival and is an important determinant of national food security. Cropland net primary productivity, which is the basis of food production and an important indicator of cropland productivity, reflects the production capacity of crops under natural conditions. However, currently, only limited knowledge was available on the relationship among cropland area, cropland management measures, and cropland productivity in China. Hence, in the current study, we used the panel data model to quantify the effects of cropland area and various cropland management measures (e.g., fertilizer use, irrigation area, agricultural machinery power, pesticide use, and agricultural film use) on cropland total net primary productivity (TNPP). Results revealed that for the entire cropland in China, an increase in cropland area, fertilizer use, agricultural machinery power, pesticide use, and agricultural film use increased cropland TNPP, whereas an increase in irrigation area decreased cropland TNPP. Further, in grain-producing areas, an increase in cropland area, fertilizer use, irrigation area, agricultural machinery power, pesticide use, and agricultural film use resulted in an increase in cropland TNPP. Moreover, in grain-balanced areas, an increase in cropland area, fertilizer use, pesticide use, and agricultural film use led to an increase in cropland TNPP, while an increase in irrigation area and agricultural machinery power reduced cropland TNPP. Finally, in grain-consuming areas, increases in cropland area, irrigation area, pesticide use, and agricultural film use caused an increase in cropland TNPP, whereas increases in fertilizer use and agricultural machinery power reduced cropland TNPP. Therefore, it is necessary to prevent the encroachment of fertile cropland and, simultaneously, implement scientific management measures based on local conditions in croplands.

The common bean grown under straw of intercropped plants improves the cropping environment in no-tillage systems. In addition, nutrient supply from straw could reduce the use of topdressing nitrogen in common bean. Thus, the objective of this work was to evaluate under no-tillage system the effect of straw type and topdressing nitrogen doses in the irrigated common bean productive and qualitative attributes. The experimental design was in randomized blocks arranged in split-plots with four replications. The plots were composed by three straw types from different cropping systems, represented by sole maize, maize-intercropped with brachiaria and maize-intercropped with crotalaria. The subplots consisted of five topdressing N doses applied on common bean 0, 50, 100, 150 and 200 kg ha−1 of nitrogen via urea (coated with polymers). The common bean grown under the straw of maize intercropped with crotalaria showed higher number of pods per plant, grain yield and lower time for maximum grain hydration when compared to those plants grown under the straw of sole maize. Moreover, the crude protein content in the common bean grains was greater when plants were grown under the straw of maize intercropped with crotalaria than the straw of maize intercropped with brachiaria. The agronomic efficiency of common bean was higher when the plants were grown under the straw of maize intercropped with crotalaria in the lowest nitrogen fertilization rate tested (50 kg ha−1). Leaf nitrogen content, grain yield, sieve yield and crude protein content in the grain increased with increasing nitrogen availability via topdressing. Therefore, the results suggest that agronomic and qualitative characteristics of common bean are benefited when cultivated on the maize straw combined with crotalaria even reducing up to 50% the requirement of nitrogen fertilization.